TY - GEN
T1 - Query expansion using word embeddings
AU - Kuzi, Saar
AU - Shtok, Anna
AU - Kurland, Oren
N1 - Publisher Copyright:
© 2016 ACM.
PY - 2016/10/24
Y1 - 2016/10/24
N2 - We present a suite of query expansion methods that are based on word embeddings. Using Word2Vec's CBOW embedding approach, applied over the entire corpus on which search is performed, we select terms that are semantically related to the query. Our methods either use the terms to expand the original query or integrate them with the effective pseudo-feedback-based relevance model. In the former case, retrieval performance is significantly better than that of using only the query, and in the latter case the performance is significantly better than that of the relevance model.
AB - We present a suite of query expansion methods that are based on word embeddings. Using Word2Vec's CBOW embedding approach, applied over the entire corpus on which search is performed, we select terms that are semantically related to the query. Our methods either use the terms to expand the original query or integrate them with the effective pseudo-feedback-based relevance model. In the former case, retrieval performance is significantly better than that of using only the query, and in the latter case the performance is significantly better than that of the relevance model.
UR - http://www.scopus.com/inward/record.url?scp=84996522155&partnerID=8YFLogxK
U2 - 10.1145/2983323.2983876
DO - 10.1145/2983323.2983876
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AN - SCOPUS:84996522155
T3 - International Conference on Information and Knowledge Management, Proceedings
SP - 1929
EP - 1932
BT - CIKM 2016 - Proceedings of the 2016 ACM Conference on Information and Knowledge Management
T2 - 25th ACM International Conference on Information and Knowledge Management, CIKM 2016
Y2 - 24 October 2016 through 28 October 2016
ER -