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Posters
Track: Posters
Paper Title:
CM-PMI: Improved Web-based Association Measure with Contextual Label Matching
Authors:
- Xiaojun Wan(Peking University)
Abstract:
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.
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