Importance

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Abstract

Tables form an important kind of data element in text retrieval. Often, the gist of an entire news article or other exposition can be concisely captured in tabular form. Information other than the key words in a digital document can be exploited to provide the users with more flexible and powerful query capabilities. More specifically, the structural information in a document is exploited to identify tables and their component fields and let the users query based on these fields. Component fields can include table lines, caption lines, row headings, column headings, or other table components. Empirical results have demonstrated that heuristic method based table extraction and component tagging can be performed effectively and efficiently. Moreover, experiments in retrieval using the system of the present invention strongly indicate that such structural decomposition can facilitate better representation of user's information needs and hence more effective retrieval of tables.

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First Claim