Research of sentiment block identification for customer reviews based on conditional random fields

Lei Jiang; Yuanchao Liu; Bingquan Liu; Chengjie Sun; Xiaolong Wang

doi:10.1007/978-3-642-17187-1_25

Research of sentiment block identification for customer reviews based on conditional random fields

Lei Jiang^*
, Yuanchao Liu
, Bingquan Liu
, Chengjie Sun
, Xiaolong Wang

^*Corresponding author for this work

School of Computer Science and Technology, Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

Many customer reviews are expressed freely and informally, thus it will bring obstacle for sentiment analysis. In this paper, we aim at finding a method to identify sentiment block from the consumer reviews. The main idea of this paper is to treat this task as a word sequence labeling problem and solved with conditional random fields model (CRF) by introducing template feature. Experimental results show that our approach can identify most sentiment blocks from customer reviews and correspondingly find the sentiment polarity of the blocks correctly.

Original language	English
Title of host publication	Information Retrieval Technology - 6th Asia Information Retrieval Societies Conference, AIRS 2010, Proceedings
Pages	261-269
Number of pages	9
DOIs	https://doi.org/10.1007/978-3-642-17187-1_25
State	Published - 2010
Externally published	Yes
Event	6th Asia Information Retrieval Societies Conference, AIRS 2010 - Taipei, Taiwan, Province of China Duration: 1 Dec 2010 → 3 Dec 2010

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	6458 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	6th Asia Information Retrieval Societies Conference, AIRS 2010
Country/Territory	Taiwan, Province of China
City	Taipei
Period	1/12/10 → 3/12/10

Keywords

Customer review mining
conditional random fields
sentiment block identification
template feature

Access to Document

10.1007/978-3-642-17187-1_25

Cite this

Jiang, L., Liu, Y., Liu, B., Sun, C., & Wang, X. (2010). Research of sentiment block identification for customer reviews based on conditional random fields. In Information Retrieval Technology - 6th Asia Information Retrieval Societies Conference, AIRS 2010, Proceedings (pp. 261-269). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6458 LNCS). https://doi.org/10.1007/978-3-642-17187-1_25

Jiang, Lei ; Liu, Yuanchao ; Liu, Bingquan et al. / Research of sentiment block identification for customer reviews based on conditional random fields. Information Retrieval Technology - 6th Asia Information Retrieval Societies Conference, AIRS 2010, Proceedings. 2010. pp. 261-269 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{43956750c59e433abd79118ecdb4fd4c,

title = "Research of sentiment block identification for customer reviews based on conditional random fields",

abstract = "Many customer reviews are expressed freely and informally, thus it will bring obstacle for sentiment analysis. In this paper, we aim at finding a method to identify sentiment block from the consumer reviews. The main idea of this paper is to treat this task as a word sequence labeling problem and solved with conditional random fields model (CRF) by introducing template feature. Experimental results show that our approach can identify most sentiment blocks from customer reviews and correspondingly find the sentiment polarity of the blocks correctly.",

keywords = "Customer review mining, conditional random fields, sentiment block identification, template feature",

author = "Lei Jiang and Yuanchao Liu and Bingquan Liu and Chengjie Sun and Xiaolong Wang",

year = "2010",

doi = "10.1007/978-3-642-17187-1\_25",

language = "英语",

isbn = "3642171869",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

pages = "261--269",

booktitle = "Information Retrieval Technology - 6th Asia Information Retrieval Societies Conference, AIRS 2010, Proceedings",

note = "6th Asia Information Retrieval Societies Conference, AIRS 2010 ; Conference date: 01-12-2010 Through 03-12-2010",

}

Jiang, L, Liu, Y , Liu, B , Sun, C & Wang, X 2010, Research of sentiment block identification for customer reviews based on conditional random fields. in Information Retrieval Technology - 6th Asia Information Retrieval Societies Conference, AIRS 2010, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6458 LNCS, pp. 261-269, 6th Asia Information Retrieval Societies Conference, AIRS 2010, Taipei, Taiwan, Province of China, 1/12/10. https://doi.org/10.1007/978-3-642-17187-1_25

Research of sentiment block identification for customer reviews based on conditional random fields. / Jiang, Lei; Liu, Yuanchao ; Liu, Bingquan et al.
Information Retrieval Technology - 6th Asia Information Retrieval Societies Conference, AIRS 2010, Proceedings. 2010. p. 261-269 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6458 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Research of sentiment block identification for customer reviews based on conditional random fields

AU - Jiang, Lei

AU - Liu, Yuanchao

AU - Liu, Bingquan

AU - Sun, Chengjie

AU - Wang, Xiaolong

PY - 2010

Y1 - 2010

N2 - Many customer reviews are expressed freely and informally, thus it will bring obstacle for sentiment analysis. In this paper, we aim at finding a method to identify sentiment block from the consumer reviews. The main idea of this paper is to treat this task as a word sequence labeling problem and solved with conditional random fields model (CRF) by introducing template feature. Experimental results show that our approach can identify most sentiment blocks from customer reviews and correspondingly find the sentiment polarity of the blocks correctly.

AB - Many customer reviews are expressed freely and informally, thus it will bring obstacle for sentiment analysis. In this paper, we aim at finding a method to identify sentiment block from the consumer reviews. The main idea of this paper is to treat this task as a word sequence labeling problem and solved with conditional random fields model (CRF) by introducing template feature. Experimental results show that our approach can identify most sentiment blocks from customer reviews and correspondingly find the sentiment polarity of the blocks correctly.

KW - Customer review mining

KW - conditional random fields

KW - sentiment block identification

KW - template feature

UR - https://www.scopus.com/pages/publications/78650885882

U2 - 10.1007/978-3-642-17187-1_25

DO - 10.1007/978-3-642-17187-1_25

M3 - 会议稿件

AN - SCOPUS:78650885882

SN - 3642171869

SN - 9783642171864

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 261

EP - 269

BT - Information Retrieval Technology - 6th Asia Information Retrieval Societies Conference, AIRS 2010, Proceedings

T2 - 6th Asia Information Retrieval Societies Conference, AIRS 2010

Y2 - 1 December 2010 through 3 December 2010

ER -

Jiang L, Liu Y , Liu B , Sun C, Wang X. Research of sentiment block identification for customer reviews based on conditional random fields. In Information Retrieval Technology - 6th Asia Information Retrieval Societies Conference, AIRS 2010, Proceedings. 2010. p. 261-269. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-17187-1_25

Research of sentiment block identification for customer reviews based on conditional random fields

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