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Cited by 425

The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.

Placing search in context: the concept revisited

·2002·ACM Transactions on Information Systems

Abstract

Keyword-based search engines are in widespread use today as a popular means for Web-based information retrieval. Although such systems seem deceptively simple, a considerable amount of skill is required in order to satisfy non-trivial information needs. This paper presents a new conceptual paradigm for performing search in context, that largely automates the search process, providing even non-professional users with highly relevant results. This paradigm is implemented in practice in the IntelliZap system, where search is initiated from a text query marked by the user in a document she views, and is guided by the text surrounding the marked query in that document ("the context"). The context-driven information retrieval process involves semantic keyword extraction and clustering to automatically generate new, augmented queries. The latter are submitted to a host of general and domain-specific search engines. Search results are then semantically reranked, using context. Experimental results testify that using context to guide search, effectively offers even inexperienced users an advanced search tool on the Web.

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Metadata

Venue
ACM Transactions on Information Systems
Published
2002-01
Volume
20
Issue
1
Pages
116-131
ISSN
  • 1046-8188 (ISSN-L)
  • 1558-2868
OpenAlex
W3216404684
Cited by
425
References
16
FWCI
12.96
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Placing search in context: the concept revisited. https://app.cochat.ai/papers/10.1145/503104.503110
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Placing search in context: the concept revisited. (2002). ACM Transactions on Information Systems. https://doi.org/10.1145/503104.503110

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.