Enhancing Content Search and Correlation

THE PROBLEM

To meet evolving needs in the education sector, one of the world’s leading academic publishers sought to improve its offering for students and teachers by delivering smarter, more targeted search results. Using AI-powered text analysis, the publisher aimed to provide users with more relevant and meaningful content recommendations drawn from its extensive library of publications.

THE SOLUTION

By leveraging expert.ai’s natural language understanding capabilities that understand and analyze the meaning of text, the publisher implemented an AI-driven solution that dynamically recommends related resources, such as journals, datasets and supplementary materials across other SAGE platforms, to users.
When a user browses a book chapter, compares reference entries or watches a video, a tab appears on the right side of the browser.

Clicking the tab reveals a curated list of articles, case studies and multimedia resources directly related to the content being viewed, based on the publisher’s proprietary taxonomy of terms and concepts.

This approach enhances the content search engine, improving findability across disciplines and content types through intelligent semantic linking.

The taxonomy powering this AI solution includes 63,000 concepts built on 50 years of publishing experience in journals, books and professional publications, as well as the semantic analysis of more than 1.5 million articles, 250,000+ book chapters and dozens of specialized dictionaries and lexicons.

BENEFITS

• Enhanced content retrieval with more than 12 million recommendations generated each month
• Improved search productivity through more accurate and relevant results
• Increased user satisfaction and loyalty