Building an Internet-Based Knowledge Ontology for Trademark Protection

Charles Trappey*, Ai-Che Chang, Amy J. C. Trappey

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Global online sales for products, where many are substantially identical or deceptively similar, are the cause of a growing number of trademark (TM) infringement lawsuits. This research proposes an intelligent trademark legal precedent recommendation system to assist trademark owners to find relevant past cases, laws, and judgments to form legal arguments to defend against infringement. Judicial precedent and applicable laws from the USA are used to construct an ontology of trademark litigation knowledge. The ontology is used to analyze potential infringement cases with similar laws and precedents used to resolve previous legal disputes. The analysis provides a basis for proceeding with legal action necessary to protect a company's brand equity when arguing potential trademark infringement. Using the Python programming language, the precedent-based recommendation system provides a means for continuously updating trademark case data and assists TM owners to quickly identify similar cases to support infringement allegations.

Original languageEnglish
Pages (from-to)123-144
Number of pages22
JournalJournal of Global Information Management
Volume29
Issue number1
DOIs
StatePublished - Jan 2021

Keywords

  • E-Discovery
  • Infringement Analysis
  • Ontology
  • Recommendation System
  • Text Mining
  • Trademark Protection
  • DESIGN SCIENCE
  • BRAND

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