[PDF] Top 20 Using Topic Models in Content Based News Recommender Systems
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Using Topic Models in Content Based News Recommender Systems
... online news it is possible to read a large amount of different news sources on a large array of topics, but since there are more articles available, finding interesting ones becomes more difficult, as ... See full document
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Implementation of Item and Content based Collaborative Filtering Techniques based on Ratings Average for Recommender Systems
... The content-based filtering approach has its origins in information retrieval and information ...by content-based filtering often indicates textual information, such as news webs and ... See full document
5
Various Methods of Using Content-Based Filtering Algorithm for Recommender Systems
... microblogging systems are produced by hundreds of millions of ...space models for the documents are constructed in the next ...is based on the ranking of the ...microbloggers using hybrid ... See full document
8
Relational clustering models for knowledge discovery and recommender systems
... the content of each ...identified based on the similarity of their visiting items, so the quality of user-based recommendations will hopefully be improved as more relational domain information are ... See full document
186
A Study of Recommender Systems on Social Networks and Content based Web Systems
... the content-based recommendation has its roots in information retrieval and information ...many content-based recommenders focus on recommending items containing textual information such as ... See full document
6
Taxonomy of Recommender Systems for Educational Data Mining (EDM) Techniques: A Systematic Review
... contrast, Content-Based approach depends on the item descriptions to produce recommendations to the user from items that are comparable to those the target user has liked previously and do not depend on ... See full document
6
Towards Understandable Personalized Recommendations: Hybrid Explanations
... a recommender service in the news ...recommend news articles to users and present them on a ...recommended systems, which use ...fully based on recommendation technique (white- ... See full document
26
Capturing knowledge of user preferences with recommender systems
... Regularly asking for a set of interests would be intrusive, imposing an extra work burden on the researchers, and thus result in a reduced uptake of the system. For this reason unobtrusive monitoring of web browsing via ... See full document
155
Personalized News Recommender using Live RSS Feeds
... different News Recommendation System and its functionalities as well as the technologies involved in these ...different topic analysis models and technologies involved to develop these ...these ... See full document
6
Off topic Response Detection for Spontaneous Spoken English Assessment
... assessment systems are becoming increasingly impor- tant to meet the demand for English sec- ond language ...current systems pri- marily assess fluency and pronunciation. However, content assessment ... See full document
10
Content based Recommender System on Customer Reviews using Sentiment Classification Algorithms
... classifier models using these algorithms and evaluate their ...important topic of Sentiment Analysis which has been discussed in this paper is the task of Opinion ...aspect based opinions and ... See full document
6
A market based approach to recommender systems
... user based on the descriptions of previously evaluated ...documents based on users’ binary ratings (“hot” and “cold”) of their interests [Pazzani et ...Usenet news articles by learning the user’s ... See full document
40
Well Argued Recommendation: Adaptive Models Based on Words in Recommender Systems
... Recommendation systems (RS) take advan- tage of products and users information in order to propose items to ...Collaborative, content-based and a few hybrid RS have been developed in the ... See full document
5
Survey of Privacy Policy Based Friend-To-Friend Content Dissemination System
... both content-based and collaborative characteristics. Adding Content-Based Characteristics to Collaborative Models Several hybrid recommender systems, including Fab and ... See full document
8
Towards Serendipity for Content–Based Recommender Systems
... basic models of recommender systems work with two kinds of data: the user- item interactions, such as ratings or buying behaviour; and attributes about the users and items such as users’ profile and ... See full document
8
Recommender Systems and their Security Concerns
... Recommender systems have attracted re- searchers’ attention since the early of 1990s, ...(e.g. news, online multimedia, e- commerce, tourism and social network) to han- dle information overload and ... See full document
33
Non-Personalized Recommender Systems and User-based Collaborative Recommender Systems
... of content-based and collaborative recommender ...are systems that combine multiple recommendation techniques together to achieve a synergy between ...making content based and ... See full document
6
Non-Compensatory Psychological Models for Recommender Systems
... learning models such as latent factor mod- els (Koren, Bell, and Volinsky 2009) have the advantage of scalability, simplicity and ...recommend models based on non- compensatory ... See full document
8
Mitigating Cold Start Problem In A Personalized Recommender System
... constrained-based recommender system a knowledge-base is generally constructed using set of variables and set of constraints ...a recommender knowledge base was constructed with all the ... See full document
5
International Journal of Computer Science and Mobile Computing
... suggestion Systems have been shown as valuable tools to help users deal with services overload and provide appropriate recommendations to ...use recommender systems Over Last ten years there has been ... See full document
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