A web-based kernel function for measuring the similarity of short text snippets
Proceedings of the 15th international conference on World Wide Web
Novel association measures using web search with double checking
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Measuring semantic similarity between words using web search engines
Proceedings of the 16th international conference on World Wide Web
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WebPMI is a popular web-based association measure to evaluate the semantic similarity between two queries (i.e. words or entities) by leveraging search results returned by search engines. This paper proposes a novel measure named CM-PMI to evaluate query similarity at a finer granularity than WebPMI, under the assumption that a query is usually associated with more than one aspect and two queries are deemed semantically related if their associated aspect sets are highly consistent with each other. CM-PMI first extracts contextual labels from search results to represent the aspects of a query, and then uses the optimal matching method to assess the consistency between the aspects of two queries. Experimental results on the benchmark Miller Charles' dataset demonstrate the good effectiveness of the proposed CM-PMI measure. Moreover, we further fuse WebPMI and CM-PMI to obtain improved results.