Enhancing Relational Topic Models with Named Entity Induced Links.

Felix Kuhr, Mathis Lichtenberger, Tanya Braun, Ralf Möller

Abstract

Relational topic modeling as an extension to classical topic modeling assumes that documents with some form of link between the documents share topics. The links between documents are given from hyperlinks in web documents, citations in articles, or friendships in social networks. In this work, we consider links between documents induced from named entities: Two documents are linked to each other if both documents have a named entity in common. We present a case study on the performance of relational topic modeling using named-entity induced links between documents. Comparing the prediction accuracy with different sets of named-entity induced links, the results show that additional links between documents can increase the performance of topic models.
OriginalspracheEnglisch
TitelICSC
Seitenumfang4
Erscheinungsdatum2021
Seiten314-317
DOIs
PublikationsstatusVeröffentlicht - 2021

Strategische Forschungsbereiche und Zentren

  • Zentren: Zentrum für Künstliche Intelligenz Lübeck (ZKIL)
  • Querschnittsbereich: Intelligente Systeme

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