DocumentCode
660906
Title
Semantic Entity Search Diversification
Author
Ruotsalo, Tuukka ; Frosterus, Matias
Author_Institution
Helsinki Inst. for Inf. Technol. HIIT, Aalto Univ., Espoo, Finland
fYear
2013
fDate
16-18 Sept. 2013
Firstpage
32
Lastpage
39
Abstract
We present an approach to diversify entity search by utilizing semantics present and inferred from the initial entity search results. Our approach makes use of ontologies and independent component analysis of the entity descriptions to reveal direct and latent semantic connections between the entities present in the initial search results. The semantic connections are then used to sample a set of diverse entities. We empirically demonstrate the performance of our approach through retrieval experiments that use a real-world dataset composed from four entity databases. The results indicate that our approach significantly improves both diversity and effectiveness of entity search.
Keywords
database management systems; ontologies (artificial intelligence); query formulation; component analysis; direct semantic connections; diverse entities; entity databases; entity descriptions; latent semantic connections; ontologies; real-world dataset; retrieval experiments; semantic entity search diversification; Cognition; Eigenvalues and eigenfunctions; Indexing; Information retrieval; Semantics; Standards; Vectors; Semantic search; diversification; information retrieval;
fLanguage
English
Publisher
ieee
Conference_Titel
Semantic Computing (ICSC), 2013 IEEE Seventh International Conference on
Conference_Location
Irvine, CA
Type
conf
DOI
10.1109/ICSC.2013.16
Filename
6693491
Link To Document