Paper Info
Title
SIMPLE: A Strategic Information Mining Platform for Licensing and Execution
Abstract
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 a business from its competition, but also generate significant opportunities in licensing, execution, long term research and innovation. In certain industries, e. g., Pharmaceutical industry, patents lead to multi-billion dollar revenue per year. In this paper, we present a holistic information mining solution, called SIMPLE, which mines large corpus of patents and scientific literature for insights. Unlike much prior work that deals with specific aspects of analytics, SIMPLE is an integrated and end-to-end IP analytics solution which addresses a wide range of challenges in patent analytics such as the data complexity, scale, and nomenclature issues. It encompasses techniques for patent data processing and modeling, analytics algorithms, web interface and web services for analytics service delivery and end-user interaction. We use real-world case studies to demonstrate the effectiveness of SIMPLE.
Year
DOI
Venue
2009
10.1109/ICDMW.2009.36
ICDM Workshops
Keywords
Field
DocType
strategic information mining platform,patents,licensing,web services,end-to-end ip analytics solution,data complexity,patent data processing,end-user interaction,web interface,analytics service delivery,simple,long term research,intellectual properties,holistic information mining solution,data mining,analytics algorithm,research organization,trademarks,core innovation,web service,intellectual property,analytic solution,service delivery,artificial neural networks,data processing,chemicals,data warehouses
Data science,Data warehouse,Data mining,Business analytics,Software analytics,Web analytics,Computer science,Intellectual property,Analytics,Web service,Business intelligence
Conference
ISSN
ISBN
Citations 
2375-9232
978-0-7695-3902-7
7
PageRank 
References 
Authors
0.50
14
13
Name
Order
Citations
PageRank
ying chen113417.07
Scott Spangler216227.58
Jeffrey Kreulen34712.01
Stephen Boyer415110.50
Thomas D. Griffin5509.06
Alfredo Alba6779.87
Amit Behal7293.66
Bin He8110758.10
Linda Kato9355.31
Ana Lelescu10698.50
Cheryl Kieliszewski11222.40
Xian Wu1249536.50
Li Zhang1339220.72