A linear-chain CRF-based learning approach for web opinion mining

Luole Qi*, Li CHEN

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

21 Citations (Scopus)


The task of opinion mining from product reviews is to extract the product entities and determine whether the opinions on the entities are positive, negative or neutral. Reasonable performance on this task has been achieved by employing rule-based, statistical approaches or generative learning models such as hidden Markov model (HMMs). In this paper, we proposed a discriminative model using linear-chain Conditional Random Field (CRFs) for opinion mining. CRFs can naturally incorporate arbitrary, non-independent features of the input without making conditional independence assumptions among the features. This can be particularly important for opinion mining on product reviews. We evaluated our approach base on three criteria: recall, precision and F-score for extracted entities, opinions and their polarities. Compared to other methods, our approach was proven more effective for accomplishing opinion mining tasks.

Original languageEnglish
Title of host publicationWeb Information Systems Engineering, WISE 2010 - 11th International Conference, Proceedings
Number of pages14
Publication statusPublished - 2010
Event11th International Conference on Web Information Systems Engineering, WISE 2010 - , Hong Kong
Duration: 12 Dec 201014 Dec 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6488 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference11th International Conference on Web Information Systems Engineering, WISE 2010
Country/TerritoryHong Kong
Internet address

Scopus Subject Areas

  • Theoretical Computer Science
  • Computer Science(all)

User-Defined Keywords

  • Conditional Random Field (CRFs)
  • Feature Function
  • Web Opinion Mining


Dive into the research topics of 'A linear-chain CRF-based learning approach for web opinion mining'. Together they form a unique fingerprint.

Cite this