Contrastive Summarization: Comparing Opinions of Czech Senators

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F15%3A43925836" target="_blank" >RIV/49777513:23520/15:43925836 - 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

Contrastive Summarization: Comparing Opinions of Czech Senators

Popis výsledku v původním jazyce

In this paper, we present a novel approach to contrastive summarization, i.e. a specific type of summarization, which aims to compare two documents (or groups of documents) on semantic and also sentiment level. The final output of contrastive summarization is a pair of summaries, depicting what topics are most often discussed with the largest difference in opinions of the authors. We explore the possibilities of combining the latent semantic information with the information about the opinions of the authors. First, we describe related works, which show, that this problem can be approached from many different directions. Next, we present our own algorithm, based on Latent Semantic Analysis, which computes scores for excerpts of the original text and based on these, it chooses best excerpts that should be included into the final summaries. Finally, we present the evaluation of our algorithm, using speeches from Czech senate.

Název v anglickém jazyce

Contrastive Summarization: Comparing Opinions of Czech Senators

Popis výsledku anglicky

In this paper, we present a novel approach to contrastive summarization, i.e. a specific type of summarization, which aims to compare two documents (or groups of documents) on semantic and also sentiment level. The final output of contrastive summarization is a pair of summaries, depicting what topics are most often discussed with the largest difference in opinions of the authors. We explore the possibilities of combining the latent semantic information with the information about the opinions of the authors. First, we describe related works, which show, that this problem can be approached from many different directions. Next, we present our own algorithm, based on Latent Semantic Analysis, which computes scores for excerpts of the original text and based on these, it chooses best excerpts that should be included into the final summaries. Finally, we present the evaluation of our algorithm, using speeches from Czech senate.

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

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

Journal of Theoretical and Applied Information Technology

ISSN

1992-8645

e-ISSN

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Svazek periodika

77

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

PK - Pákistánská islámská republika

Počet stran výsledku

7

Strana od-do

62-68

Kód UT WoS článku

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EID výsledku v databázi Scopus

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