|کد مقاله||کد نشریه||سال انتشار||مقاله انگلیسی||ترجمه فارسی||نسخه تمام متن|
|4950290||1364283||2018||11 صفحه PDF||ندارد||دانلود رایگان|
â¢A social network-based query personalization algorithm is presented.â¢The algorithm considers influencers from the userâs social network.â¢Both the userâs and the influencersâ preferences are used for personalizing queries.â¢The algorithm is evaluated both performance- and quality-wise.
Query personalization has emerged as a means to handle the issue of information volume growth, aiming to tailor query answer results to match the goals and interests of each user. Query personalization dynamically enhances queries, based on information regarding user preferences or other contextual information; typically enhancements relate to incorporation of conditions that filter out results that are deemed of low value to the user and/or ordering results so that data of high value are presented first. In the domain of personalization, social network information can prove valuable; usersâ social networks profiles, including their interests, influence from social friends, etc. can be exploited to personalize queries. In this paper, we present a query personalization algorithm, which employs collaborative filtering techniques and takes into account influence factors between social network users, leading to personalized results that are better-targeted to the user.
Journal: Future Generation Computer Systems - Volume 78, Part 1, January 2018, Pages 440-450