Claim Mining: Legal-Based Technology Analysis Using the Semantics of Patent Claims
|Other Titles:||Claim Mining: Patentrecht-basierte Technologieanalyse unter Anwendung semantischer Analyse von Patentansprüchen||Authors:||Wittfoth, Sven||Supervisor:||Möhrle, Martin G.||1. Expert:||Kotzab, Herbert||2. Expert:||Walter, Lothar||Abstract:||
Entrepreneurial success within a technology field often derives either from trade secrets or exclusive rights. Consequently, intellectual properties in terms of patents can be seen as a company’s intangible assets that can prohibit competitors from manufacturing, using, selling, offering for sale, or importing patented products or processes. Many approaches have been elaborated for the analysis of patents to gain strategic insights. Examples are provided by data-driven technology analyses to adjust R&D expenses, plan M&A activities, or create technology roadmaps. However, recent approaches lack both sufficient semantic analysis of patent claims and the provision of scientific-based strategic insights. From a legal perspective, patent claims are the most crucial element within patents because exclusive rights derive from patent claims and their features based on patent law. In particular, recent approaches apply the same natural language processes (NLPs) on title, abstract, description, and claims, even though the legal part of patent claims strongly differs in its wording and syntactic structure. Former approaches neglected claim-specific information, such as dependency level in terms of independent, dependent, and multiple dependent claims, as well as the claim categories (e.g. product, manufacturing process claim) defined in the preamble of each claim. This cumulative dissertation aims to overcome these drawbacks by introducing a claim mining framework. Consequently, untapped opportunities for several application fields within technology analysis are explored. Furthermore, this framework provides claim-specific NLPs in terms of both a claim pre-processing that tags claim’s dependency levels and categories and a claim processing that applies claim-specific stopword filters and term weightings to implement similarity measurements. In doing so, application fields within technology analyses, such as information retrieval, technology forecasting, strategic technology planning, patent quality and value identification, and competitor analysis are addressed. Finally, theoretical and managerial implications are drawn to demonstrate the usefulness of this work.
|Keywords:||Semantic patent analysis; Innovation dynamics; Technology intelligence; Text mining; Strategic decision making||Issue Date:||8-Sep-2020||Type:||Dissertation||DOI:||10.26092/elib/322||URN:||urn:nbn:de:gbv:46-elib45258||Institution:||Universität Bremen||Faculty:||FB07 Wirtschaftswissenschaften|
|Appears in Collections:||Dissertationen|
checked on Jan 27, 2021
checked on Jan 27, 2021
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