Patents by Inventor Mostafa SALEHI

Mostafa SALEHI has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Method for detecting spam reviews written on websites
    Patent number: 10467664
    Abstract: A method for detecting if an online review written by a user on a website of a telecommunications network is a spam, using at least one previously-labeled review, a review dataset comprising at least one review to be analyzed, and a spam feature list listing different features of spam reviews, method wherein: a) a weight is computed for each spam feature of the spam feature list, corresponding to the importance of the spam feature in the detection of spam reviews, and based at least on the features of said at least one previously-labeled review, and b) a probability of being a spam for a review under analysis in the review dataset is computed by using at least the weights of the spam features computed at step a) and a comparison between the features of said review under analysis and the ones of at least one review previously-labeled as spam.
    Type: Grant
    Filed: January 30, 2017
    Date of Patent: November 5, 2019
    Assignee: INSTITUT MINES-TELECOM
    Inventors: Mostafa Salehi, Saeedreza Shehnepoor, Reza Farahbakhsh, Noel Crespi
  • METHOD FOR DETECTING SPAM REVIEWS WRITTEN ON WEBSITES
    Publication number: 20170221111
    Abstract: A method for detecting if an online review written by a user on a website of a telecommunications network is a spam, using at least one previously-labeled review, a review dataset comprising at least one review to be analyzed, and a spam feature list listing different features of spam reviews, method wherein: a) a weight is computed for each spam feature of the spam feature list, corresponding to the importance of the spam feature in the detection of spam reviews, and based at least on the features of said at least one previously-labeled review, and b) a probability of being a spam for a review under analysis in the review dataset is computed by using at least the weights of the spam features computed at step a) and a comparison between the features of said review under analysis and the ones of at least one review previously-labeled as spam.
    Type: Application
    Filed: January 30, 2017
    Publication date: August 3, 2017
    Applicant: INSTITUT MINES-TELECOM
    Inventors: Mostafa SALEHI, Saeedreza SHEHNEPOOR, Reza FARAHBAKHSH, Noel CRESPI