AHCI RESEARCH GROUP
Publications
Papers published in international journals,
proceedings of conferences, workshops and books.
OUR RESEARCH
Scientific Publications
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You can use the tag cloud to select only the papers dealing with specific research topics.
You can expand the Abstract, Links and BibTex record for each paper.
2018
Nuccio, Carlo; Augello, Agnese; Gaglio, Salvatore; Pilato, Giovanni
Interaction Capabilities of a Robotic Receptionist Journal Article
In: Smart Innovation, Systems and Technologies, vol. 76, pp. 171–180, 2018, ISSN: 21903018.
Abstract | Links | BibTeX | Tags: Anthropomorphic Robots, Computational Creativity, Human computer interaction, Human Robot Interaction, Humanoid Robots, Ontologies, Robotics
@article{nuccioInteractionCapabilitiesRobotic2018,
title = {Interaction Capabilities of a Robotic Receptionist},
author = { Carlo Nuccio and Agnese Augello and Salvatore Gaglio and Giovanni Pilato},
editor = { Giuseppe De Pietro and Luigi Gallo and Robert J. Howlett and Lakhmi C. Jain},
doi = {10.1007/978-3-319-59480-4_18},
issn = {21903018},
year = {2018},
date = {2018-01-01},
journal = {Smart Innovation, Systems and Technologies},
volume = {76},
pages = {171--180},
abstract = {A system aimed at facilitating the interaction between a human user and an humanoid robot is presented. The system is suited to answer questions about laboratories activities, people involved, projects, research themes and collaborations among employees. The task is accomplished by the HermiT reasoner invoked by a speech recognition module. The system is capable of navigating a specific ontology making inference on it. The presented system is part of a broader social robot framework whose goal is to give the user a fulfilling social interaction experience, driven by the perception of the robot internal state and involving intuitive and computational creativity capabilities. textcopyright Springer International Publishing AG 2018.},
keywords = {Anthropomorphic Robots, Computational Creativity, Human computer interaction, Human Robot Interaction, Humanoid Robots, Ontologies, Robotics},
pubstate = {published},
tppubtype = {article}
}
A system aimed at facilitating the interaction between a human user and an humanoid robot is presented. The system is suited to answer questions about laboratories activities, people involved, projects, research themes and collaborations among employees. The task is accomplished by the HermiT reasoner invoked by a speech recognition module. The system is capable of navigating a specific ontology making inference on it. The presented system is part of a broader social robot framework whose goal is to give the user a fulfilling social interaction experience, driven by the perception of the robot internal state and involving intuitive and computational creativity capabilities. textcopyright Springer International Publishing AG 2018.
Nuccio, Carlo; Augello, Agnese; Gaglio, Salvatore; Pilato, Giovanni
Interaction capabilities of a robotic receptionist Journal Article
In: Smart Innovation, Systems and Technologies, vol. 76, pp. 171–180, 2018, ISSN: 21903018.
Abstract | Links | BibTeX | Tags: Anthropomorphic Robots, Computational Creativity, Human computer interaction, Human Robot Interaction, Humanoid Robots, Ontologies, Robotics
@article{nuccio_interaction_2018,
title = {Interaction capabilities of a robotic receptionist},
author = {Carlo Nuccio and Agnese Augello and Salvatore Gaglio and Giovanni Pilato},
editor = {Giuseppe De Pietro and Luigi Gallo and Robert J. Howlett and Lakhmi C. Jain},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85020412736&doi=10.1007%2f978-3-319-59480-4_18&partnerID=40&md5=36826af104eeb18f5d3fe6ff7ef1c18f},
doi = {10.1007/978-3-319-59480-4_18},
issn = {21903018},
year = {2018},
date = {2018-01-01},
journal = {Smart Innovation, Systems and Technologies},
volume = {76},
pages = {171–180},
abstract = {A system aimed at facilitating the interaction between a human user and an humanoid robot is presented. The system is suited to answer questions about laboratories activities, people involved, projects, research themes and collaborations among employees. The task is accomplished by the HermiT reasoner invoked by a speech recognition module. The system is capable of navigating a specific ontology making inference on it. The presented system is part of a broader social robot framework whose goal is to give the user a fulfilling social interaction experience, driven by the perception of the robot internal state and involving intuitive and computational creativity capabilities. © Springer International Publishing AG 2018.},
keywords = {Anthropomorphic Robots, Computational Creativity, Human computer interaction, Human Robot Interaction, Humanoid Robots, Ontologies, Robotics},
pubstate = {published},
tppubtype = {article}
}
A system aimed at facilitating the interaction between a human user and an humanoid robot is presented. The system is suited to answer questions about laboratories activities, people involved, projects, research themes and collaborations among employees. The task is accomplished by the HermiT reasoner invoked by a speech recognition module. The system is capable of navigating a specific ontology making inference on it. The presented system is part of a broader social robot framework whose goal is to give the user a fulfilling social interaction experience, driven by the perception of the robot internal state and involving intuitive and computational creativity capabilities. © Springer International Publishing AG 2018.
2016
Augello, Agnese; Maniscalco, Umberto; Pilato, Giovanni; Vella, Filippo
Disaster Prevention Virtual Advisors through Soft Sensor Paradigm Journal Article
In: Smart Innovation, Systems and Technologies, vol. 55, pp. 619–627, 2016, ISSN: 21903018.
