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A Conceptual-Modeling Approach to Extracting Data from the Web
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In: http://www.deg.byu.edu/papers/er98.ps (1998)
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Abstract:
Electronically available data on the Web is exploding at an ever increasing pace. Much of this data is unstructured, which makes searching hard and traditional database querying impossible. Many Web documents, however, contain an abundance of recognizable constants that together describe the essence of a document's content. For these kinds of data-rich documents (e.g., advertisements, movie reviews, weather reports, travel information, sports summaries, financial statements, obituaries, and many others) we can apply a conceptual-modeling approach to extract and structure data. The approach is based on an ontology---a conceptual model instance---that describes the data of interest, including relationships, lexical appearance, and context keywords. By parsing the ontology, we can automatically produce a database scheme and recognizers for constants and keywords, and then invoke routines to recognize and extract data from unstructured documents and structure it according to the.
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Keyword:
data extraction; data structuring; data-rich document; obituary; ontological conceptual modeling; ontology; unstructured data; World-Wide Web
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URL: http://www.deg.byu.edu/papers/er98.ps
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.33.2789
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| 22 |
Constructing Controlled English for Both Human Usage and Machine Processing
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In: http://ceur-ws.org/Vol-1004/paper14.pdf
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| 23 |
International Journal of Signal Processing, Image Processing and Pattern Recognition 55 Unstructured Document Categorization: A Study
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In: http://www.sersc.org/journals/IJSIP/vol1_no1/papers/07.pdf
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| 24 |
Unstructured Content Analysis & Classification System for the IRS R.Palson Kennedy
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In: http://www.ijcaonline.org/allpdf/pxc387216.pdf
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