Placing search in context: the concept revisited

    ACM Transactions on Information Systems (TOIS), pp. 116-131, 2002.

    Cited by: 1709|Bibtex|Views33|Links
    EI
    Keywords:
    non-trivial information needdomain-specific search enginesemantic processingmarked queryaugmented queryMore(12+)
    Wei bo:
    The goal of the experiment described below was to determine what number of keywords in a keyword-based search engine is equivalent to using the context with our IntelliZap system

    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 l...More

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    Introduction
    • Given the constantly increasing information overflow of the digital age, the importance of information retrieval has become critical.
    • Web search is today one of the most challenging problems of the Internet, striving at providing users with search results most relevant to their information needs.
    • Internet search engines evolved through several generations since their inception in 1994, progressing from simple keyword matching to techniques such as link analysis and relevance feedback [11].
    • Search engines have entered their third generation, and current research efforts continue to be aimed at increasing coverage and relevance
    Highlights
    • Given the constantly increasing information overflow of the digital age, the importance of information retrieval has become critical
    • We propose an approach that changes the basic settings of the search scene by using the context of the query as an additional input
    • The goal of the experiment described below was to determine what number of keywords in a keyword-based search engine is equivalent to using the context with our IntelliZap system
    • Each subject was presented with three short texts and was asked to find information relevant to the text using IntelliZap and each of the following search engines: Google, Yahoo!, AltaVista, and Northern Light13
    • The subjects were asked to search for relevant information using one, two and three keywords using each of the search engines
    • This paper describes a novel algorithm and system for processing queries in their context
    Results
    • The authors discuss a series of experiments conducted on the IntelliZap system.
    • A survey conducted by the NEC Research Institute shows that about 70% of Web users typically use only a single keyword or search term [3].
    • Each subject was presented with three short texts and was asked to find information relevant to the text using IntelliZap and each of the following search engines: Google, Yahoo!, AltaVista, and Northern Light13.
    • The subjects were asked to search for relevant information using one, two and three keywords using each of the search engines.
    • The non-monotonic behavior of the number of relevant results among the stages is due to the usage of different texts
    Conclusion
    • This paper describes a novel algorithm and system for processing queries in their context.
    • Using the context surrounding the marked queries, the system enables even inexperienced web searchers to obtain satisfactory results.
    • This is done by autonomously generating augmented queries, and by autonomously selecting relevant search engine sites to which the queries are targeted.
    • Context should be utilized to expand the augmented queries in a disambiguated manner.
    • More work could be done on tailoring the generic approach shown here for maximizing the context-guided capabilities of individual search engines
    Summary
    • Introduction:

      Given the constantly increasing information overflow of the digital age, the importance of information retrieval has become critical.
    • Web search is today one of the most challenging problems of the Internet, striving at providing users with search results most relevant to their information needs.
    • Internet search engines evolved through several generations since their inception in 1994, progressing from simple keyword matching to techniques such as link analysis and relevance feedback [11].
    • Search engines have entered their third generation, and current research efforts continue to be aimed at increasing coverage and relevance
    • Results:

      The authors discuss a series of experiments conducted on the IntelliZap system.
    • A survey conducted by the NEC Research Institute shows that about 70% of Web users typically use only a single keyword or search term [3].
    • Each subject was presented with three short texts and was asked to find information relevant to the text using IntelliZap and each of the following search engines: Google, Yahoo!, AltaVista, and Northern Light13.
    • The subjects were asked to search for relevant information using one, two and three keywords using each of the search engines.
    • The non-monotonic behavior of the number of relevant results among the stages is due to the usage of different texts
    • Conclusion:

      This paper describes a novel algorithm and system for processing queries in their context.
    • Using the context surrounding the marked queries, the system enables even inexperienced web searchers to obtain satisfactory results.
    • This is done by autonomously generating augmented queries, and by autonomously selecting relevant search engine sites to which the queries are targeted.
    • Context should be utilized to expand the augmented queries in a disambiguated manner.
    • More work could be done on tailoring the generic approach shown here for maximizing the context-guided capabilities of individual search engines
    Related work
    • Using context for search is not a new idea. A number of existing information retrieval systems utilize the notion of context to some extent. The problem is, however, that everyone defines context a little differently.

      Lawrence [8] contains an elaborate review of using context in Web search. Explicit context information can be supplied to a search engine in the form of a category restriction3. Such a category may considerably disambiguate a query and thus focus the results. For instance, given the search term “jaguar”, possible categories are “fauna” or “cars”. Inquirus-2 project [7] specifically requests context information in this way.
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