Recommender Systems using Pennant Diagrams in Digital Libraries

TL;DR

This paper introduces a recommender system for digital libraries that uses Pennant diagrams based on co-citation and co-occurrence analysis to visually represent relatedness between documents, enhancing user understanding.

Contribution

The paper presents a novel application of Pennant diagrams in digital library recommender systems, integrating co-citation and co-occurrence analysis for improved visualization.

Findings

Demonstrated pennant diagrams in sowiport digital library

Evaluated the utility of pennants for search enhancement

Discussed visualization and practical implementation issues

Abstract

In digital libraries recommendations can be valuable for researchers, e.g. recommending related literature to a given context. Typically, in a scientific context the simple presentation of related content is not sufficient. Often the users demand a more detailed view on the connection of a document and its specific recommendations. The aim of pennants introduced by Howard White (2007) is to provide the user with a graph showing the relatedness / distance between a given document and related documents. Co-citation but also co-occurrence analysis are established methods for finding related documents to a seed. A seed could be for instance an author, a keyword, or a publication. In this paper we introduce a recommender system in the digital library sowiport using pennant diagrams which can be created from co-citation and/or co-occurrence analysis. The presentation at the NKOS workshop will present demos of pennants in sowiport and will elaborate on practical questions in visualizing pennants and evaluating the utility of pennants for search.