Personalized Ranking Algorithm Based on User Interest Modeling
نویسندگان
چکیده
منابع مشابه
User Multi-interest Modeling Based on Semantic Similar Network in Personalized Information Retrieval
People spend far more time searching information over the Internet than using it, because the desired information is often buried within a long list of searched results. Personalized internet access is a feasible solution to solve this search vs. use dilemma, which helps identify the web documents users truly need. A user’s interests are usually represented by a profile. In this research, an im...
متن کاملModeling and broadening temporal user interest in personalized news recommendation
User profiling is an important step for solving the problem of personalized news recommendation. Traditional user profiling techniques often construct profiles of users based on static historical data accessed by users. However, due to the frequent updating of news repository, it is possible that a user’s finegrained reading preference would evolve over time while his/her long-term interest rem...
متن کاملWeb pages ranking algorithm based on reinforcement learning and user feedback
The main challenge of a search engine is ranking web documents to provide the best response to a user`s query. Despite the huge number of the extracted results for user`s query, only a small number of the first results are examined by users; therefore, the insertion of the related results in the first ranks is of great importance. In this paper, a ranking algorithm based on the reinforcement le...
متن کاملAn Improved Collaborative Filtering Algorithm Based on User Interest
With the development of personalized services, collaborative filtering techniques have been successfully applied to the network recommendation system. But sparse data seriously affect the performance of collaborative filtering algorithms. To alleviate the impact of data sparseness, using user interest information, an improved user-based clustering Collaborative Filtering (CF) algorithm is propo...
متن کاملPersonalized Ranking of Search Results with Implicitly Learned User Interest Hierarchies
Web search engines are usually designed to serve all users, without considering the interests of individual users. Personalized web search incorporates an individual user's interests when deciding relevant results to return. We propose to learn a user profile, called a user interest hierarchy (UIH), from web pages that are of interest to the user. The user’s interest in web pages will be determ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: DEStech Transactions on Computer Science and Engineering
سال: 2017
ISSN: 2475-8841
DOI: 10.12783/dtcse/cst2017/12567