Query expansion using local and global document analysis
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Advantages of query biased summaries in information retrieval
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Local Feedback in Full-Text Retrieval Systems
Journal of the ACM (JACM)
Improving the effectiveness of information retrieval with local context analysis
ACM Transactions on Information Systems (TOIS)
Relevance based language models
Proceedings of the 24th 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
Retrieval and novelty detection at the sentence level
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Using top-ranking sentences to facilitate effective information access: Book Reviews
Journal of the American Society for Information Science and Technology
Novelty detection based on sentence level patterns
Proceedings of the 14th ACM international conference on Information and knowledge management
Example-based machine translation using efficient sentence retrieval based on edit-distance
ACM Transactions on Asian Language Information Processing (TALIP)
Aspects of sentence retrieval
The Combination and Evaluation of Query Performance Prediction Methods
ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
Highly frequent terms and sentence retrieval
SPIRE'07 Proceedings of the 14th international conference on String processing and information retrieval
Query expansion for language modeling using sentence similarities
IRFC'11 Proceedings of the Second international conference on Multidisciplinary information retrieval facility
Exploring accumulative query expansion for relevance feedback
INEX'10 Proceedings of the 9th international conference on Initiative for the evaluation of XML retrieval: comparative evaluation of focused retrieval
Summarizing highly structured documents for effective search interaction
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Effective sentence retrieval based on query-independent evidence
Information Processing and Management: an International Journal
Sentence length bias in TREC novelty track judgements
Proceedings of the Seventeenth Australasian Document Computing Symposium
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The retrieval of sentences that are relevant to a given information need is a challenging passage retrieval task. In this context, the well-known vocabulary mismatch problem arises severely because of the fine granularity of the task. Short queries, which are usually the rule rather than the exception, aggravate the problem. Consequently, effective sentence retrieval methods tend to apply some form of query expansion, usually based on pseudo-relevance feedback. Nevertheless, there are no extensive studies comparing different statistical expansion strategies for sentence retrieval. In this work we study thoroughly the effect of distinct statistical expansion methods on sentence retrieval. We start from a set of retrieved documents in which relevant sentences have to be found. In our experiments different term selection strategies are evaluated and we provide empirical evidence to show that expansion before sentence retrieval yields competitive performance. This is particularly novel because expansion for sentence retrieval is often done after sentence retrieval (i.e. expansion terms are mined from a ranked set of sentences) and there are no comparative results available between both types of expansion. Furthermore, this comparison is particularly valuable because there are important implications in time efficiency. We also carefully analyze expansion on weak and strong queries and demonstrate clearly that expanding queries before sentence retrieval is not only more convenient for efficiency purposes, but also more effective when handling poor queries.