Improved Technology Similarity Measurement in the Medical Field based on Subject-Action-Object Semantic Structure: A Case Study of Alzheimer's Disease
Autor: | Rongrong Li, Yuqin Liu, Shuo Zhang, Xuefeng Wang |
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Rok vydání: | 2023 |
Předmět: |
Structure (mathematical logic)
Vocabulary Computer science business.industry Strategy and Management media_common.quotation_subject Unified Medical Language System Object (computer science) computer.software_genre Semantic network Feature (linguistics) Similarity (psychology) Artificial intelligence Electrical and Electronic Engineering International Patent Classification business computer Natural language processing media_common |
Zdroj: | IEEE Transactions on Engineering Management. 70:280-293 |
ISSN: | 1558-0040 0018-9391 |
DOI: | 10.1109/tem.2020.3047370 |
Popis: | This article presents an improved method of measuring technology similarity by introducing a subject-action-object (SAO) analysis that uses the feature weights of semantic structure and professional vocabulary to measure technology similarity in the medical field. First, the SAO semantic structures are extracted and cleaned; then the structures related to technology are identified using a semantic network of the unified medical language system (UMLS). Second, the similarity between the SAO semantic structures is evaluated using semantic information from the Metathesaurus of the UMLS. Third, the feature weights of the SAO semantic structure are introduced to represent the importance of the patentees’ technology features. Finally, using the SAO and weight information, each patentee's vector is constructed to measure the technology complementarity between different patentees. This study conducts empirical research on Alzheimer's disease. The results indicate that the propose method for measuring technology similarity enables finer distinctions with more reliable outcomes than the traditional methods that are based on keywords and international patent classification. |
Databáze: | OpenAIRE |
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