Enhanced recommendation system in community–question-answering websites using splay-tree methodology

Abstract

In community-driven ranking systems participants with superior scores acquire strong reputation than low scored participants. The community-question-aswering websites, like stackexchange network, participants with unreciprocated or unnoticed questions for a long time get a badge called tumbleweed without taking into account of their earlier period performance. The user-driven question and answering website considers this reward as a consolation prize and discourages them instead of encouraging. Mostly, the users who ask unnoticed questions are either a new or less scored participants. The center of attention of this research work is to propose a recommendation system that prevents unnoticed questions from the participants who are about to receive a tumbleweed badge. A splay-tree is a tree with a self-balancing ability which brings the newly accessed node to the apex of the tree. In this paper, the splay-tree correspond to participants’ ranks and the highlight of the work is to raise average or beneath average scorer to apex without disturbing existing toppers.