Publications

@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}

}

@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}

}