HPS: High precision stemmer

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F15%3A43922745" target="_blank" >RIV/49777513:23520/15:43922745 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1016/j.ipm.2014.08.006" target="_blank" >http://dx.doi.org/10.1016/j.ipm.2014.08.006</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.ipm.2014.08.006" target="_blank" >10.1016/j.ipm.2014.08.006</a>

Jazyk výsledku

angličtina

Název v původním jazyce

HPS: High precision stemmer

Popis výsledku v původním jazyce

Research into unsupervised ways of stemming has resulted, in the past few years, in the development of methods that are reliable and perform well. Our approach further shifts the boundaries of the state of the art by providing more accurate stemming results. The idea of the approach consists in building a stemmer in two stages. In the first stage, a stemming algorithm based upon clustering, which exploits the lexical and semantic information of words, is used to prepare large-scale training data for thesecond-stage algorithm. The second-stage algorithm uses a maximum entropy classifier. The stemming-specific features help the classifier decide when and how to stem a particular word. In our research, we have pursued the goal of creating a multi-purposestemming tool. Its design opens up possibilities of solving non-traditional tasks such as approximating lemmas or improving language modeling. However, we still aim at very good results in the traditional task of information retrieval. T

Název v anglickém jazyce

HPS: High precision stemmer

Popis výsledku anglicky

Research into unsupervised ways of stemming has resulted, in the past few years, in the development of methods that are reliable and perform well. Our approach further shifts the boundaries of the state of the art by providing more accurate stemming results. The idea of the approach consists in building a stemmer in two stages. In the first stage, a stemming algorithm based upon clustering, which exploits the lexical and semantic information of words, is used to prepare large-scale training data for thesecond-stage algorithm. The second-stage algorithm uses a maximum entropy classifier. The stemming-specific features help the classifier decide when and how to stem a particular word. In our research, we have pursued the goal of creating a multi-purposestemming tool. Its design opens up possibilities of solving non-traditional tasks such as approximating lemmas or improving language modeling. However, we still aim at very good results in the traditional task of information retrieval. T

Druh

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

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

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Projekt

<a href="/cs/project/ED1.1.00%2F02.0090" target="_blank" >ED1.1.00/02.0090: NTIS - Nové technologie pro informační společnost</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

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

Název periodika

Information Processing and Mangement

ISSN

0306-4573

e-ISSN

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Svazek periodika

51

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

24

Strana od-do

68-91

Kód UT WoS článku

000345491900005

EID výsledku v databázi Scopus

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