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A Co-occurrence Based Personal Sense Approach to Opinion Mining. / Panicheva, P.; Cardiff, J.; Rosso, P.

1st Workshop on Opinion Mining and Sentiment Analysis (WOMSA), CAEPIA-TTIA Conference (2009). 2009. стр. 205-212.

Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференцийстатья в сборнике материалов конференции

Harvard

Panicheva, P, Cardiff, J & Rosso, P 2009, A Co-occurrence Based Personal Sense Approach to Opinion Mining. в 1st Workshop on Opinion Mining and Sentiment Analysis (WOMSA), CAEPIA-TTIA Conference (2009). стр. 205-212.

APA

Panicheva, P., Cardiff, J., & Rosso, P. (2009). A Co-occurrence Based Personal Sense Approach to Opinion Mining. в 1st Workshop on Opinion Mining and Sentiment Analysis (WOMSA), CAEPIA-TTIA Conference (2009) (стр. 205-212)

Vancouver

Panicheva P, Cardiff J, Rosso P. A Co-occurrence Based Personal Sense Approach to Opinion Mining. в 1st Workshop on Opinion Mining and Sentiment Analysis (WOMSA), CAEPIA-TTIA Conference (2009). 2009. стр. 205-212

Author

Panicheva, P. ; Cardiff, J. ; Rosso, P. / A Co-occurrence Based Personal Sense Approach to Opinion Mining. 1st Workshop on Opinion Mining and Sentiment Analysis (WOMSA), CAEPIA-TTIA Conference (2009). 2009. стр. 205-212

BibTeX

@inproceedings{0fd87829d7e940d78b118df07bbf53d0,
title = "A Co-occurrence Based Personal Sense Approach to Opinion Mining",
abstract = "Recent years have seen increasing interest in analyzing the millions of texts published every year in blogs and forums. One of the applications attracting most attention is the automated gathering opinions of people on different products. In this paper, we elaborate a methodology for opinion mining and subjectivity analysis, based on the notion of personal sense. Our hypothesis is that the personal sense of the words that the author uses in a text is reflected their appraisal of a product described in the text. In this preliminary work, we describe a new methodology applied to the polarity classification task, and present and evaluate our the preliminary results.",
keywords = "Opinion mining, personal sense, polarity classification.",
author = "P. Panicheva and J. Cardiff and P. Rosso",
year = "2009",
language = "English",
pages = "205--212",
booktitle = "1st Workshop on Opinion Mining and Sentiment Analysis (WOMSA), CAEPIA-TTIA Conference (2009)",

}

RIS

TY - GEN

T1 - A Co-occurrence Based Personal Sense Approach to Opinion Mining

AU - Panicheva, P.

AU - Cardiff, J.

AU - Rosso, P.

PY - 2009

Y1 - 2009

N2 - Recent years have seen increasing interest in analyzing the millions of texts published every year in blogs and forums. One of the applications attracting most attention is the automated gathering opinions of people on different products. In this paper, we elaborate a methodology for opinion mining and subjectivity analysis, based on the notion of personal sense. Our hypothesis is that the personal sense of the words that the author uses in a text is reflected their appraisal of a product described in the text. In this preliminary work, we describe a new methodology applied to the polarity classification task, and present and evaluate our the preliminary results.

AB - Recent years have seen increasing interest in analyzing the millions of texts published every year in blogs and forums. One of the applications attracting most attention is the automated gathering opinions of people on different products. In this paper, we elaborate a methodology for opinion mining and subjectivity analysis, based on the notion of personal sense. Our hypothesis is that the personal sense of the words that the author uses in a text is reflected their appraisal of a product described in the text. In this preliminary work, we describe a new methodology applied to the polarity classification task, and present and evaluate our the preliminary results.

KW - Opinion mining

KW - personal sense

KW - polarity classification.

M3 - Conference contribution

SP - 205

EP - 212

BT - 1st Workshop on Opinion Mining and Sentiment Analysis (WOMSA), CAEPIA-TTIA Conference (2009)

ER -

ID: 4687572