Algorithm of Repeated Results Re-ranking based on Polysemy
Pengwei Guo, Bin Zhang, Da-ming Sun · Advances in computer science research · 2015
In order to make search results better fit users' current search interest, this paper proposes an algorithm of repeated results re-ranking using a model of polysemy.The algorithm considers the characteristics of the keywords to improve the rank of repeated results.Based on the analysis of polysemy of the keywords, we propose a polysemous model of concept lattice, then we combine with the user interest model to change the rank of repeated results in a search session.The method of this paper considers the impact of polysemy of keywords which may improve the ranking.The experimental results show that the process based on the polysemy of the keyword can reduce the length of the search session, especially when the keywords have multiple meanings.