IRSep 24, 2020

ArXivDigest: A Living Lab for Personalized Scientific Literature Recommendation

arXiv:2009.11576v11 citations
Originality Synthesis-oriented
AI Analysis

This addresses the problem of limited evaluation resources for researchers in explainable scientific literature recommendation, though it is incremental as it builds on existing recommendation concepts.

The authors tackled the lack of open evaluation resources for personalized scientific literature recommendations by introducing arXivDigest, an online service that provides personalized arXiv recommendations to users and serves as a living lab for researchers working on explainable recommendations.

Providing personalized recommendations that are also accompanied by explanations as to why an item is recommended is a research area of growing importance. At the same time, progress is limited by the availability of open evaluation resources. In this work, we address the task of scientific literature recommendation. We present arXivDigest, which is an online service providing personalized arXiv recommendations to end users and operates as a living lab for researchers wishing to work on explainable scientific literature recommendations.

Code Implementations1 repo
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The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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