Abstract | Links | BibTeX | Tags: Artificial intelligence, Conversational Agents, Decision Support Systems, Disaster Prevention, Human computer interaction, Natural Language Processing, Ontologies, Sensor systems
@article{augelloDisasterPreventionVirtual2016,
title = {Disaster Prevention Virtual Advisors through Soft Sensor Paradigm},
author = { Agnese Augello and Umberto Maniscalco and Giovanni Pilato and Filippo Vella},
editor = { Giuseppe De Pietro and Luigi Gallo and Robert J. Howlett and Lakhmi C. Jain},
doi = {10.1007/978-3-319-39345-2_55},
issn = {21903018},
year = {2016},
date = {2016-01-01},
journal = {Smart Innovation, Systems and Technologies},
volume = {55},
pages = {619--627},
abstract = {In this paper we illustrate the architecture of an intelligent advisor agent aimed at limiting, or as far as possible preventing, the damages caused by catastrophic events, such as floods and landslides. The agent models the domain and makes forecasting by exploiting both ontology models and belief network models. Furthermore, it uses a monitoring network to recommend preventive measures and giving alerts, if necessary, before that the event happens. The monitoring network can be implemented through both physical and soft sensors: this choice makes the measurements more adequate and available also in case of failure of some of the physical sensors. The front-end of the agent is made by a chat-bot, capable to interact with human users using natural language. textcopyright Springer International Publishing Switzerland 2016.},
keywords = {Artificial intelligence, Conversational Agents, Decision Support Systems, Disaster Prevention, Human computer interaction, Natural Language Processing, Ontologies, Sensor systems},
pubstate = {published},
tppubtype = {article}
}
In this paper we illustrate the architecture of an intelligent advisor agent aimed at limiting, or as far as possible preventing, the damages caused by catastrophic events, such as floods and landslides. The agent models the domain and makes forecasting by exploiting both ontology models and belief network models. Furthermore, it uses a monitoring network to recommend preventive measures and giving alerts, if necessary, before that the event happens. The monitoring network can be implemented through both physical and soft sensors: this choice makes the measurements more adequate and available also in case of failure of some of the physical sensors. The front-end of the agent is made by a chat-bot, capable to interact with human users using natural language. textcopyright Springer International Publishing Switzerland 2016.
Augello, Agnese; Maniscalco, Umberto; Pilato, Giovanni; Vella, Filippo
Disaster prevention virtual advisors through soft sensor paradigm Journal Article
In: Smart Innovation, Systems and Technologies, vol. 55, pp. 619–627, 2016, ISSN: 21903018.
Abstract | Links | BibTeX | Tags: Artificial intelligence, Conversational Agents, Decision Support Systems, Disaster Prevention, Human computer interaction, Natural Language Processing, Ontologies, Sensor systems
@article{augello_disaster_2016,
title = {Disaster prevention virtual advisors through soft sensor paradigm},
author = {Agnese Augello and Umberto Maniscalco and Giovanni Pilato and Filippo Vella},
editor = {Giuseppe De Pietro and Luigi Gallo and Robert J. Howlett and Lakhmi C. Jain},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84977119923&doi=10.1007%2f978-3-319-39345-2_55&partnerID=40&md5=a54a699ddea48ce7e9ab353ef5ce4ba0},
doi = {10.1007/978-3-319-39345-2_55},
issn = {21903018},
year = {2016},
date = {2016-01-01},
journal = {Smart Innovation, Systems and Technologies},
volume = {55},
pages = {619–627},
abstract = {In this paper we illustrate the architecture of an intelligent advisor agent aimed at limiting, or as far as possible preventing, the damages caused by catastrophic events, such as floods and landslides. The agent models the domain and makes forecasting by exploiting both ontology models and belief network models. Furthermore, it uses a monitoring network to recommend preventive measures and giving alerts, if necessary, before that the event happens. The monitoring network can be implemented through both physical and soft sensors: this choice makes the measurements more adequate and available also in case of failure of some of the physical sensors. The front-end of the agent is made by a chat-bot, capable to interact with human users using natural language. © Springer International Publishing Switzerland 2016.},
keywords = {Artificial intelligence, Conversational Agents, Decision Support Systems, Disaster Prevention, Human computer interaction, Natural Language Processing, Ontologies, Sensor systems},
pubstate = {published},
tppubtype = {article}
}
In this paper we illustrate the architecture of an intelligent advisor agent aimed at limiting, or as far as possible preventing, the damages caused by catastrophic events, such as floods and landslides. The agent models the domain and makes forecasting by exploiting both ontology models and belief network models. Furthermore, it uses a monitoring network to recommend preventive measures and giving alerts, if necessary, before that the event happens. The monitoring network can be implemented through both physical and soft sensors: this choice makes the measurements more adequate and available also in case of failure of some of the physical sensors. The front-end of the agent is made by a chat-bot, capable to interact with human users using natural language. © Springer International Publishing Switzerland 2016.
2014
Augello, Agnese; Pilato, Giovanni; Vassallo, Giorgio; Gaglio, Salvatore
Chatbots as Interface to Ontologies Journal Article
In: Advances in Intelligent Systems and Computing, vol. 260, pp. 285–299, 2014, ISSN: 21945357.
Abstract | Links | BibTeX | Tags: Chatbots, Conversational Agents, Knowledge Representation, Natural Language Processing, Ontologies
@article{augelloChatbotsInterfaceOntologies2014,
title = {Chatbots as Interface to Ontologies},
author = { Agnese Augello and Giovanni Pilato and Giorgio Vassallo and Salvatore Gaglio},
doi = {10.1007/978-3-319-03992-3_20},
issn = {21945357},
year = {2014},
date = {2014-01-01},
journal = {Advances in Intelligent Systems and Computing},
volume = {260},
pages = {285--299},
abstract = {Chatbots are simple conversational agents using 'pattern matching rules' to carry out the dialogue with the user and various expedients to improve their credibility. However, the rules on which they are based on are too restrictive and their language understanding capability is very limited. Nevertheless chatbots are widespread in several applications, especially to provide information to users in a new and enjoyable way. In this chapter we describe different chatbot architectures, exploiting the use of ontologies in order to create clever information suppliers overcoming the main limits of chatbots: The knowledge base building and the rigidness of the dialogue mechanism. textcopyright Springer International Publishing Switzerland 2014.},
keywords = {Chatbots, Conversational Agents, Knowledge Representation, Natural Language Processing, Ontologies},
pubstate = {published},
tppubtype = {article}
}
Chatbots are simple conversational agents using 'pattern matching rules' to carry out the dialogue with the user and various expedients to improve their credibility. However, the rules on which they are based on are too restrictive and their language understanding capability is very limited. Nevertheless chatbots are widespread in several applications, especially to provide information to users in a new and enjoyable way. In this chapter we describe different chatbot architectures, exploiting the use of ontologies in order to create clever information suppliers overcoming the main limits of chatbots: The knowledge base building and the rigidness of the dialogue mechanism. textcopyright Springer International Publishing Switzerland 2014.
