Web content mining using MicroGenres

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F10%3A86080924" target="_blank" >RIV/61989100:27240/10:86080924 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-642-14461-5_4" target="_blank" >http://dx.doi.org/10.1007/978-3-642-14461-5_4</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-642-14461-5_4" target="_blank" >10.1007/978-3-642-14461-5_4</a>

Result language
angličtina
Original language name
Web content mining using MicroGenres
Original language description
The size and growth of the current Web is still creating new challenges to researchers. For example, one of these challenges is the improvement of user familarity to a large number of Web pages. Today's search engines provide tools that allow users to refine their queries. One way is the refinement of a query based on the analysis of web content. Possible outcomes are not only recommended collocations, but also recommended page genres (e.g., discussion forums, etc.). It is proving to be very useful to provide the details of page content when viewing the page. Not only text snippets, but also parts of the page menu, for certain pages how many posts are present in the discussion, what day the review was created, or what the price is of a product sold onthe page. Obtaining this information from unstructured or semi-structured content is not straightforward. In this chapter the development of methods capable of detecting and extracting information from Web pages will be addressed. The con
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
IN - Informatics
OECD FORD branch
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Publication year
2010
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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