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A General Information Extraction Framework Based on Formal Languages
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DOI：10.1007/978-3-032-01475-7_14.png)
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Abstract
En 中文
For a terminal alphabet.S and an attribute alphabet Gamma, a.(Sigma, Gamma)-extractor is a function that maps every string over Sigma to a table with a column per attribute and with sets of positions of.w as cell entries. This rather general information extraction framework extends the wellknown document spanner framework, which has intensively been investigated in the database theory community over the last decade. Moreover, our framework is based on formal language theory in a particularly clean and simple way. In addition to this conceptual contribution, we investigate closure properties, different representation formalisms and the complexity of natural decision problems for extractors.
Keywords:
Information Extraction
Regular Languages
Context-Free Languages
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