RECOMMENDATION ENGINE

摘要

A system and method that computes a probability score indicating the probability that the user would prefer a particular item. The system prompts the user to review a particular item and subsequently prompts the user to reveal whether he liked the item or otherwise. The search engine also extracts the other review scores which were generated by the reviewers in respect of the item name specified by the user. Subsequently, the search engine also elicits the other review scores, preferably along with the corresponding reviews, in respect of the items reviewed by the reviewers who also reviewed the item specified by the user. The system further calculates probability scores indicating the probability that a user would prefer any of the items related to the reviews generated by the reviewers who also reviewed the item specified by the user. Accordingly the system generates recommendations based on the probability scores.

主权项

1. A computer implemented system for recommending at least one item to a user based at least partially on items previously reviewed by said user, the system comprising:
a prompter that prompts said user to review at least one item, and prompts said user to assign a user score to the reviewed item based on a pre-determined user scoring criteria; a search engine that searches for and elicits a first group of at least one review score, the at least one review score generated by a respective at least one reviewer, wherein said first group of at least one review score corresponds with the item reviewed by said user, said search engine searching for and eliciting a second group of at least one review score, wherein said second group of at least one review score is generated by at least one reviewer who generated said first group of at least one review score; a processor that calculates weight scores based on a combination of said user score and each of said at least one review score available in said first group, said processor further linking the calculated weight scores with corresponding reviewers, said processor calculating an average weight corresponding to each said at least one reviewer based on respective weight scores, said processor calculating probability scores for each of said second group of at least one review score, said probability scores indicative of a probability of said user preferring each of the items corresponding to said at least one review score present in said second group, said probability scores being functions of respective at least one review score present in said second group and average weights of respective at least one reviewer; a recommendation engine that selects a review having a highest probability score and the item thereof from said second group, said recommendation engine recommending the selected item to said user; and a storage mechanism that stores information corresponding to at least one item previously recommended to said user, wherein said prompter selectively prompts said user to review at least one of the previously recommended items.