Augello, Agnese; Pilato, Giovanni; Vassallo, Giorgio; Gaglio, Salvatore
Chatbots as interface to ontologies Journal Article
In: Advances in Intelligent Systems and Computing, vol. 260, pp. 285–299, 2014, ISSN: 21945357.
Abstract | Links | BibTeX | Tags: Chatbots, Conversational Agents, Knowledge Representation, Natural Language Processing, Ontologies
@article{augello_chatbots_2014,
title = {Chatbots as interface to ontologies},
author = {Agnese Augello and Giovanni Pilato and Giorgio Vassallo and Salvatore Gaglio},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84903692272&doi=10.1007%2f978-3-319-03992-3_20&partnerID=40&md5=55d82e9b0b5fdbf8176e8c168c729e14},
doi = {10.1007/978-3-319-03992-3_20},
issn = {21945357},
year = {2014},
date = {2014-01-01},
journal = {Advances in Intelligent Systems and Computing},
volume = {260},
pages = {285–299},
abstract = {Chatbots are simple conversational agents using 'pattern matching rules' to carry out the dialogue with the user and various expedients to improve their credibility. However, the rules on which they are based on are too restrictive and their language understanding capability is very limited. Nevertheless chatbots are widespread in several applications, especially to provide information to users in a new and enjoyable way. In this chapter we describe different chatbot architectures, exploiting the use of ontologies in order to create clever information suppliers overcoming the main limits of chatbots: The knowledge base building and the rigidness of the dialogue mechanism. © Springer International Publishing Switzerland 2014.},
keywords = {Chatbots, Conversational Agents, Knowledge Representation, Natural Language Processing, Ontologies},
pubstate = {published},
tppubtype = {article}
}
Chatbots are simple conversational agents using 'pattern matching rules' to carry out the dialogue with the user and various expedients to improve their credibility. However, the rules on which they are based on are too restrictive and their language understanding capability is very limited. Nevertheless chatbots are widespread in several applications, especially to provide information to users in a new and enjoyable way. In this chapter we describe different chatbot architectures, exploiting the use of ontologies in order to create clever information suppliers overcoming the main limits of chatbots: The knowledge base building and the rigidness of the dialogue mechanism. © Springer International Publishing Switzerland 2014.
2012
Augello, Agnese; Pilato, Giovanni; Machi, Alberto; Gaglio, Salvatore
An Approach to Enhance Chatbot Semantic Power and Maintainability: Experiences within the FRASI Project Proceedings Article
In: Proceedings - IEEE 6th International Conference on Semantic Computing, ICSC 2012, pp. 186–193, 2012, ISBN: 978-0-7695-4859-3.
Abstract | Links | BibTeX | Tags: Artificial intelligence, Human computer interaction, Ontologies, Semantic Computing
@inproceedings{augelloApproachEnhanceChatbot2012,
title = {An Approach to Enhance Chatbot Semantic Power and Maintainability: Experiences within the FRASI Project},
author = { Agnese Augello and Giovanni Pilato and Alberto Machi and Salvatore Gaglio},
doi = {10.1109/ICSC.2012.26},
isbn = {978-0-7695-4859-3},
year = {2012},
date = {2012-01-01},
booktitle = {Proceedings - IEEE 6th International Conference on Semantic Computing, ICSC 2012},
pages = {186--193},
abstract = {The paper illustrates the implementation and semantic enhancement of a domain-oriented Question-Answering system based on a pattern-matching chat bot technology, developed within an industrial project, named FRASI. The main difficulty in building a KB for a chat bot is to handwrite all possible question-answer pairs that constitute the KB. The proposed approach simplifies the chat bot realization thanks to two solutions. The first one uses an ontology, which is exploited in a twofold manner: to construct dynamic answers as a result of an inference process about the domain, and to automatically populate, off-line, the chat bot KB with sentences that can be derived from the ontology, describing properties and relations between concepts involved in the dialogue. The second one is to preprocess user sentences, and to reduce them to a simpler structure that can be referred to existing elements of the chat bot KB. The enhanced symbolic reduction of user questions and the automatic population of question templates in the chat bot KB from domain ontology have been implemented as two computational services (external modules). textcopyright 2012 IEEE.},
keywords = {Artificial intelligence, Human computer interaction, Ontologies, Semantic Computing},
pubstate = {published},
tppubtype = {inproceedings}
}
The paper illustrates the implementation and semantic enhancement of a domain-oriented Question-Answering system based on a pattern-matching chat bot technology, developed within an industrial project, named FRASI. The main difficulty in building a KB for a chat bot is to handwrite all possible question-answer pairs that constitute the KB. The proposed approach simplifies the chat bot realization thanks to two solutions. The first one uses an ontology, which is exploited in a twofold manner: to construct dynamic answers as a result of an inference process about the domain, and to automatically populate, off-line, the chat bot KB with sentences that can be derived from the ontology, describing properties and relations between concepts involved in the dialogue. The second one is to preprocess user sentences, and to reduce them to a simpler structure that can be referred to existing elements of the chat bot KB. The enhanced symbolic reduction of user questions and the automatic population of question templates in the chat bot KB from domain ontology have been implemented as two computational services (external modules). textcopyright 2012 IEEE.
