Experiments on incorporating syntactic processing of user queries into a document retrieval strategy
SIGIR '88 Proceedings of the 11th annual international ACM SIGIR conference on Research and development in information retrieval
The use of phrases and structured queries in information retrieval
SIGIR '91 Proceedings of the 14th annual international ACM SIGIR conference on Research and development in information retrieval
Probabilistic models in information retrieval
The Computer Journal - Special issue on information retrieval
Using WordNet to disambiguate word senses for text retrieval
SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
Automatic routing and retrieval using Smart: TREC-2
TREC-2 Proceedings of the second conference on Text retrieval conference
A language modeling approach to information retrieval
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
IR evaluation methods for retrieving highly relevant documents
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Question-answering by predictive annotation
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
The use of phrases from query texts in information retrieval (poster session)
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Document language models, query models, and risk minimization for information retrieval
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Using part-of-speech patterns to reduce query ambiguity
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Computational Statistics & Data Analysis - Nonlinear methods and data mining
Incorporating query term dependencies in language models for document retrieval
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Detecting dominant locations from search queries
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
A Markov random field model for term dependencies
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Introduction to the CoNLL-2003 shared task: language-independent named entity recognition
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
An exploration of proximity measures in information retrieval
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Personal name classification in web queries
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
Trada: tree based ranking function adaptation
Proceedings of the 17th ACM conference on Information and knowledge management
Structural annotation of search queries using pseudo-relevance feedback
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Joint annotation of search queries
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Automated feature generation from structured knowledge
Proceedings of the 20th ACM international conference on Information and knowledge management
Extending BM25 with multiple query operators
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Two-Stage learning to rank for information retrieval
ECIR'13 Proceedings of the 35th European conference on Advances in Information Retrieval
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Most existing information retrieval (IR) systems do not take much advantage of natural language processing (NLP) techniques due to the complexity and limited observed effectiveness of applying NLP to IR. In this paper, we demonstrate that substantial gains can be obtained over a strong baseline using NLP techniques, if properly handled. We propose a framework for deriving semantic text matching features from named entities identified in Web queries; we then utilize these features in a supervised machine-learned ranking approach, applying a set of emerging machine learning techniques. Our approach is especially useful for queries that contain multiple types of concepts. Comparing to a major commercial Web search engine, we observe a substantial 4% DCG5 gain over the affected queries.