Towards interactive query expansion
SIGIR '88 Proceedings of the 11th annual international ACM SIGIR conference on Research and development in information retrieval
Constructing literature abstracts by computer: techniques and prospects
Information Processing and Management: an International Journal - Special issue on natural language processing and information retrieval
Query expansion using lexical-semantic relations
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Natural language information retrieval
TREC-2 Proceedings of the second conference on Text retrieval conference
A trainable document summarizer
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
Generating summaries of multiple news articles
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
Abstract generation based on rhetorical structure extraction
COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 1
A self-learning universal concept spotter
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 2
Applying summarization techniques for term selection in relevance feedback
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Generic summaries for indexing in information retrieval
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Using Semantics for Efficient Information Retrieval
NLDB '00 Proceedings of the 5th International Conference on Applications of Natural Language to Information Systems-Revised Papers
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We discuss a semi-interactive approach to information retrieval which consists of two tasks performed in a sequence. First, the system assists the searcher in building a comprehensive statement of information need, using automatically generated topical summaries of sample documents. Second, the detailed statement of information need is automatically processed by a series of natural language processing routines in order to derive an optimal search query for a statistical information retrieval system. In this paper, we investigate the role of automated document summarization in building effective search statements. We also discuss the results of latest evaluation of our system at the annual Text Retrieval Conference (TREC).