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Statystyczne metody klasyfikacji tekstów

dc.contributor.authorIdczak, Adam
dc.contributor.authorKorzeniewski, Jerzy
dc.date.accessioned2022-04-04T12:07:21Z
dc.date.available2022-04-04T12:07:21Z
dc.date.issued2022
dc.identifier.citationIdczak A., Korzeniewski J., Statystyczne metody klasyfikacji tekstów, WUŁ, Łódź 2022, https://doi.org/10.18778/8220-786-6pl_PL
dc.identifier.isbn978-83-8220-786-6
dc.identifier.urihttp://hdl.handle.net/11089/41490
dc.description.abstractW ostatnich latach, wraz z szybkim rozwojem technologii komputerowych i internetowych, coraz większego znaczenia nabierają komputerowe metody badania tekstu, w szczególności metody ustalania sentymentu czy też wydźwięku tekstu. Metody komputerowe mogą być później wykorzystywane w takich zagadnieniach, jak streszczanie tekstu, wyszukiwanie informacji z tekstu, sprawdzanie poprawności tekstu, maszynowe tłumaczenie tekstu i wielu innych. Niniejsza monografia zawiera przegląd metod analizy sentymentu dla dokumentów głównie anglojęzycznych, badanie efektywności wybranych metod analizy sentymentu w zastosowaniu do dokumentów polskojęzycznych, propozycje nowych metod, które mogą poprawić jakość klasyfikacji. W nowych propozycjach nacisk został położony na problemy klasyfikacji binarnej, niekorzystanie ze źródeł zewnętrznych, korzystanie w jak najmniejszym stopniu ze zbioru uczącego. Proponujemy przenieść ciężar klasyfikacji tekstów z obszernego zbioru uczącego na wyszukiwanie i analizowanie związków pomiędzy słowami tworzącymi dokument, a nawet grupami słów. Zaproponowana metoda ma prostą interpretację, może konkurować z metodami standardowymi oraz może być wykorzystana do innych problemów związanych z ustalaniem sentymentu tekstów.pl_PL
dc.language.isoplpl_PL
dc.publisherWydawnictwo Uniwersytetu Łódzkiegopl_PL
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Międzynarodowe*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectsentyment dokumentupl_PL
dc.subjectklasyfikacja dokumentupl_PL
dc.subjectkomputerowe metody uczenia siępl_PL
dc.subjectkorelacja liniowapl_PL
dc.subjectmetoda SVMpl_PL
dc.subjectklasyfikator Bayesapl_PL
dc.titleStatystyczne metody klasyfikacji tekstówpl_PL
dc.typeBookpl_PL
dc.page.number142pl_PL
dc.contributor.authorAffiliationUniwersytet Łódzki, Wydział Ekonomiczno-Socjologiczny, Instytut Statystyki i Demografii, Katedra Metod Statystycznychpl_PL
dc.contributor.authorAffiliationUniwersytet Łódzki, Wydział Ekonomiczno-Socjologiczny, Instytut Statystyki i Demografii, Katedra Demografiipl_PL
dc.identifier.eisbn978-83-8220-787-3
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dc.identifier.doi10.18778/8220-786-6


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