Recommendation of Scholarly Venues Based on Dynamic User Interests

Hamed Alhoori; Richard Furuta

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arXiv · 1612.05817

Recommendation of Scholarly Venues Based on Dynamic User Interests

Hamed Alhoori·Richard Furuta

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Abstract

The ever-growing number of venues publishing academic work makes it difficult for researchers to identify venues that publish data and research most in line with their scholarly interests. A solution is needed, therefore, whereby researchers can identify information dissemination pathways in order to both access and contribute to an existing body of knowledge. In this study, we present a system to recommend scholarly venues rated in terms of relevance to a given researcher's current scholarly pursuits and interests. We collected our data from an academic social network and modeled researchers' scholarly reading behavior in order to propose a new and adaptive implicit rating technique for venues. We present a way to recommend relevant, specialized scholarly venues using these implicit ratings that can provide quick results, even for new researchers without a publication history and for emerging scholarly venues that do not yet have an impact factor. We performed a large-scale experiment with real data to evaluate the current scholarly recommendation system and showed that our proposed system achieves better results than the baseline. The results provide important up-to-the-minute signals that compared with post-publication usage-based metrics represent a closer reflection of a researcher's interests.

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Hamed Alhoori, Richard Furuta. 2017-12-26. Recommendation of Scholarly Venues Based on Dynamic User Interests. https://arxiv.org/abs/1612.05817

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