Use of syntactic context to produce term association lists for text retrieval
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
A vector space model for automatic indexing
Communications of the ACM
Mining anchor text for query refinement
Proceedings of the 13th international conference on World Wide Web
Scoring missing terms in information retrieval tasks
Proceedings of the thirteenth ACM international conference on Information and knowledge management
A web-based kernel function for measuring the similarity of short text snippets
Proceedings of the 15th international conference on World Wide Web
Generating query substitutions
Proceedings of the 15th international conference on World Wide Web
Consistent phrase relevance measures
Proceedings of the 2nd International Workshop on Data Mining and Audience Intelligence for Advertising
Translating queries into snippets for improved query expansion
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Improving similarity measures for short segments of text
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
A comparison of co-occurrence and similarity measures as simulations of context
CICLing'08 Proceedings of the 9th international conference on Computational linguistics and intelligent text processing
Gazpacho and summer rash: lexical relationships from temporal patterns of web search queries
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 3 - Volume 3
Generalized syntactic and semantic models of query reformulation
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
The viability of web-derived polarity lexicons
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
| Hi-index | 0.00 |
We present a large-scale, data-driven approach to computing distributional similarity scores for queries. We contrast this to recent web-based techniques which either require the offline computation of complete phrase vectors, or an expensive on-line interaction with a search engine interface. Independent of the computational advantages of our approach, we show empirically that our technique is more effective at ranking query alternatives that the computationally more expensive technique of using the results from a web search engine.