A System for Probabilistic Linking of Thesauri and Classification Systems
This work addresses the challenge of integrating different knowledge organization systems for users in domains like information retrieval or library science, but it appears incremental as it builds on an existing model without major breakthroughs.
The paper tackles the problem of linking concepts in a thesaurus to classes in a classification system by developing a system that uses the Polylingual Labeled Topic Model (PLL-TM) to create probabilistic semantic links from document text, descriptors, and classes, and presents these links in an interactive visualization for users.
This paper presents a system which creates and visualizes probabilistic semantic links between concepts in a thesaurus and classes in a classification system. For creating the links, we build on the Polylingual Labeled Topic Model (PLL-TM). PLL-TM identifies probable thesaurus descriptors for each class in the classification system by using information from the natural language text of documents, their assigned thesaurus descriptors and their designated classes. The links are then presented to users of the system in an interactive visualization, providing them with an automatically generated overview of the relations between the thesaurus and the classification system.