NDLI: Word Embedding Causes Topic Shifting; Exploit Global Context!

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Word Embedding Causes Topic Shifting; Exploit Global Context!

Content Provider	ACM Digital Library
Author	Hanbury, Allan Zamani, Hamed Rekabsaz, Navid Lupu, Mihai
Abstract	Exploitation of term relatedness provided by word embedding has gained considerable attention in recent IR literature. However, an emerging question is whether this sort of relatedness fits to the needs of IR with respect to retrieval effectiveness. While we observe a high potential of word embedding as a resource for related terms, the incidence of several cases of topic shifting deteriorates the final performance of the applied retrieval models. To address this issue, we revisit the use of global context (i.e. the term co-occurrence in documents) to measure the term relatedness. We hypothesize that in order to avoid topic shifting among the terms with high word embedding similarity, they should often share similar global contexts as well. We therefore study the effectiveness of post filtering of related terms by various global context relatedness measures. Experimental results show significant improvements in two out of three test collections, and support our initial hypothesis regarding the importance of considering global context in retrieval.
Starting Page	1105
Ending Page	1108
Page Count	4
File Format	PDF
ISBN	9781450350228
DOI	10.1145/3077136.3080733
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2017-08-07
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Word2vec Lsi Word embedding Term relatedness Global context
Content Type	Text
Resource Type	Article

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