Information retrieval on the web
ACM Computing Surveys (CSUR)
Ontology learning for search applications
OTM'07 Proceedings of the 2007 OTM Confederated international conference on On the move to meaningful internet systems: CoopIS, DOA, ODBASE, GADA, and IS - Volume Part I
Unsupervised keyphrase extraction for search ontologies
NLDB'06 Proceedings of the 11th international conference on Applications of Natural Language to Information Systems
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In spite of intensive research on linguistic techniques in information retrieval, there are still few large-scale search engines that have taken full advantage of these techniques. This paper presents the integration of various linguistic techniques in one of the largest search engines on the Internet. The techniques include language identification, offensive content filtering, phrasing and anti-phrasing, normalization, and clustering. We go into some of the challenges of Internet search and discuss our experiences with these techniques.