Evolution of the user's content: An Overview of the state of the art

2013/05/08 by Djallel Bouneffouf, Bouneffouf, Djallel · 2 citations
Computer Science · Mathematics · #Computer science #Content (measure theory) #FOS: Computer and information sciences #I.2 #Image Retrieval and Classification Techniques #Information Retrieval (cs.IR) #Mathematics #Programming language #Recommender Systems and Techniques #Social media #State (computer science) #User-generated content #Video Analysis and Summarization #World Wide Web #cs.IR

paper · pdf · doi:10.48550/arxiv.1305.1787

published in arXiv (Cornell University) (Cornell University)

arxiv created 2013/05/08 · openalex publication_date 2013/05/08 · arxiv updated 2013/05/09 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

The evolution of the user's content still remains a problem for an accurate recommendation.This is why the current research aims to design Recommender Systems (RS) able to continually adapt information that matches the user's interests. This paper aims to explain this problematic point in outlining the proposals that have been made in research with their advantages and disadvantages.

Citations

• Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions

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