Gene Interaction Extraction from Biomedical Texts by Sentence Skeletonization

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F11%3A00185142" target="_blank" >RIV/68407700:21230/11:00185142 - isvavai.cz</a>

Výsledek na webu

<a href="http://ceur-ws.org/Vol-802/" target="_blank" >http://ceur-ws.org/Vol-802/</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Gene Interaction Extraction from Biomedical Texts by Sentence Skeletonization

Popis výsledku v původním jazyce

The presented paper describes a method of text preprocessing improving the performance of sequential data mining applied in the task of gene interaction extraction from biomedical texts. The need of text preprocessing rises primarily from the fact, thatthe language encoded by any general word sequence is mostly not sequential. The method involves a number of heuristic language transformations, all together converting sentences into forms with higher degree of sequentiality. The core idea of enhancing sentence sequentiality results from the observation that the components constituting the semantical and grammatical content of sentences are not equally relevant for extracting a highly specific type of information. Experiments employing a simple sequential algorithm confirmed the usability of the proposed text preprocessing in the gene interaction extraction task.

Název v anglickém jazyce

Gene Interaction Extraction from Biomedical Texts by Sentence Skeletonization

Popis výsledku anglicky

The presented paper describes a method of text preprocessing improving the performance of sequential data mining applied in the task of gene interaction extraction from biomedical texts. The need of text preprocessing rises primarily from the fact, thatthe language encoded by any general word sequence is mostly not sequential. The method involves a number of heuristic language transformations, all together converting sentences into forms with higher degree of sequentiality. The core idea of enhancing sentence sequentiality results from the observation that the components constituting the semantical and grammatical content of sentences are not equally relevant for extracting a highly specific type of information. Experiments employing a simple sequential algorithm confirmed the usability of the proposed text preprocessing in the gene interaction extraction task.

Druh

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

CEP obor

JC - Počítačový hardware a software

OECD FORD obor

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Projekt

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Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2011

Kód důvěrnosti údajů

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

Název periodika

CEUR workshop proceedings

ISSN

1613-0073

e-ISSN

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Svazek periodika

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Číslo periodika v rámci svazku

802

Stát vydavatele periodika

DE - Spolková republika Německo

Počet stran výsledku

12

Strana od-do

1-12

Kód UT WoS článku

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EID výsledku v databázi Scopus

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