Exploring Applying MeSH Ontology for Biomedical Patent Citation Recommendation

Open Access
Wan, Yinan
Graduate Program:
Information Sciences and Technology
Master of Science
Document Type:
Master Thesis
Date of Defense:
March 19, 2014
Committee Members:
  • John Yen, Thesis Advisor
  • Patent
  • citation
  • recommendation
  • MeSH
  • ontology
Patent citation recommendation, as one of the prior-art search, is critical in the patent examination. Other than paper citation, the content scope is important for patent recommendation. A thorough prior-art search for patent will both help applicants to properly scale the proposal and USPTO examiners to evaluate the originality of the invention and accept how the invention can be distinguished from the prior art. Integrating technical terminology will help determine the scale of technical paper in a more precise way. MeSH ontology is a controlled vocabulary with hierarchical semantics developed by the National Library of Medicine to index the biomedical articles. Here we developed a method to assign and evaluate the MeSH semantic similarity for the patent document. The experimental results generate a three-step “best measure set” to integrate the MeSH descriptor semantic similarity into the document similarity measure. We also further improved the result by using the Medical Text Indexer (MTI) to assign the MeSH descriptors. We used 28438 Biotechnology patents as patent pool. Results evaluated by the average recall rate suggest though the MeSH semantic similarity measure may not exceed some of the sophisticated content-based measure, its outperforming the basic cosine similarity measure suggests its potential to act as one feature to be integrate into other complex search engine.