Technology opportunity discovery based on patent analysis: a hybrid approach of subject-action-object and generative topographic mapping

An incomplete understanding of the technical details in a firm's technology selection can lead to a failure in the process of the technology opportunity discovery (TOD) and cause a series of R&D problems. This study proposes an approach for the automated TOD by combining the subject-section...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Technology analysis & strategic management Jg. 36; H. 9; S. 2070 - 2083
Hauptverfasser: Wang, Jinfeng, Ding, Zhaoye, Liu, Zhenfeng, Feng, Lijie
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Abingdon Routledge 01.09.2024
Taylor & Francis Ltd
Schlagworte:
ISSN:0953-7325, 1465-3990
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:An incomplete understanding of the technical details in a firm's technology selection can lead to a failure in the process of the technology opportunity discovery (TOD) and cause a series of R&D problems. This study proposes an approach for the automated TOD by combining the subject-section-object (SAO) and the generative topographic mapping (GTM), which concentrates on the role of the semantic information in TOD process. First, the semantic information of the technology components in a target field is extracted and the topics of different semantic structures are defined. Second, the GTM-based patent map is established to discover technology opportunities based on a vector matrix composed of patents and topics. Finally, the degree of semantic similarity is applied to measure the technology novelty and to identify promising technology opportunities. The case of the coal-bed methane extraction technology demonstrates that the automated approach based on the semantic information can help understand the concrete details of technology opportunities and improve the accuracy of TOD.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0953-7325
1465-3990
DOI:10.1080/09537325.2022.2126306