Publications

@inproceedings{augelloInnovativeSimilarityMeasure2016,

title = {An Innovative Similarity Measure for Sentence Plagiarism Detection},

author = { Agnese Augello and Alfredo Cuzzocrea and Giovanni Pilato and Carmelo Spiccia and Giorgio Vassallo},

editor = { O Gervasi and B Murgante and S Misra and {relax AMAC} Rocha and {relax CM} Torre and D Tanier and {relax BO} Apduhan and E Stankova and S Wang},

doi = {10.1007/978-3-319-42092-9_42},

isbn = {978-3-319-42092-9},

year  = {2016},

date = {2016-01-01},

booktitle = {COMPUTATIONAL SCIENCE AND ITS APPLICATIONS - ICCSA 2016, PT V},

volume = {9790},

pages = {552--566},

publisher = {SPRINGER INTERNATIONAL PUBLISHING AG},

address = {GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND},

series = {Lecture Notes in Computer Science},

abstract = {We propose and experimentally assess Semantic Word Error Rate (SWER), an innovative similarity measure for sentence plagiarism detection. SWER introduces a complex approach based on latent semantic analysis, which is capable of outperforming the accuracy of competitor methods in plagiarism detection. We provide principles and functionalities of SWER, and we complement our analytical contribution by means of a significant preliminary experimental analysis. Derived results are promising, and confirm to use the goodness of our proposal.},

keywords = {Plagiarism Detection, Semantic Computing},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{augello_innovative_2016,

title = {An Innovative Similarity Measure for Sentence Plagiarism Detection},

author = {Agnese Augello and Alfredo Cuzzocrea and Giovanni Pilato and Carmelo Spiccia and Giorgio Vassallo},

editor = {O Gervasi and B Murgante and S Misra and AMAC Rocha and CM Torre and D Tanier and BO Apduhan and E Stankova and S Wang},

doi = {10.1007/978-3-319-42092-9_42},

isbn = {978-3-319-42092-9},

year  = {2016},

date = {2016-01-01},

booktitle = {COMPUTATIONAL SCIENCE AND ITS APPLICATIONS - ICCSA 2016, PT V},

volume = {9790},

pages = {552–566},

publisher = {SPRINGER INTERNATIONAL PUBLISHING AG},

address = {GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND},

series = {Lecture Notes in Computer Science},

abstract = {We propose and experimentally assess Semantic Word Error Rate (SWER), an innovative similarity measure for sentence plagiarism detection. SWER introduces a complex approach based on latent semantic analysis, which is capable of outperforming the accuracy of competitor methods in plagiarism detection. We provide principles and functionalities of SWER, and we complement our analytical contribution by means of a significant preliminary experimental analysis. Derived results are promising, and confirm to use the goodness of our proposal.},

keywords = {Plagiarism Detection, Semantic Computing},

pubstate = {published},

tppubtype = {inproceedings}

}