Web content mining using MicroGenres

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

Web content mining using MicroGenres

Popis výsledku v původním jazyce

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

Název v anglickém jazyce

Web content mining using MicroGenres

Popis výsledku anglicky

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

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2010

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Studies in Computational Intelligence

ISSN

1860-949X

e-ISSN

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Svazek periodika

311

Číslo periodika v rámci svazku

2010

Stát vydavatele periodika

DE - Spolková republika Německo

Počet stran výsledku

32

Strana od-do

79-111

Kód UT WoS článku

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EID výsledku v databázi Scopus

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