Personalised recommendation system for ranking in question-answering websites with splay tree by avoiding tumbleweed badge

Abstract

An efficient and effective way to construct trust relationship among peer users in electronic learning environment is ranking. User-driven ranking systems are based only on the feedback or ratings provided by the users. Users with higher points obtain high reputation compared to less scored users. In popular 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. The question-answering website community considers this award as a consolation prize and discourages the awardees instead of encouraging them. Most of the people who ask Tumbleweed questions are new or low-reputation users. The focus of this research work is to design a recommendation system that prevent tumbleweed questions from the users who are about to receive a tumbleweed badge. A splay tree is a binary search tree with a self-balancing skill which brings the recently accessed item to the top of the tree. In this paper, the splay tree represents users' ranks with methods to avoid tumbleweed badge. The spotlight of the work is to bring up average or below average scorer to top without affecting existing topers.