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Description
  • Web 2.0 (social networking, blogging, online forums, etc.) has been growing at a very high rate and becoming a network of heterogeneous data; this makes things difficult to find and is therefore not almost useful. It is necessary to design suitable metric for such volume of information, which would reflect semantic content of pages in the better way. One of the options for more accurate comprehension of semantic information is to use a sophisticated analysis of sentences called Sentiment Analysis. This paper discusses a novel model for gathering and processing data from Web 2.0. The model builds on webometrics and starts from the idea that almost any text can be machine-recognized. This idea is further verified using proposed methodology for a trend assessment.
  • Web 2.0 (social networking, blogging, online forums, etc.) has been growing at a very high rate and becoming a network of heterogeneous data; this makes things difficult to find and is therefore not almost useful. It is necessary to design suitable metric for such volume of information, which would reflect semantic content of pages in the better way. One of the options for more accurate comprehension of semantic information is to use a sophisticated analysis of sentences called Sentiment Analysis. This paper discusses a novel model for gathering and processing data from Web 2.0. The model builds on webometrics and starts from the idea that almost any text can be machine-recognized. This idea is further verified using proposed methodology for a trend assessment. (en)
Title
  • Trend Classification Methodology
  • Trend Classification Methodology (en)
skos:prefLabel
  • Trend Classification Methodology
  • Trend Classification Methodology (en)
skos:notation
  • RIV/68407700:21230/13:00208807!RIV14-MSM-21230___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • S
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 111764
http://linked.open...ai/riv/idVysledku
  • RIV/68407700:21230/13:00208807
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Sentiment Analysis; Trend Classification; Web 2.0; Webometrics (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [E044B9F77735]
http://linked.open...v/mistoKonaniAkce
  • Fort Worth, TX
http://linked.open...i/riv/mistoVydani
  • Fort Worth, Texas
http://linked.open...i/riv/nazevZdroje
  • Proceedings of the IADIS International Conference WWW/INTERNET 2013
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Jelínek, Ivan
  • Malinský, Radek
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • IADIS Press
https://schema.org/isbn
  • 978-989-8533-16-6
http://localhost/t...ganizacniJednotka
  • 21230
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