Using Relational Similarity between Word Pairs for Latent Relational Search on the Web

• Published in: 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Vol. 1; pp. 196 - 199
• Main Authors: Duc, Nguyen Tuan, Bollegala, Danushka, Ishizuka, Mitsuru
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.08.2010
• Subjects: analogical search; Clustering algorithms; Companies; Filters; Frequency measurement; Indexes; latent relational search; Logic gates; Pattern clustering; relational similarity; Search engines; Semantics; Vectors
• ISBN: 9781424484829; 1424484820
• DOI: 10.1109/WI-IAT.2010.167

Latent relational search is a new search paradigm based on the degree of analogy between two word pairs. A latent relational search engine is expected to return the word Paris as an answer to the question mark (?) in the query {(Japan, Tokyo), (France, ?)} because the relation between Japan and Tokyo is highly similar to that between France and Paris. We propose an approach for exploring and indexing word pairs to efficiently retrieve candidate answers for a latent relational search query. Representing relations between two words in a word pair by lexical patterns allows our search engine to achieve a high MRR and high precision for the top 1 ranked result. When evaluating with a Web corpus, the proposed method achieves an MRR of 0.963 and it retrieves correct answer in the top 1 for 95.0% of queries.