Placing search in context

Article Properties
Abstract
Journal Categories
Science
Mathematics
Instruments and machines
Electronic computers
Computer science
Science
Science (General)
Cybernetics
Information theory
Technology
Electrical engineering
Electronics
Nuclear engineering
Telecommunication
Technology
Technology (General)
Industrial engineering
Management engineering
Information technology
Description

Tired of irrelevant search results? This paper introduces a novel approach to web-based information retrieval, focusing on context-driven search to deliver highly relevant results for both professional and non-professional users. The study presents a new conceptual paradigm where search is initiated from a user-selected text query within a document. The key innovation lies in leveraging the surrounding text as "context" to guide the search process, automating query augmentation and refinement. This context-driven process involves semantic keyword extraction and clustering to generate new, augmented queries that are submitted to various search engines. Finally, search results are semantically reranked using the initial context, ensuring relevance. The IntelliZap system implements this paradigm, demonstrating its effectiveness in offering even inexperienced users an advanced search tool. Experimental results confirm that using context significantly improves the quality and relevance of search results, offering a powerful alternative to traditional keyword-based search engines.

Published in ACM Transactions on Information Systems, this research aligns with the journal's focus on information retrieval and management systems. The proposed search paradigm directly addresses challenges in information retrieval by leveraging context to improve search relevance, a key topic in the field. The development and evaluation of the IntelliZap system demonstrate practical applications of information system principles, aligning with the journal's emphasis on both theoretical and practical contributions.

Refrences
Citations
Citations Analysis
The first research to cite this article was titled The use of dynamic contexts to improve casual internet searching and was published in 2003. The most recent citation comes from a 2024 study titled The use of dynamic contexts to improve casual internet searching . This article reached its peak citation in 2019 , with 26 citations.It has been cited in 122 different journals, 11% of which are open access. Among related journals, the Natural Language Engineering cited this research the most, with 7 citations. The chart below illustrates the annual citation trends for this article.
Citations used this article by year