Measuring the similarity between implicit semantic relations using web search engines

Measuring the similarity between implicit semantic relations is an important task in information retrieval and natural language processing. For example, consider the situation where you know an entity-pair (e.g. Google, YouTube), between which a particular relation holds (e.g. acquisition), and you are interested in retrieving other entity-pairs for which the same relation holds (e.g. Yahoo, Inktomi). Existing keyword-based search engines cannot be directly applied in this case because in keyword-based search, the goal is to retrieve documents that are relevant to the words used in the query – not necessarily to the relations implied by a pair of words. Accurate measurement of relational similarity is an important step in numerous natural language processing tasks such as identification of word analogies, and classification of noun-modifier pairs. We propose a method that uses Web search engines to efficiently compute the relational similarity between two pairs of words. Our met...

• Type: Conference
• Year: 2009
• Where: WSDM
• Authors: Danushka Bollegala, Yutaka Matsuo, Mitsuru Ishizuka
• Keywords: Data Mining, Extracted Lexical Patterns, Relational Similarity, Semantic Relations, Wsdm 2009