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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Hongtao Wu Haobo Yang Jianhong Ma Runhua Tan |
| Copyright Year | 2010 |
| Description | Author affiliation: School of Mechanical Engineering, Hebei University of Technology, Tianjin, China (Runhua Tan) || School of Computer Science & Software, Hebei University of Technology, Tianjin, China (Hongtao Wu; Haobo Yang; Jianhong Ma) |
| Abstract | In concept design, function of system is usually described with a verb and a noun. The verb describes the operation that the system applies on the object which is represented by the noun. The functional verbs are commonly expanded with its synonyms and antonyms, troponyms and hypernyms to use as design stimuli in engineering problems. To reuse previous design resolution, this paper presents a function based patent retrieval approach in which the initial keywords are represented as “verb + noun”, and then the verbs and nouns are automatically expanded into verb set and noun set using Functional Basis and WordNet. The verb set is not only used as design stimuli, but also used as keywords for patent retrieval. The noun set is used to filter retrieval results. The experiment results indicate that the proposed approach can retrieve more functional relevant patents and facilitate cross-domain patent retrieval. |
| Starting Page | 348 |
| Ending Page | 351 |
| File Size | 586373 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424485017 |
| ISSN | 2157362X |
| e-ISBN | 9781424485031 |
| e-ISBN | 9781424485024 |
| DOI | 10.1109/IEEM.2010.5674304 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-12-07 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Computers Patents Technological innovation Design engineering Databases Patent Retrievals Query Expansion Search problems Biology Design Stimuli Functional Keywords Functional Basis |
| Content Type | Text |
| Resource Type | Article |
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