2011
DOI: 10.1016/j.eswa.2010.12.114
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Development of a Patent Retrieval and Analysis Platform – A hybrid approach

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Cited by 35 publications
(21 citation statements)
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“…Chen and Chi [3] used the International Patent Classification (IPC) codes to weight terms by their categories. Liu et al [12] proposed to use a hybrid approach using both the text of a patent document and bibliographic data. Their results showed that the combination of the bibliographic data matching and text mining results gives the best recall result.…”
Section: Related Workmentioning
confidence: 99%
“…Chen and Chi [3] used the International Patent Classification (IPC) codes to weight terms by their categories. Liu et al [12] proposed to use a hybrid approach using both the text of a patent document and bibliographic data. Their results showed that the combination of the bibliographic data matching and text mining results gives the best recall result.…”
Section: Related Workmentioning
confidence: 99%
“…Classifying patents into predesigned categories makes patent searching and retrieving much easier, which thus improves the success of technology transfer. Liu et al [23] developed the Patent Retrieval and Analysis Platform, which matches fields of patents and identifies similar patents based on bibliographic pattern discovery and text mining approaches. Shih and Liu [38] proposed a network based classification approach that firstly constructs ontology network and then identifies k-nearest neighbors and patent classes.…”
Section: Related Work 21 Technology Transfermentioning
confidence: 99%
“…A number of such techniques have been used not only to generate an analytic measure of the extent to which different patents are similar in content [48,76] but also to create a visual representation of the relationships inherent in the patent data [38,72,81]. There also can be value in applying a clustering or categorization technique to the data in order to extract significant characteristics about the relationships between the different patents [10,45,74].…”
Section: Related Literaturementioning
confidence: 99%