Collecting evaluative expressions for opinion extraction

Nozomi Kobayashi; Kentaro Inui; Yuji Matsumoto; Kenji Tateishi; Toshikazu Fukushima

doi:10.1007/978-3-540-30211-7_63

Collecting evaluative expressions for opinion extraction

Nozomi Kobayashi, Kentaro Inui, Yuji Matsumoto, Kenji Tateishi, Toshikazu Fukushima

INF - System Information Sciences

Research output: Contribution to journal › Conference article › peer-review

56 Citations (Scopus)

Abstract

Automatic extraction of human opinions from Web documents has been receiving increasing interest. To automate the process of opinion extraction, having a collection of evaluative expressions such as "something is confortable" would be useful. However, it can be costly to manually create an exhaustive list of such expressions for many domains, because they tend to be domain-dependent. Motivated by this, we explored ways to accelerate the process of collecting evaluative expressions by applying a text mining technique. This paper proposes a semi-automatic method that uses particular cooccurrence patterns of evaluated subjects, focused attributes and value expressions.

Original language	English
Pages (from-to)	596-605
Number of pages	10
Journal	Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
Volume	3248
DOIs	https://doi.org/10.1007/978-3-540-30211-7_63
Publication status	Published - 2005
Event	First International Joint Conference on Natural Language Processing - IJCNLP 2004 - Hainan Island, China Duration: 2004 Mar 22 → 2004 Mar 24

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

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title = "Collecting evaluative expressions for opinion extraction",

abstract = "Automatic extraction of human opinions from Web documents has been receiving increasing interest. To automate the process of opinion extraction, having a collection of evaluative expressions such as {"}something is confortable{"} would be useful. However, it can be costly to manually create an exhaustive list of such expressions for many domains, because they tend to be domain-dependent. Motivated by this, we explored ways to accelerate the process of collecting evaluative expressions by applying a text mining technique. This paper proposes a semi-automatic method that uses particular cooccurrence patterns of evaluated subjects, focused attributes and value expressions.",

author = "Nozomi Kobayashi and Kentaro Inui and Yuji Matsumoto and Kenji Tateishi and Toshikazu Fukushima",

note = "Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; First International Joint Conference on Natural Language Processing - IJCNLP 2004 ; Conference date: 22-03-2004 Through 24-03-2004",

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T1 - Collecting evaluative expressions for opinion extraction

AU - Kobayashi, Nozomi

AU - Inui, Kentaro

AU - Matsumoto, Yuji

AU - Tateishi, Kenji

AU - Fukushima, Toshikazu

PY - 2005

Y1 - 2005

N2 - Automatic extraction of human opinions from Web documents has been receiving increasing interest. To automate the process of opinion extraction, having a collection of evaluative expressions such as "something is confortable" would be useful. However, it can be costly to manually create an exhaustive list of such expressions for many domains, because they tend to be domain-dependent. Motivated by this, we explored ways to accelerate the process of collecting evaluative expressions by applying a text mining technique. This paper proposes a semi-automatic method that uses particular cooccurrence patterns of evaluated subjects, focused attributes and value expressions.

AB - Automatic extraction of human opinions from Web documents has been receiving increasing interest. To automate the process of opinion extraction, having a collection of evaluative expressions such as "something is confortable" would be useful. However, it can be costly to manually create an exhaustive list of such expressions for many domains, because they tend to be domain-dependent. Motivated by this, we explored ways to accelerate the process of collecting evaluative expressions by applying a text mining technique. This paper proposes a semi-automatic method that uses particular cooccurrence patterns of evaluated subjects, focused attributes and value expressions.

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SP - 596

EP - 605

JO - Lecture Notes in Computer Science

JF - Lecture Notes in Computer Science

SN - 0302-9743

T2 - First International Joint Conference on Natural Language Processing - IJCNLP 2004

Y2 - 22 March 2004 through 24 March 2004

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