Main Reference PaperGSLDA- LDA-based group spamming detection in product reviews, Applied Intelligence, 2018 [Java/Python/R]
  • In product based recommendations, a group of fraudsters writing hype-reviews or defaming-reviews for one or more target products. It becomes the review spamming. To detect the review spam, this work proposed a named GSLDA. The proposed LDA model detects the spams by boosting the number of suspicious reviewers according to review time burstiness and rating score homogeneity.

+ Description
  • In product based recommendations, a group of fraudsters writing hype-reviews or defaming-reviews for one or more target products. It becomes the review spamming. To detect the review spam, this work proposed a named GSLDA. The proposed LDA model detects the spams by boosting the number of suspicious reviewers according to review time burstiness and rating score homogeneity.

  • To improve the clustering accuracy

  • To detect the fake reviews

+ Aim & Objectives
  • To improve the clustering accuracy

  • To detect the fake reviews

  • A proposed LDA model is combined with other review spamming detection techniques to improve the detection of review spam further.

+ Contribution
  • A proposed LDA model is combined with other review spamming detection techniques to improve the detection of review spam further.

  • OS: Ubuntu 12.04 LTS 64bit

  • Language: Java/Python/R

+ Software Tools & Technologies
  • OS: Ubuntu 12.04 LTS 64bit

  • Language: Java/Python/R

  • M.E / M.Tech/ MS / Ph.D.- Customized according to the client requirements.

+ Project Recommended For
  • M.E / M.Tech/ MS / Ph.D.- Customized according to the client requirements.

  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

+ Order To Delivery
  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

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