PEN recsys: a Personalized News Recommender Systems Framework (DEMO)
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Recommender systems have been increasingly adopted as personalisation services in e-commerce. They facilitate users to locate items which they would be interested in viewing or purchasing. However, most studies have emphasised on the algorithm's performanc ...
Search engines essentially rely on the structure of the graph of hyperlinks. Although accurate for the main trend, this is not effective when some query is ambiguous. Leveraging semantic information by the mean of interest matching allows proposing complem ...
Product review sites such as TripAdvisor, Yelp or Amazon provide a single, non personalized ranking of products. The sparse review data makes personalizing recommendations difficult. Topic Profile Collaborative Filtering exploits review texts to identify u ...
Because of the abundance of news on the web, news recommendation is an important problem. We compare three approaches for personalized news recommendation: collaborative filtering at the level of news items, content-based system recommending items with sim ...
We present the Personalized News (PEN) recommender systems framework, currently in use by a newspaper website to evaluate various algorithms for news recommendations. We briefly describe its system architecture and related components. We show how a researc ...
Social media platforms are created and exploited for various activities carried out individually or collaboratively and relying on different resources and tools. Social media platforms are inherently contextual; the context being defined as a specific acti ...
The proliferation of online news creates a need for filtering interesting articles. Compared to other products, however, recommending news has specific challenges: news preferences are subject to trends, users do not want to see multiple articles with simi ...
Recommender systems have emerged, as an intelligent information filtering tool, to help users effectively identify information items of interest from a set of overwhelming choices and provide personalized services. Most recommendation technologies typicall ...
We introduce WaRR, a tool that records and replays with high fidelity the interaction between users and modern web applications. WaRR consists of two independent components: the WaRR Recorder and the WaRR Replayer. The WaRR Recorder is embedded in a web bro ...
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Social networks today are great source of data which can be used and analyzed in different ways. In our project the main goal is to predict the behavior of the users, more accurately said: we try to predict what will a particular user tweet in the future, ...