SoTaRePo: Society-Tag Relationship Protocol based architecture for UIP construction

Abstract

As with the advancement of web services, there has been a rapid proliferation in web size and number of web users, where, each user holds a different viewpoint towards the same information. This, in turn, has become a big challenge for the web search platforms to interpret the preferences of the users and provide the desired information to them. The most suitable solution to the problem of search platforms is personalization of web search. A personalization system is a kind of expert and intelligent system which can automatically learn about the preferences of a user so that the system can provide the search results as per their relevance to a user. The process of acquiring knowledge about user’s preferences by a personalization system is known as User Interest Profile (UIP). In the field of search personalization, it can also not be denied that only an efficient and complete UIP can lead to an effective and high performing web search personalization methodology design. But most of the studies conducted for web search personalization have only focused on UIP modeling without any thought about the quality of UIP. Rather limited attention has been paid to sparsity issue of UIP modeling. In this paper, we propose a novel protocol based architecture model to create an efficient UIP by exploiting direct and indirect interest of a user. Direct interest aims at mining user’s preferences from his own activities on a social information platform. The explicitly defined society and real-world activity relationships of a user on a social platform are used to predict his indirect interest as UIP constructed solely on the basis of direct interest is sparse and ineffective. In order to unearth user’s activity relationships the concept of semantic relatedness, computed using Word2vec model, has been used. Moreover, different trust levels in society relationships have also been incorporated into the proposed model to facilitate the prediction of user’s indirect interest. A series of experiments have been conducted on a del.icio.us dataset to evaluate the effectiveness of the proposed model. The results show that the model has outperformed each and every baseline in relation to complete and efficient UIP construction.