TY - GEN
T1 - Information retrieval with a simplified conceptual graph-like representation
AU - Ordoñez-Salinas, Sonia
AU - Gelbukh, Alexander
N1 - Funding Information:
Acknowledgements. The work was done during the first author’s research stay at the Laboratorio de Lenguaje Natural y Procesamiento de Texto of the Centro de Investi-gación en Computación of the Instituto Politécnico Nacional, Mexico, partially funded by the Universidad Nacional de Colombia and Universidad Distrital F.J.C., Bogota, Colombia, and with partial support of Mexican Government (SNI, CONACYT grant 50206-H, CONACYT scholarship for Sabbatical stay at Waseda U., COFAA-IPN, and SIP-IPN grant 20100773) to the second author.
PY - 2010
Y1 - 2010
N2 - We argue for that taking into account semantic relations between words in the text can improve information retrieval performance. We implemented the process of information retrieval with simplified Conceptual Graph-like structures and compare the results with those of the vector space model. Our semantic representation, combined with a small simplification of the vector space model, gives better results. In order to build Conceptual Graph-like representation, we have developed a grammar based on the dependency formalism and the standard defined for Conceptual Graphs (CG). We used noun pre-modifiers and noun post-modifiers, as well as verb frames, extracted from VerbNet, as a source of definition of semantic roles. VerbNet was chosen since its definitions of semantic roles have much in common with the CG standard. We experimented on a subset of the ImageClef 2008 collection of titles and annotations of medical images.
AB - We argue for that taking into account semantic relations between words in the text can improve information retrieval performance. We implemented the process of information retrieval with simplified Conceptual Graph-like structures and compare the results with those of the vector space model. Our semantic representation, combined with a small simplification of the vector space model, gives better results. In order to build Conceptual Graph-like representation, we have developed a grammar based on the dependency formalism and the standard defined for Conceptual Graphs (CG). We used noun pre-modifiers and noun post-modifiers, as well as verb frames, extracted from VerbNet, as a source of definition of semantic roles. VerbNet was chosen since its definitions of semantic roles have much in common with the CG standard. We experimented on a subset of the ImageClef 2008 collection of titles and annotations of medical images.
KW - Conceptual Graph
KW - Dependency Grammar
KW - Information Retrieval
UR - http://www.scopus.com/inward/record.url?scp=78650035292&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-16761-4_9
DO - 10.1007/978-3-642-16761-4_9
M3 - Contribución a la conferencia
SN - 3642167608
SN - 9783642167607
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 92
EP - 104
BT - Advances in Artificial Intelligence - 9th Mexican International Conference on Artificial Intelligence, MICAI 2010, Proceedings
T2 - 9th Mexican International Conference on Artificial Intelligence, MICAI 2010
Y2 - 8 November 2010 through 13 November 2010
ER -