Abstract
Data on the Web in HTML tables is mostly structured, but we usually do not know the structure in advance. Thus, we cannot directly query for data of interest. We propose a solution to this problem based on document-independent extraction ontologies. The solution entails elements of table understanding, data integration, and wrapper creation. Table understanding allows us to recognize attributes and values, pair attributes with values, and form records. Data-integration techniques allow us to match source records with a target schema. Ontologically specified wrappers allow us to extract data from source records into a target schema. Experimental results show that we can successfully map data of interest from source HTML tables with unknown structure to a given target database schema. We can thus “directly” query source data with unknown structure through a known target schema.
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Embley, D.W., Tao, C., Liddle, S.W. (2002). Automatically Extracting Ontologically Specified Data from HTML Tables of Unknown Structure. In: Spaccapietra, S., March, S.T., Kambayashi, Y. (eds) Conceptual Modeling — ER 2002. ER 2002. Lecture Notes in Computer Science, vol 2503. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45816-6_32
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DOI: https://doi.org/10.1007/3-540-45816-6_32
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