Pilato, Giovanni; Augello, Agnese; Missikoff, Michele; Taglino, Francesco
Integration of Ontologies and Bayesian Networks for Maritime Situation Awareness Proceedings Article
In: Proceedings - IEEE 6th International Conference on Semantic Computing, ICSC 2012, pp. 170–177, 2012, ISBN: 978-0-7695-4859-3.
Abstract | Links | BibTeX | Tags: Context awareness, Ontologies, Semantic Computing
@inproceedings{pilatoIntegrationOntologiesBayesian2012,
title = {Integration of Ontologies and Bayesian Networks for Maritime Situation Awareness},
author = { Giovanni Pilato and Agnese Augello and Michele Missikoff and Francesco Taglino},
doi = {10.1109/ICSC.2012.25},
isbn = {978-0-7695-4859-3},
year = {2012},
date = {2012-01-01},
booktitle = {Proceedings - IEEE 6th International Conference on Semantic Computing, ICSC 2012},
pages = {170--177},
abstract = {This paper describes the main lines of the Intelligent Maritime Awareness Situation System (IMASS) developed to support an Electronic Surveillance platform conceived to contrast pirates activities in the Aden Gulf. The proposal is based on a solution that integrates an ontological approach in the description of the observed reality and a Bayesian approach to represent the experience and the knowledge of the domain experts. The intelligent system has been developed at a prototypical stage and tested with a complex scenario created with a simulator. The results are encouraging and indicate that this is a promising direction to go. textcopyright 2012 IEEE.},
keywords = {Context awareness, Ontologies, Semantic Computing},
pubstate = {published},
tppubtype = {inproceedings}
}
This paper describes the main lines of the Intelligent Maritime Awareness Situation System (IMASS) developed to support an Electronic Surveillance platform conceived to contrast pirates activities in the Aden Gulf. The proposal is based on a solution that integrates an ontological approach in the description of the observed reality and a Bayesian approach to represent the experience and the knowledge of the domain experts. The intelligent system has been developed at a prototypical stage and tested with a complex scenario created with a simulator. The results are encouraging and indicate that this is a promising direction to go. textcopyright 2012 IEEE.
Augello, Agnese; Pilato, Giovanni; Machi, Alberto; Gaglio, Salvatore
An approach to enhance chatbot semantic power and maintainability: Experiences within the FRASI project Proceedings Article
In: Proceedings - IEEE 6th International Conference on Semantic Computing, ICSC 2012, pp. 186–193, 2012, ISBN: 978-0-7695-4859-3.
Abstract | Links | BibTeX | Tags: Artificial intelligence, Human computer interaction, Ontologies, Semantic Computing
@inproceedings{augello_approach_2012,
title = {An approach to enhance chatbot semantic power and maintainability: Experiences within the FRASI project},
author = {Agnese Augello and Giovanni Pilato and Alberto Machi and Salvatore Gaglio},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84870664082&doi=10.1109%2fICSC.2012.26&partnerID=40&md5=4662866d6b85b9419fdd875cc2b92568},
doi = {10.1109/ICSC.2012.26},
isbn = {978-0-7695-4859-3},
year = {2012},
date = {2012-01-01},
booktitle = {Proceedings - IEEE 6th International Conference on Semantic Computing, ICSC 2012},
pages = {186–193},
abstract = {The paper illustrates the implementation and semantic enhancement of a domain-oriented Question-Answering system based on a pattern-matching chat bot technology, developed within an industrial project, named FRASI. The main difficulty in building a KB for a chat bot is to handwrite all possible question-answer pairs that constitute the KB. The proposed approach simplifies the chat bot realization thanks to two solutions. The first one uses an ontology, which is exploited in a twofold manner: to construct dynamic answers as a result of an inference process about the domain, and to automatically populate, off-line, the chat bot KB with sentences that can be derived from the ontology, describing properties and relations between concepts involved in the dialogue. The second one is to preprocess user sentences, and to reduce them to a simpler structure that can be referred to existing elements of the chat bot KB. The enhanced symbolic reduction of user questions and the automatic population of question templates in the chat bot KB from domain ontology have been implemented as two computational services (external modules). © 2012 IEEE.},
keywords = {Artificial intelligence, Human computer interaction, Ontologies, Semantic Computing},
pubstate = {published},
tppubtype = {inproceedings}
}
The paper illustrates the implementation and semantic enhancement of a domain-oriented Question-Answering system based on a pattern-matching chat bot technology, developed within an industrial project, named FRASI. The main difficulty in building a KB for a chat bot is to handwrite all possible question-answer pairs that constitute the KB. The proposed approach simplifies the chat bot realization thanks to two solutions. The first one uses an ontology, which is exploited in a twofold manner: to construct dynamic answers as a result of an inference process about the domain, and to automatically populate, off-line, the chat bot KB with sentences that can be derived from the ontology, describing properties and relations between concepts involved in the dialogue. The second one is to preprocess user sentences, and to reduce them to a simpler structure that can be referred to existing elements of the chat bot KB. The enhanced symbolic reduction of user questions and the automatic population of question templates in the chat bot KB from domain ontology have been implemented as two computational services (external modules). © 2012 IEEE.
Pilato, Giovanni; Augello, Agnese; Missikoff, Michele; Taglino, Francesco
Integration of ontologies and Bayesian networks for maritime situation awareness Proceedings Article
In: Proceedings - IEEE 6th International Conference on Semantic Computing, ICSC 2012, pp. 170–177, 2012, ISBN: 978-0-7695-4859-3.
