Generative Models for Item Adoptions

As the increase of social media, number of internet user has increase in large number. This enhance e-shoping, so researchers get new field for mining that is product prediction. Web item prediction has been widely used to reduce the user confusion problem. This paper has focus on product prediction where new combination of Jaccard base social network utilization is done with probabilistic function LDA. Results shows that with the increase in features for Jaccard coefficient prediction accuracy has increase. Although research in this field is just a start, it is required to develop an adaptive algorithm as per social network.

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