Text mining techniques for patent analysis

By Yuen-Hsien Tseng, Chi-Jen Lin, Yu-I Lin. Information Processing & Management, 2007

807 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

An approach to discovering new technology opportunities: Keyword-based patent map approach (2009, background): “In fact, there have been several attempts to apply text mining to developing patent maps (Tseng et al., 2007a, b; Yoon and Park, 2004), but previous studies have focused mainly on the development process.”
Data mining techniques and applications — A decade review (2017, background): “Text mining can be classified as document processing, document summarization, indexing, topic clustering and mapping [18].”
A literature review on the state-of-the-art in patent analysis (2014, background): “Therefore, the task of parsing the unstructured data requires extraction tools having capabilities of segmentation of textual data into meaningful structures [10].”
Current research trends and prospects among the various materials and designs used in lithium-based batteries (2013, background): “ments, most patents do follow this specific structure [17].”
Explaining Data-Driven Document Classifications (2014, background): “…(Pang and Lee 2008), spam identification (Attenberg et al. 2009), web page classifi- cation (Qi and Davison 2009), legal document classification(Tseng et al. 2007), medical document triage (Wallace et al. 2010), and document classification for topical web search (Pant and Srini- vasan…”