Abstract | Links | BibTeX | Tags: Context awareness, Ontologies, Semantic Computing
@inproceedings{pilato_integration_2012,
title = {Integration of ontologies and Bayesian networks for maritime situation awareness},
author = {Giovanni Pilato and Agnese Augello and Michele Missikoff and Francesco Taglino},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84870710321&doi=10.1109%2fICSC.2012.25&partnerID=40&md5=c2cc15e0a1d39d1a54be4cc963479c00},
doi = {10.1109/ICSC.2012.25},
isbn = {978-0-7695-4859-3},
year = {2012},
date = {2012-01-01},
booktitle = {Proceedings - IEEE 6th International Conference on Semantic Computing, ICSC 2012},
pages = {170–177},
abstract = {This paper describes the main lines of the Intelligent Maritime Awareness Situation System (IMASS) developed to support an Electronic Surveillance platform conceived to contrast pirates activities in the Aden Gulf. The proposal is based on a solution that integrates an ontological approach in the description of the observed reality and a Bayesian approach to represent the experience and the knowledge of the domain experts. The intelligent system has been developed at a prototypical stage and tested with a complex scenario created with a simulator. The results are encouraging and indicate that this is a promising direction to go. © 2012 IEEE.},
keywords = {Context awareness, Ontologies, Semantic Computing},
pubstate = {published},
tppubtype = {inproceedings}
}
This paper describes the main lines of the Intelligent Maritime Awareness Situation System (IMASS) developed to support an Electronic Surveillance platform conceived to contrast pirates activities in the Aden Gulf. The proposal is based on a solution that integrates an ontological approach in the description of the observed reality and a Bayesian approach to represent the experience and the knowledge of the domain experts. The intelligent system has been developed at a prototypical stage and tested with a complex scenario created with a simulator. The results are encouraging and indicate that this is a promising direction to go. © 2012 IEEE.
2011
Augello, Agnese; Scriminaci, Mario; Gaglio, Salvatore; Pilato, Giovanni
A Modular Framework for Versatile Conversational Agent Building Proceedings Article
In: Proceedings of the International Conference on Complex, Intelligent and Software Intensive Systems, CISIS 2011, pp. 577–582, 2011, ISBN: 978-0-7695-4373-4.
Abstract | Links | BibTeX | Tags: Conversational Agents, Intelligent Agents, Knowledge Representation, Ontologies, Semantic Computing, Semantic Spaces
@inproceedings{augelloModularFrameworkVersatile2011,
title = {A Modular Framework for Versatile Conversational Agent Building},
author = { Agnese Augello and Mario Scriminaci and Salvatore Gaglio and Giovanni Pilato},
doi = {10.1109/CISIS.2011.95},
isbn = {978-0-7695-4373-4},
year = {2011},
date = {2011-01-01},
booktitle = {Proceedings of the International Conference on Complex, Intelligent and Software Intensive Systems, CISIS 2011},
pages = {577--582},
abstract = {This paper illustrates a web-based infrastructure of an architecture for conversational agents equipped with a modular knowledge base. This solution has the advantage to allow the building of specific modules that deal with particular features of a conversation (ranging from its topic to the manner of reasoning of the chatbot). This enhances the agent interaction capabilities. The approach simplifies the chatbot knowledge base design process: extending, generalizing or even restricting the chatbot knowledge base in order to suit it to manage specific dialoguing tasks as much as possible. textcopyright 2011 IEEE.},
keywords = {Conversational Agents, Intelligent Agents, Knowledge Representation, Ontologies, Semantic Computing, Semantic Spaces},
pubstate = {published},
tppubtype = {inproceedings}
}
This paper illustrates a web-based infrastructure of an architecture for conversational agents equipped with a modular knowledge base. This solution has the advantage to allow the building of specific modules that deal with particular features of a conversation (ranging from its topic to the manner of reasoning of the chatbot). This enhances the agent interaction capabilities. The approach simplifies the chatbot knowledge base design process: extending, generalizing or even restricting the chatbot knowledge base in order to suit it to manage specific dialoguing tasks as much as possible. textcopyright 2011 IEEE.
Augello, Agnese; Scriminaci, Mario; Gaglio, Salvatore; Pilato, Giovanni
A modular framework for versatile conversational agent building Proceedings Article
In: Proceedings of the International Conference on Complex, Intelligent and Software Intensive Systems, CISIS 2011, pp. 577–582, 2011, ISBN: 978-0-7695-4373-4.
Abstract | Links | BibTeX | Tags: Conversational Agents, Intelligent Agents, Knowledge Representation, Ontologies, Semantic Computing, Semantic Spaces
@inproceedings{augello_modular_2011,
title = {A modular framework for versatile conversational agent building},
author = {Agnese Augello and Mario Scriminaci and Salvatore Gaglio and Giovanni Pilato},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-80052692335&doi=10.1109%2fCISIS.2011.95&partnerID=40&md5=321e5590d4e49b21dd71c453692e04d7},
doi = {10.1109/CISIS.2011.95},
isbn = {978-0-7695-4373-4},
year = {2011},
date = {2011-01-01},
booktitle = {Proceedings of the International Conference on Complex, Intelligent and Software Intensive Systems, CISIS 2011},
pages = {577–582},
abstract = {This paper illustrates a web-based infrastructure of an architecture for conversational agents equipped with a modular knowledge base. This solution has the advantage to allow the building of specific modules that deal with particular features of a conversation (ranging from its topic to the manner of reasoning of the chatbot). This enhances the agent interaction capabilities. The approach simplifies the chatbot knowledge base design process: extending, generalizing or even restricting the chatbot knowledge base in order to suit it to manage specific dialoguing tasks as much as possible. © 2011 IEEE.},
keywords = {Conversational Agents, Intelligent Agents, Knowledge Representation, Ontologies, Semantic Computing, Semantic Spaces},
pubstate = {published},
tppubtype = {inproceedings}
}
This paper illustrates a web-based infrastructure of an architecture for conversational agents equipped with a modular knowledge base. This solution has the advantage to allow the building of specific modules that deal with particular features of a conversation (ranging from its topic to the manner of reasoning of the chatbot). This enhances the agent interaction capabilities. The approach simplifies the chatbot knowledge base design process: extending, generalizing or even restricting the chatbot knowledge base in order to suit it to manage specific dialoguing tasks as much as possible. © 2011 IEEE.
