SEARCH FOR ENTITIES BASED ON THE IMPLICIT SEMANTIC RELATIONS

Tran Lam Quan, Vu Tat Thang

Abstract


The ability to infer undefined information/knowledge by similar inference is one of the natural abilities of human. The paper aims to study, simulate the above ability. The IRS model searches for undefined information/knowledge from an unfamiliar domain using similarities from familiar domains, through query. Because the semantic relations or similarities are not explicitly stated in the query, the IRS model is called an implicit semantic entity search model. The paper presents extracting, clustering, ranking techniques and a model of implicit relational search on Vietnamese language domain.


Keywords


implicit relational entity search; named-entity; semantic relation; similarity relation

References


The ability to infer undefined information/knowledge by similar inference is one of the natural abilities of human. The paper aims to study, simulate the above ability. The IRS model searches for undefined information/knowledge from an unfamiliar domain using similarities from familiar domains, through query. Because the semantic relations or similarities are not explicitly stated in the query, the IRS model is called an implicit semantic entity search model. The paper presents extracting, clustering, ranking techniques and a model of implicit relational search on Vietnamese language domain




DOI: https://doi.org/10.15625/1813-9663/0/0/13210 Display counter: Abstract : 13 views.

Journal of Computer Science and Cybernetics ISSN: 1813-9663

Published by Vietnam Academy of Science and Technology