Name
Abstract | ||
|---|---|---|
Patent documents contain important technical knowledge and research results. They have high quality information to inspire designers in product development. However, they are lengthy and have much noisy results such that it takes a lot of human efforts for analysis. And due to the fact that hidden and unanticipated information plays a dominant role for TRIZ user, it is difficult to discern manually, thus, patent analysis has long been considered useful in product innovative process. Automatic tools for assisting innovators and patent engineers in obtaining useful information from patent documents are in great demand. In TRIZ theory, a product design problem can be considered as one or several Contradictions and Inventive Principles. Text mining could be used to analyze these textual documents and extract useful information from large amount documents quickly and automatically. In this paper, a computer-aided approach for extracting useful information from patent documents according to TRIZ Inventive Principles is proposed. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-0-387-75456-7_9 | International Federation for Information Processing |
Keywords | Field | DocType |
patent analysis,TRIZ,inventive principles,text mining | Data science,Text mining,TRIZ,Computer science,Product design,Patent analysis,New product development | Conference |
Volume | Issue | ISSN |
250 | null | 1571-5736 |
Citations | PageRank | References |
4 | 0.44 | 11 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yanhong Liang | 1 | 5 | 1.18 |
| Runhua Tan | 2 | 13 | 13.78 |