2010
Augello, Agnese; Pilato, Giovanni; Gaglio, Salvatore
An Intelligent Advisor to Suggest Strategies in Economic Policy Decisions Proceedings Article
In: CISIS 2010 - The 4th International Conference on Complex, Intelligent and Software Intensive Systems, pp. 734–739, 2010, ISBN: 978-0-7695-3967-6.
Abstract | Links | BibTeX | Tags: Artificial intelligence, Conversational Agents, Decision Networks, Decision Support Systems, Knowledge Representation, Ontologies
@inproceedings{augelloIntelligentAdvisorSuggest2010,
title = {An Intelligent Advisor to Suggest Strategies in Economic Policy Decisions},
author = { Agnese Augello and Giovanni Pilato and Salvatore Gaglio},
doi = {10.1109/CISIS.2010.75},
isbn = {978-0-7695-3967-6},
year = {2010},
date = {2010-01-01},
booktitle = {CISIS 2010 - The 4th International Conference on Complex, Intelligent and Software Intensive Systems},
pages = {734--739},
abstract = {In this paper we illustrate the architecture of an agent that plays the role of an "intelligent advisor". The advisor is aimed at suggesting the best managing strategies for a model of a virtual town. A Decision Support System (DSS) embedded on a conversational agent constitutes the intelligent advisor architecture. Two interacting knowledge representation areas characterize the DSS. The first one deals with the description of the domain and the deterministic events through the use of ontologies. The second one deals with the management of situations characterized by uncertainty. The intelligent advisor tries to prospect the future evolutions of particular choices taken by the user, and as a consequence, suggests the player-user the best strategy given the current status of the game. textcopyright 2010 IEEE.},
keywords = {Artificial intelligence, Conversational Agents, Decision Networks, Decision Support Systems, Knowledge Representation, Ontologies},
pubstate = {published},
tppubtype = {inproceedings}
}
In this paper we illustrate the architecture of an agent that plays the role of an "intelligent advisor". The advisor is aimed at suggesting the best managing strategies for a model of a virtual town. A Decision Support System (DSS) embedded on a conversational agent constitutes the intelligent advisor architecture. Two interacting knowledge representation areas characterize the DSS. The first one deals with the description of the domain and the deterministic events through the use of ontologies. The second one deals with the management of situations characterized by uncertainty. The intelligent advisor tries to prospect the future evolutions of particular choices taken by the user, and as a consequence, suggests the player-user the best strategy given the current status of the game. textcopyright 2010 IEEE.
2009
Sorce, Salvatore; Augello, Agnese; Santangelo, Antonella; Genco, Alessandro; Gentile, Antonio; Gaglio, Salvatore; Pilato, Giovanni
An RFID Framework for Multimodal Service Provision Proceedings Article
In: Proceedings of the International Conference on Complex, Intelligent and Software Intensive Systems, CISIS 2009, pp. 730–735, 2009, ISBN: 978-0-7695-3575-3.
Abstract | Links | BibTeX | Tags: Common Sense Reasoning, Context awareness, Conversational Agents, Human computer interaction, Multimodal Interaction, Ontologies, RFID Technology
@inproceedings{sorceRFIDFrameworkMultimodal2009,
title = {An RFID Framework for Multimodal Service Provision},
author = { Salvatore Sorce and Agnese Augello and Antonella Santangelo and Alessandro Genco and Antonio Gentile and Salvatore Gaglio and Giovanni Pilato},
doi = {10.1109/CISIS.2009.168},
isbn = {978-0-7695-3575-3},
year = {2009},
date = {2009-01-01},
booktitle = {Proceedings of the International Conference on Complex, Intelligent and Software Intensive Systems, CISIS 2009},
pages = {730--735},
abstract = {In recent years there has been a growing interest toward the evelopment of pervasive and contextaware services, and RFID technology played a relevant role in the context sensing task. We propose the use of RFID technology together with a conversational agent in order to implement a multimodal information retrieval service we call SensorMesh. The information acquired from RFID tags about the nearest point of interest is processed by the conversational agent that carries a more natural interaction with the user, also exploiting a common sense ontology. The service is accessible using a multimodal browser on Personal Digital Assistants (PDAs); the browser allows the user to interact with the conversational agent by means of spoken language instead of the traditional, keyboard- (or stylus-) based input systems. The resulting system offers a more natural interaction with respect to traditional prerecorded, audio-visual services, and it is particularly suitable for non technology-skilled users. textcopyright 2009 IEEE.},
keywords = {Common Sense Reasoning, Context awareness, Conversational Agents, Human computer interaction, Multimodal Interaction, Ontologies, RFID Technology},
pubstate = {published},
tppubtype = {inproceedings}
}
In recent years there has been a growing interest toward the evelopment of pervasive and contextaware services, and RFID technology played a relevant role in the context sensing task. We propose the use of RFID technology together with a conversational agent in order to implement a multimodal information retrieval service we call SensorMesh. The information acquired from RFID tags about the nearest point of interest is processed by the conversational agent that carries a more natural interaction with the user, also exploiting a common sense ontology. The service is accessible using a multimodal browser on Personal Digital Assistants (PDAs); the browser allows the user to interact with the conversational agent by means of spoken language instead of the traditional, keyboard- (or stylus-) based input systems. The resulting system offers a more natural interaction with respect to traditional prerecorded, audio-visual services, and it is particularly suitable for non technology-skilled users. textcopyright 2009 IEEE.
