Learning (k,l)-contextual tree languages for information extraction from web pages
نویسندگان
چکیده
منابع مشابه
Learning (k, l)-Contextual Tree Languages for Information Extraction
Learning regular languages from positive examples only is known to be infeasible. A common solution is to define a learnable subclass of the regular languages. In the past, this has been done for regular string languages. Using ideas from those techniques, we define a learnable subclass of regular unranked tree languages, called the (k,l)-contextual tree languages. We describe the use of this s...
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Recently, several wrapper induction algorithms for structured documents have been introduced. They are based on contextual tree languages and learn from positive examples only but have the disadvantage that they need parameters. To obtain the optimal parameter setting, they use precision and recall. This goes in fact beyond learning from positive examples only. In this paper, a parameter estima...
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The problem of extracting information from the Web consists in building patterns allowing to extract specific information from documents of a given Web source. Up to now, most existing techniques use string-based representations of documents as well as string-based patterns. Using tree representations naturally allows to overcome limitations of string-based approaches. While some tree-based app...
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ژورنال
عنوان ژورنال: Machine Learning
سال: 2008
ISSN: 0885-6125,1573-0565
DOI: 10.1007/s10994-008-5049-7