A fact-oriented ontological approach to SAO-based function modeling of patents for implementing Function-based Technology Database

Highlights? Function-Oriented Search (FOS) is a new tool for searching patent to find solutions to new problems. ? Function-based Technology Database (FTDB) is a key component of FOS. ? We suggests a fact-oriented ontological approach to implementing an FTDB. ? The proposed approach implements an FTDB for an SAO-based patent retrieval system to support FOS. ? We verified the feasibility of the approach by using it to conduct case studies of patent retrieval. Function-Oriented Search (FOS) has been proposed as a tool for use in searching patent databases to find existing solutions to new problems. To implement FOS effectively, a well-structured Function-based Technology Database (FTDB) is required. An FTDB is a data repository of technology information represented as "function". To implement an FTDB, four features should be addressed: continual data updating, limited area searching, function generalization, and semantics handling. In this paper, we consider these features to suggest a fact-oriented ontological approach to implementing an FTDB by Subject-Action-Object (SAO)-based function modeling of patents. The proposed approach uses fact-oriented ontology modeling of SAO structures extracted from patent documents, and implements an FTDB, which is an SAO-based patent retrieval system to support FOS. We also verify the feasibility of the proposed approach to by using it to conduct case studies of patent retrieval.

[1]  Caterina Rizzi,et al.  Trends of Evolutions and Patent Analysis: An Application in the Household Appliances Field , 2007 .

[2]  Sandra Müller,et al.  Patent-Based Inventor Profiles as a Basis for Human Resource Decisions in Research and Development , 2005 .

[3]  Mike Uschold,et al.  A Framework for Understanding and Classifying Ontology Applications , 1999 .

[4]  Donald Chapin,et al.  Semantics of Business Vocabulary & Business Rules (SBVR) , 2005, Rule Languages for Interoperability.

[5]  Thomas R. Gruber,et al.  Toward principles for the design of ontologies used for knowledge sharing? , 1995, Int. J. Hum. Comput. Stud..

[6]  Darrell L. Mann,et al.  Better technology forecasting using systematic innovation methods , 2003 .

[7]  Gaetano Cascini,et al.  Natural Language Processing of Patents and Technical Documentation , 2004, Document Analysis Systems.

[8]  Michael Uschold,et al.  Knowledge level modelling: concepts and terminology , 1998, The Knowledge Engineering Review.

[9]  Glenn Carroll,et al.  Taggers for Parsers , 1996, Artif. Intell..

[10]  Jeongsoo Lee,et al.  An ontology-based Enterprise Architecture , 2010, Expert Syst. Appl..

[11]  Runhua Tan,et al.  Technology Innovation of Product Using CAI System Based on TRIZ , 2007, IFIP CAI.

[12]  Terry Halpin,et al.  Fact-Oriented Modeling: Past, Present and Future , 2007 .

[13]  G. Altshuller.  Creativity as an exact science : the theory of the solution of inventive problems , 1984 .

[14]  Hugo Liu,et al.  ConceptNet — A Practical Commonsense Reasoning Tool-Kit , 2004 .

[15]  Semyon Savransky,et al.  Engineering of Creativity: Introduction to TRIZ Methodology of Inventive Problem Solving , 2000 .

[16]  Fu ying Zhang,et al.  Research on technical strategy for new product development based on TRIZ evolution theory , 2007 .