Sorce, Salvatore; Augello, Agnese; Santangelo, Antonella; Genco, Alessandro; Gentile, Antonio; Gaglio, Salvatore; Pilato, Giovanni
An RFID framework for multimodal service provision Proceedings Article
In: Proceedings of the International Conference on Complex, Intelligent and Software Intensive Systems, CISIS 2009, pp. 730–735, 2009, ISBN: 978-0-7695-3575-3.
Abstract | Links | BibTeX | Tags: Common Sense Reasoning, Context awareness, Conversational Agents, Human computer interaction, Multimodal Interaction, Ontologies, RFID Technology
@inproceedings{sorce_rfid_2009,
title = {An RFID framework for multimodal service provision},
author = {Salvatore Sorce and Agnese Augello and Antonella Santangelo and Alessandro Genco and Antonio Gentile and Salvatore Gaglio and Giovanni Pilato},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-70349743844&doi=10.1109%2fCISIS.2009.168&partnerID=40&md5=5667642a4b78f7ba9959dd18cc832673},
doi = {10.1109/CISIS.2009.168},
isbn = {978-0-7695-3575-3},
year = {2009},
date = {2009-01-01},
booktitle = {Proceedings of the International Conference on Complex, Intelligent and Software Intensive Systems, CISIS 2009},
pages = {730–735},
abstract = {In recent years there has been a growing interest toward the evelopment of pervasive and contextaware services, and RFID technology played a relevant role in the context sensing task. We propose the use of RFID technology together with a conversational agent in order to implement a multimodal information retrieval service we call SensorMesh. The information acquired from RFID tags about the nearest point of interest is processed by the conversational agent that carries a more natural interaction with the user, also exploiting a common sense ontology. The service is accessible using a multimodal browser on Personal Digital Assistants (PDAs); the browser allows the user to interact with the conversational agent by means of spoken language instead of the traditional, keyboard- (or stylus-) based input systems. The resulting system offers a more natural interaction with respect to traditional prerecorded, audio-visual services, and it is particularly suitable for non technology-skilled users. © 2009 IEEE.},
keywords = {Common Sense Reasoning, Context awareness, Conversational Agents, Human computer interaction, Multimodal Interaction, Ontologies, RFID Technology},
pubstate = {published},
tppubtype = {inproceedings}
}
In recent years there has been a growing interest toward the evelopment of pervasive and contextaware services, and RFID technology played a relevant role in the context sensing task. We propose the use of RFID technology together with a conversational agent in order to implement a multimodal information retrieval service we call SensorMesh. The information acquired from RFID tags about the nearest point of interest is processed by the conversational agent that carries a more natural interaction with the user, also exploiting a common sense ontology. The service is accessible using a multimodal browser on Personal Digital Assistants (PDAs); the browser allows the user to interact with the conversational agent by means of spoken language instead of the traditional, keyboard- (or stylus-) based input systems. The resulting system offers a more natural interaction with respect to traditional prerecorded, audio-visual services, and it is particularly suitable for non technology-skilled users. © 2009 IEEE.
2007
Pilato, Giovanni; Augello, Agnese; Scriminaci, Mario; Vassallo, Giorgio; Gaglio, Salvatore
Sub-Symbolic Mapping of Cyc Microtheories in Data-Driven "Conceptual" Spaces Journal Article
In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4692 LNAI, no. PART 1, pp. 156–163, 2007, ISSN: 03029743.
Abstract | Links | BibTeX | Tags: Cognitive Systems, Conceptual Spaces, Ontologies
@article{pilatoSubsymbolicMappingCyc2007,
title = {Sub-Symbolic Mapping of Cyc Microtheories in Data-Driven "Conceptual" Spaces},
author = { Giovanni Pilato and Agnese Augello and Mario Scriminaci and Giorgio Vassallo and Salvatore Gaglio},
doi = {10.1007/978-3-540-74819-9_20},
issn = {03029743},
year = {2007},
date = {2007-01-01},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
volume = {4692 LNAI},
number = {PART 1},
pages = {156--163},
abstract = {The presented work aims to combine statistical and cognitive-oriented approaches with symbolic ones so that a conceptual similarity relationship layer can be added to a Cyc KB microtheory. Given a specific microtheory, a LSA-inspired conceptual space is inferred from a corpus of texts created using both ad hoc extracted pages from the Wikipedia repository and the built-in comments about the concepts of the specific Cyc microtheory. Each concept is projected in the conceptual space and the desired layer of subsymbolic relationships between concepts is created. This procedure can help a user in finding the concepts that are "sub-symbolically conceptually related" to a new concept that he wants to insert in the microtheory. Experimental results involving two Cyc microtheories are also reported. textcopyright Springer-Verlag Berlin Heidelberg 2007.},
keywords = {Cognitive Systems, Conceptual Spaces, Ontologies},
pubstate = {published},
tppubtype = {article}
}
The presented work aims to combine statistical and cognitive-oriented approaches with symbolic ones so that a conceptual similarity relationship layer can be added to a Cyc KB microtheory. Given a specific microtheory, a LSA-inspired conceptual space is inferred from a corpus of texts created using both ad hoc extracted pages from the Wikipedia repository and the built-in comments about the concepts of the specific Cyc microtheory. Each concept is projected in the conceptual space and the desired layer of subsymbolic relationships between concepts is created. This procedure can help a user in finding the concepts that are "sub-symbolically conceptually related" to a new concept that he wants to insert in the microtheory. Experimental results involving two Cyc microtheories are also reported. textcopyright Springer-Verlag Berlin Heidelberg 2007.
Pilato, Giovanni; Augello, Agnese; Vassallo, Giorgio; Gaglio, Salvatore
Sub-Symbolic Semantic Layer in Cyc for Intuitive Chat-Bots Proceedings Article
In: ICSC 2007 International Conference on Semantic Computing, pp. 121–128, 2007, ISBN: 0-7695-2997-6 978-0-7695-2997-4.
