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One factor that may affect whether users of technical support Web sites can rapidly find information relevant to their needs is the quality of the summary of documents returned as the result of search queries. This paper reports on two studies that were part of an effort to create high-quality machine-generated summaries for the presentation of search results for technical support documents. The initial study asked experts to compose document summaries. The results of the first study were used to guide the development of heuristics for generating programmatic summaries that were tested in the second study, which was a user evaluation that compared the effectiveness of four types of document summaries for search purposes: programmatic summaries based on selective sentence extraction using knowledge of the semantic structure of documents, a term-hits-in-context (THIC) summary, the current summaries on the company's live site, and document titles alone. This comparison sought to determine the techniques most likely to help users find information, hence increasing customer goal attainment and satisfaction. The implications of our results for summarizing technical support documents for search are discussed.
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