Improving the effectiveness of information retrieval with local context analysis
ACM Transactions on Information Systems (TOIS)
Agglomerative clustering of a search engine query log
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
A vector space model for automatic indexing
Communications of the ACM
Clustering user queries of a search engine
Proceedings of the 10th international conference on World Wide Web
A study of smoothing methods for language models applied to Ad Hoc information retrieval
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Probabilistic query expansion using query logs
Proceedings of the 11th international conference on World Wide Web
Optimizing search engines using clickthrough data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Using terminological feedback for web search refinement: a log-based study
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
The mathematics of statistical machine translation: parameter estimation
Computational Linguistics - Special issue on using large corpora: II
Automatic retrieval and clustering of similar words
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Identifying similarities, periodicities and bursts for online search queries
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Semantic similarity between search engine queries using temporal correlation
WWW '05 Proceedings of the 14th international conference on World Wide Web
The computation of word associations: comparing syntagmatic and paradigmatic approaches
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Context-sensitive information retrieval using implicit feedback
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Query chains: learning to rank from implicit feedback
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
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
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Improving web search ranking by incorporating user behavior information
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
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Learn from web search logs to organize search results
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Context sensitive stemming for web search
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AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Analysis of long queries in a large scale search log
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Beyond hyperlinks: organizing information footprints in search logs to support effective browsing
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A query model based on normalized log-likelihood
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Query reformulation using anchor text
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Alignment of short length parallel corpora with an application to web search
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Learning similarity function for rare queries
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CLEF'11 Proceedings of the Second international conference on Multilingual and multimodal information access evaluation
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Proceedings of the 20th ACM international conference on Information and knowledge management
Proceedings of the 20th ACM international conference on Information and knowledge management
Query suggestion by constructing term-transition graphs
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SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
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SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
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SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
A generalized hidden Markov model with discriminative training for query spelling correction
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Automatically mining question reformulation patterns from search log data
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Short Papers - Volume 2
A discriminative model for query spelling correction with latent structural SVM
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Domain dependent query reformulation for web search
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Improved query suggestion by query search
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Learning a Lightweight Ontology for Semantic Retrieval in Patient-Centered Information Systems
International Journal of Knowledge Management
Modeling reformulation using query distributions
ACM Transactions on Information Systems (TOIS)
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
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Predicting the impact of expansion terms using semantic and user interaction features
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Learning to rank query suggestions for adhoc and diversity search
Information Retrieval
When do people use query suggestion? A query suggestion log analysis
Information Retrieval
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Search engine logs are an emerging new type of data that offers interesting opportunities for data mining. Existing work on mining such data has mostly attempted to discover knowledge at the level of queries (e.g., query clusters). In this paper, we propose to mine search engine logs for patterns at the level of terms through analyzing the relations of terms inside a query. We define two novel term association patterns (i.e., context-sensitive term substitutions and term additions) and propose new methods for mining such patterns from search engine logs. These two patterns can be used to address the mis-specification and under-specification problems of ineffective queries. Experiment results on real search engine logs show that the mined context-sensitive term substitutions can be used to effectively reword queries and improve their accuracy, while the mined context-sensitive term addition patterns can be used to support query refinement in a more effective way.