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
Searching the Web: the public and their queries
Journal of the American Society for Information Science and Technology
Capitalization Recovery for Text
Information Retrieval Techniques for Speech Applications [this book is based on the workshop “Information Retrieval Techniques for Speech Applications”, held as part of the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in New Orleans, USA, in September 2001].
History repeats itself: repeat queries in Yahoo's logs
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Restoring punctuation and capitalization in transcribed speech
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
CLEF 2006: ad hoc track overview
CLEF'06 Proceedings of the 7th international conference on Cross-Language Evaluation Forum: evaluation of multilingual and multi-modal information retrieval
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User queries to search engines are observed to predominantly contain inflected content words but lack stopwords and capitalization. Thus, they often resemble natural language queries after case folding and stopword removal. Query recovery aims to generate a linguistically well-formed query from a given user query as input to provide natural language processing tasks and cross-language information retrieval (CLIR). The evaluation of query translation shows that translation scores (NIST and BLEU) decrease after case folding, stopword removal, and stemming. A baseline method for query recovery reconstructs capitalization and stopwords, which considerably increases translation scores and significantly increases mean average precision for a standard CLIR task.