Recommended System for Enhancing Tag Popularity in a Question Answering Community through Splay-net Techniques

Abstract

Collaborative filtering filters information by using the recommendations of peer participants. The long tail problem states users with higher points obtain a high reputation compared to less scored users. In popular community question answering websites, like stack exchange network sites, users with unanswered or ignored questions for a long time get a tumbleweed badge without considering their past history. This deteriorates their further contribution to the website. Mostly new or low-reputation people ask the tumbleweed questions. The popularity of the tags follows a long tail theory. The focus of this research work is to design a recommendation system that prevents participants from tumbleweed badge with tag suggestion method to add new or non-popular tags to the existing popular tag list. The splay-net has a self-balancing graph which brings the recently accessed item to the top of the tree. In this paper, we use the splay-net technique to represent users’ reputation along with their tags.