A general language model for information retrieval (poster abstract)
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Language Modeling for Information Retrieval
Language Modeling for Information Retrieval
Efficient and self-tuning incremental query expansion for top-k query processing
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Simple questions to improve pseudo-relevance feedback results
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Improving web site search using web server logs
CASCON '06 Proceedings of the 2006 conference of the Center for Advanced Studies on Collaborative research
Improving query precision using semantic expansion
Information Processing and Management: an International Journal
Adaptive document clustering based on query-based similarity
Information Processing and Management: an International Journal
Combining fields for query expansion and adaptive query expansion
Information Processing and Management: an International Journal
Parsimonious translation models for information retrieval
Information Processing and Management: an International Journal
Query performance prediction in web search environments
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Context sensitive stemming for web search
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
A new robust relevance model in the language model framework
Information Processing and Management: an International Journal
Effective and efficient user interaction for long queries
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Task-aware search personalization
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Matching task profiles and user needs in personalized web search
Proceedings of the 17th ACM conference on Information and knowledge management
Query dependent pseudo-relevance feedback based on wikipedia
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Adaptive relevance feedback in information retrieval
Proceedings of the 18th ACM conference on Information and knowledge management
Enhancing relevance models with adaptive passage retrieval
ECIR'08 Proceedings of the IR research, 30th European conference on Advances in information retrieval
Multilingual PRF: english lends a helping hand
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Multilingual pseudo-relevance feedback: performance study of assisting languages
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Exploring social annotation tags to enhance information retrieval performance
AMT'10 Proceedings of the 6th international conference on Active media technology
Proceedings of the fourth ACM international conference on Web search and data mining
Proceedings of the 2010 conference on STAIRS 2010: Proceedings of the Fifth Starting AI Researchers' Symposium
An ontological representation of documents and queries for information retrieval systems
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part II
Social annotation in query expansion: a machine learning approach
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Predicting the performance of recommender systems: an information theoretic approach
ICTIR'11 Proceedings of the Third international conference on Advances in information retrieval theory
Patent query reduction using pseudo relevance feedback
Proceedings of the 20th ACM international conference on Information and knowledge management
Query performance prediction: evaluation contrasted with effectiveness
ECIR'2010 Proceedings of the 32nd European conference on Advances in Information Retrieval
Expert Systems with Applications: An International Journal
Automatic refinement of patent queries using concept importance predictors
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Exploiting External Collections for Query Expansion
ACM Transactions on the Web (TWEB)
Keyphrase extraction through query performance prediction
Journal of Information Science
Conceptual representing of documents and query expansion based on ontology
WISM'12 Proceedings of the 2012 international conference on Web Information Systems and Mining
Efficient and effective retrieval using selective pruning
Proceedings of the sixth ACM international conference on Web search and data mining
Relevance Feedback Fusion via Query Expansion
WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 03
Collaborative pseudo-relevance feedback
Expert Systems with Applications: An International Journal
| Hi-index | 0.00 |
Query expansion is a well-known technique that has been shown to improve average retrieval performance. This technique has not been used in many operational systems because of the fact that it can greatly degrade the performance of some individual queries. We show how comparison between language models of the unexpanded and expanded retrieval results can be used to predict when the expanded retrieval has strayed from the original sense of the query. In these cases, the unexpanded results are used while the expanded results are used in the remaining cases (where such straying is not detected). We evaluate this method on a wide variety of TREC collections.