Main Reference PaperIdentifying Features in Opinion Mining via Intrinsic and Extrinsic Domain Relevance, IEEE Transactions on Knowledge and Data Engineering, 2014.
  • This paper proposes a novel intercorpus statistics approach to opinion feature extraction based on the IEDR feature-filtering criterion, which utilizes the disparities in distributional characteristics of features across two corpora, one domain-specific and one domain-independent. IEDR identifies candidate features that are specific to the given review domain and yet not overly generic (domainindependent).

+ Description
  • This paper proposes a novel intercorpus statistics approach to opinion feature extraction based on the IEDR feature-filtering criterion, which utilizes the disparities in distributional characteristics of features across two corpora, one domain-specific and one domain-independent. IEDR identifies candidate features that are specific to the given review domain and yet not overly generic (domainindependent).

  • To improve efficiency of identification features.

  • To improve performance of opinion mining

+ Aim & Objectives
  • To improve efficiency of identification features.

  • To improve performance of opinion mining

  • The contribution work will employ fine-grained topic modeling approach to jointly identify opinion features, including non-noun features, infrequent features, as well as implicit features.

+ Contribution
  • The contribution work will employ fine-grained topic modeling approach to jointly identify opinion features, including non-noun features, infrequent features, as well as implicit features.

  • Java JDK 1.8, MySQL 5.5.40.

  • Netbeans 8.0.1 & J2SE

+ Software Tools & Technologies
  • Java JDK 1.8, MySQL 5.5.40.

  • Netbeans 8.0.1 & J2SE

  • B.E / B.Tech / M.E / M.Tech

+ Project Recommended For
  • B.E / B.Tech / M.E / M.Tech

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