DLIRMay 1, 2017

Towards effective research recommender systems for repositories

arXiv:1705.00578v121 citations
Originality Synthesis-oriented
AI Analysis

This work tackles the problem of improving user experience and functionality in research repositories for researchers and users, but it is incremental as it builds on existing recommender system concepts.

The paper addresses the challenge of enhancing research repositories with recommender systems by presenting the CORE Recommender, which has been redeveloped and deployed across multiple repositories and journals, though no concrete performance numbers are provided.

In this paper, we argue why and how the integration of recommender systems for research can enhance the functionality and user experience in repositories. We present the latest technical innovations in the CORE Recommender, which provides research article recommendations across the global network of repositories and journals. The CORE Recommender has been recently redeveloped and released into production in the CORE system and has also been deployed in several third-party repositories. We explain the design choices of this unique system and the evaluation processes we have in place to continue raising the quality of the provided recommendations. By drawing on our experience, we discuss the main challenges in offering a state-of-the-art recommender solution for repositories. We highlight two of the key limitations of the current repository infrastructure with respect to developing research recommender systems: 1) the lack of a standardised protocol and capabilities for exposing anonymised user-interaction logs, which represent critically important input data for recommender systems based on collaborative filtering and 2) the lack of a voluntary global sign-on capability in repositories, which would enable the creation of personalised recommendation and notification solutions based on past user interactions.

Foundations

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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