Time aware topic based recommender system
نویسندگان
چکیده
منابع مشابه
Evolutionary User Clustering Based on Time-Aware Interest Changes in the Recommender System
The plenty of data on the Internet has created problems for users and has caused confusion in finding the proper information. Also, users' tastes and preferences change over time. Recommender systems can help users find useful information. Due to changing interests, systems must be able to evolve. In order to solve this problem, users are clustered that determine the most desirable users, it pa...
متن کاملA time-aware spatio-textual recommender system
Location-Based Social Networks (LBSNs) allow users to post ratings and reviews and to notify friends of these posts. Several models have been proposed for Point-of-Interest (POI) recommendation that use explicit (i.e. ratings, comments) or implicit (i.e. statistical scores, views, and user influence) information. However the models so far fail to capture sufficiently user preferences as they ch...
متن کاملTOAST: A Topic-Oriented Tag-Based Recommender System
Social Annotation Systems have emerged as a popular application with the advance of Web 2.0 technologies. Tags generated by users using arbitrary words to express their own opinions and perceptions on various resources provide a new intermediate dimension between users and resources, which deemed to convey the user preference information. Using clustering for topic extraction and incorporating ...
متن کاملCOReS: Context-aware, Ontology-based Recommender system for Service recommendation
Advances in telecommunications and information technology have allowed the proliferation of mobile and multifunctional devices and their incorporation more and more into physical objects, making new information and services available. A consequent problem of this new scenario is information overload, i.e. users face vast and distributed information sources, and have difficulty in selecting thos...
متن کاملContext-Aware Recommender System Based on Boolean Matrix Factorisation
In this work we propose and study an approach for collaborative filtering, which is based on Boolean matrix factorisation and exploits additional (context) information about users and items. To avoid similarity loss in case of Boolean representation we use an adjusted type of projection of a target user to the obtained factor space. We have compared the proposed method with SVD-based approach o...
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: Big Data and Information Analytics
سال: 2016
ISSN: 2380-6966
DOI: 10.3934/bdia.2016008