SIMPLE: Interactive Analytics on Patent Data

Intellectual Properties (IP), such as patents and trademarks, are one of the most critical assets in today’s enterprises and research organizations. They represent the core innovation and differentiators of an organization. When leveraged effectively, they not only protect freedom of action, but also generate significant opportunities in licensing, execution, long term research and innovation. In this paper, we expand upon a previous paper describing a solution called SIMPLE, which mines large corpus of patents and scientific literature for insights. In this paper we focus on the interactive analytics aspects of SIMPLE, which allow the analyst to explore large unstructured information collections containing mixed information in a dynamic way. We use real-world case studies to demonstrate the effectiveness of interactive analytics in SIMPLE.

[1]  C. M. Sperberg-McQueen,et al.  Extensible markup language , 1997 .

[2]  W. Scott Spangler,et al.  Generating and Browsing Multiple Taxonomies Over a Document Collection , 2003, J. Manag. Inf. Syst..

[3]  Thomas Klose,et al.  Enhancing patent landscape analysis with visualization output , 2010 .

[4]  William H. Press,et al.  Numerical Recipes in C, 2nd Edition , 1992 .

[5]  W. Scott Spangler,et al.  COA: finding novel patents through text analysis , 2009, KDD.

[6]  Inderjit S. Dhillon,et al.  Visualizing Class Structure of Multidimensional Data , 1998 .

[7]  Makoto Iwayama,et al.  Overview of the Patent Mining Task at the NTCIR-7 Workshop , 2008, NTCIR.

[8]  Houfeng Wang,et al.  Bootstrapping both Product Properties and Opinion Words from Chinese Reviews with Cross-Training , 2007 .

[9]  Jon Rigelsford.  Patent Strategy for Researchers and Research Managers , 2002 .

[10]  Haim Levkowitz,et al.  Least Square Projection: A Fast High-Precision Multidimensional Projection Technique and Its Application to Document Mapping , 2008, IEEE Transactions on Visualization and Computer Graphics.

[11]  W. Scott Spangler,et al.  Multi-taxonomy: Determining Perceived Brand Characteristics from Web Data , 2008, 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology.

[12]  W. Scott Spangler,et al.  Intelligent Web Services Selection based on AHP and Wiki , 2007, IEEE/WIC/ACM International Conference on Web Intelligence (WI'07).

[13]  Kas Kasravi,et al.  Patent Mining - Discover y of Business Value from Patent Repositor ies , 2007, 2007 40th Annual Hawaii International Conference on System Sciences (HICSS'07).

[14]  Rajeev Motwani,et al.  The PageRank Citation Ranking : Bringing Order to the Web , 1999, WWW 1999.

[15]  Christiane Fellbaum,et al.  Book Reviews: WordNet: An Electronic Lexical Database , 1999, CL.

[16]  Scott Spangler,et al.  Mining the Talk: Unlocking the Business Value in Unstructured Information (IBM Press) , 2007 .

[17]  Ellis Horowitz,et al.  Extracting problem solved concepts from patent documents , 2009, PaIR@CIKM.

[18]  W. Scott Spangler,et al.  SIMPLE: A Strategic Information Mining Platform for Licensing and Execution , 2009, 2009 IEEE International Conference on Data Mining Workshops.

[19]  C. M. Sperberg-McQueen,et al.  Extensible Markup Language (XML) , 1997, World Wide Web J..

[20]  Jun Rao,et al.  Dynamic faceted search for discovery-driven analysis , 2008, CIKM '08.

[21]  W. Scott Spangler,et al.  Machines in the conversation: Detecting themes and trends in informal communication streams , 2006, IBM Syst. J..