Selecting text entries using a few positive samples and similarity ranking

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43110%2F11%3A00173470" target="_blank" >RIV/62156489:43110/11:00173470 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Selecting text entries using a few positive samples and similarity ranking

Popis výsledku v původním jazyce

This research was inspired by procedures that are used by human bibliographic searchers: Given some textual and only 'positive' (relevant, interesting) examples coming just from one category, find promptly and simply in an available collection of variousunlabeled documents the most similar ones that belong to a relevant topic defined by an applicant. The problem of the categorization of unlabeled relevant and irrelevant textual documents is here solved by using a small subset of relevant available patterns labeled manually in advance. Unlabeled text items are compared with such labeled patterns. The unlabeled samples are then ranked according their degree of similarity with the patterns. At the top of the rank, there are the most similar (relevant) items. Entries receding from the rank top represent gradually less and less similar entries. The authors emphasize that this simple method, aimed at processing large volumes of text entries, provides initial filtering results from the accur

Název v anglickém jazyce

Selecting text entries using a few positive samples and similarity ranking

Popis výsledku anglicky

This research was inspired by procedures that are used by human bibliographic searchers: Given some textual and only 'positive' (relevant, interesting) examples coming just from one category, find promptly and simply in an available collection of variousunlabeled documents the most similar ones that belong to a relevant topic defined by an applicant. The problem of the categorization of unlabeled relevant and irrelevant textual documents is here solved by using a small subset of relevant available patterns labeled manually in advance. Unlabeled text items are compared with such labeled patterns. The unlabeled samples are then ranked according their degree of similarity with the patterns. At the top of the rank, there are the most similar (relevant) items. Entries receding from the rank top represent gradually less and less similar entries. The authors emphasize that this simple method, aimed at processing large volumes of text entries, provides initial filtering results from the accur

Druh

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

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

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Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2011

Kód důvěrnosti údajů

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

Název periodika

Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis

ISSN

1211-8516

e-ISSN

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Svazek periodika

LIX

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

10

Strana od-do

399-408

Kód UT WoS článku

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EID výsledku v databázi Scopus

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