Abstract | Links | BibTeX | Tags: Artificial intelligence, Chatbots, Common Sense Reasoning, Conversational Agents, Cyc Ontology, Knowledge Representation, Latent Semantic Analysis, Ontologies, Semantic Computing, Semantic Spaces
@inproceedings{pilatoSubsymbolicSemanticLayer2007,
title = {Sub-Symbolic Semantic Layer in Cyc for Intuitive Chat-Bots},
author = { Giovanni Pilato and Agnese Augello and Giorgio Vassallo and Salvatore Gaglio},
doi = {10.1109/ICSC.2007.37},
isbn = {0-7695-2997-6 978-0-7695-2997-4},
year = {2007},
date = {2007-01-01},
booktitle = {ICSC 2007 International Conference on Semantic Computing},
pages = {121--128},
abstract = {The work presented in this paper aims to combine Latent Semantic Analysis methodology, common sense and traditional knowledge representation in order to improve the dialogue capabilities of a conversational agent. In our approach the agent brain is characterized by two areas: a "rational area", composed by a structured, rule-based knowledge base, and an "associative area", obtained through a data-driven semantic space. Concepts are mapped in this space and their mutual geometric distance is related to their conceptual similarity. The geometric distance between concepts implicitly defines a sub-symbolic relationship net, which can be seen as a new "subsymbolic semantic layer" automatically added to the Cyc ontology. Users queries can also be mapped in the same conceptual space, and evoke similar ontology concepts. As a result the agent can exploit this feature, attempting to retrieve ontological concepts that are not easily reachable by means of the traditional ontology reasoning engine. textcopyright 2007 IEEE.},
keywords = {Artificial intelligence, Chatbots, Common Sense Reasoning, Conversational Agents, Cyc Ontology, Knowledge Representation, Latent Semantic Analysis, Ontologies, Semantic Computing, Semantic Spaces},
pubstate = {published},
tppubtype = {inproceedings}
}
The work presented in this paper aims to combine Latent Semantic Analysis methodology, common sense and traditional knowledge representation in order to improve the dialogue capabilities of a conversational agent. In our approach the agent brain is characterized by two areas: a "rational area", composed by a structured, rule-based knowledge base, and an "associative area", obtained through a data-driven semantic space. Concepts are mapped in this space and their mutual geometric distance is related to their conceptual similarity. The geometric distance between concepts implicitly defines a sub-symbolic relationship net, which can be seen as a new "subsymbolic semantic layer" automatically added to the Cyc ontology. Users queries can also be mapped in the same conceptual space, and evoke similar ontology concepts. As a result the agent can exploit this feature, attempting to retrieve ontological concepts that are not easily reachable by means of the traditional ontology reasoning engine. textcopyright 2007 IEEE.
Pilato, Giovanni; Augello, Agnese; Vassallo, Giorgio; Gaglio, Salvatore
Sub-symbolic semantic layer in Cyc for intuitive chat-bots Proceedings Article
In: ICSC 2007 International Conference on Semantic Computing, pp. 121–128, 2007, ISBN: 0-7695-2997-6 978-0-7695-2997-4.
Abstract | Links | BibTeX | Tags: Artificial intelligence, Chatbots, Common Sense Reasoning, Conversational Agents, Cyc Ontology, Knowledge Representation, Latent Semantic Analysis, Ontologies, Semantic Computing, Semantic Spaces
@inproceedings{pilato_sub-symbolic_2007,
title = {Sub-symbolic semantic layer in Cyc for intuitive chat-bots},
author = {Giovanni Pilato and Agnese Augello and Giorgio Vassallo and Salvatore Gaglio},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-47749136245&doi=10.1109%2fICSC.2007.37&partnerID=40&md5=1ff5f81a3db6cd161a1eccd4c9eab2e8},
doi = {10.1109/ICSC.2007.37},
isbn = {0-7695-2997-6 978-0-7695-2997-4},
year = {2007},
date = {2007-01-01},
booktitle = {ICSC 2007 International Conference on Semantic Computing},
volume = {4692 LNAI},
number = {PART 1},
pages = {121–128},
abstract = {The work presented in this paper aims to combine Latent Semantic Analysis methodology, common sense and traditional knowledge representation in order to improve the dialogue capabilities of a conversational agent. In our approach the agent brain is characterized by two areas: a "rational area", composed by a structured, rule-based knowledge base, and an "associative area", obtained through a data-driven semantic space. Concepts are mapped in this space and their mutual geometric distance is related to their conceptual similarity. The geometric distance between concepts implicitly defines a sub-symbolic relationship net, which can be seen as a new "subsymbolic semantic layer" automatically added to the Cyc ontology. Users queries can also be mapped in the same conceptual space, and evoke similar ontology concepts. As a result the agent can exploit this feature, attempting to retrieve ontological concepts that are not easily reachable by means of the traditional ontology reasoning engine. © 2007 IEEE.},
keywords = {Artificial intelligence, Chatbots, Common Sense Reasoning, Conversational Agents, Cyc Ontology, Knowledge Representation, Latent Semantic Analysis, Ontologies, Semantic Computing, Semantic Spaces},
pubstate = {published},
tppubtype = {inproceedings}
}
The work presented in this paper aims to combine Latent Semantic Analysis methodology, common sense and traditional knowledge representation in order to improve the dialogue capabilities of a conversational agent. In our approach the agent brain is characterized by two areas: a "rational area", composed by a structured, rule-based knowledge base, and an "associative area", obtained through a data-driven semantic space. Concepts are mapped in this space and their mutual geometric distance is related to their conceptual similarity. The geometric distance between concepts implicitly defines a sub-symbolic relationship net, which can be seen as a new "subsymbolic semantic layer" automatically added to the Cyc ontology. Users queries can also be mapped in the same conceptual space, and evoke similar ontology concepts. As a result the agent can exploit this feature, attempting to retrieve ontological concepts that are not easily reachable by means of the traditional ontology reasoning engine. © 2007 IEEE.