22 June 2021
Project MUSE is partnering with UNSILO, part of Cactus Communications that develops artificial intelligence(AI)-powered solutions for publishers, to implement robust new AI-driven content recommendations throughout its collection of books and journals in the humanities and social sciences. UNSILO recently completed the initial indexing of the Project MUSE content collection and enhanced related content recommendations appear throughout the platform.
The UNSILO Recommender API automatically identifies links to relevant content from the MUSE content corpus for any selected document (book chapter or journal article). The indexing is updated every 24 hours as new content is added to MUSE. Links are delivered to the platform in real time, enriching the user experience and providing relevance-ranked discovery that augments the learning experience. Over 250 concepts are extracted from every document, and then matched by rank with related material.
Wendy Queen, Director of Project MUSE, commented, “We’re excited to be working with an innovative, industry-leading partner to bring this rich new discovery experience to researchers on the MUSE platform. UNSILO’s leading-edge AI technology will help unearth the most relevant, useful, and timely connections across our deeply interdisciplinary body of content, increasing the efficiency and impact of research with Project MUSE. The continually-refreshed recommendations generated by the UNSILO indexing will increase the visibility of both archival and newly-published material on MUSE, driving usage and helping to fulfill our mission of broad dissemination of essential humanities and social science scholarship.”
Nishchay Shah, Chief Technology Officer at Cactus Communications, commented: “We are very proud to be partnering with Project MUSE, one of the most respected names in academic publishing. We feel that UNSILO’s concept extraction tools are uniquely suited to the vast wealth of MUSE content, including humanities, social sciences, the arts, philosophy, and religion. UNSILO is content agnostic: it is based on the corpus supplied, which in MUSE’s case is one of the most extensive full-text scholarly content repositories available. We believe that MUSE users will find many new and valuable content links from the corpus. At UNSILO, we look forward and to learning more about MUSE users and how they make use of the new tools for discovery provided.”