Title :
Prospective Client Driven Technology Recommendation
Author :
He, Qi ; Spangler, W. Scott ; He, Bin ; Chen, Ying ; Kato, Linda
Author_Institution :
Almaden Res. Center, IBM, San Jose, CA, USA
Abstract :
Helping locate the patents of the right technologies for licensing to prospective clients is more than one billion USD business annually to IBM. However, searching for right technologies from multiple massive data sources for a value presentation to customers is a typical human labor intensive task in the past. In this paper, we design a prospective client driven technology recommendation system to enable the automatic search of technologies for patent licensing. The idea has been to make use of knowledges from the large-scale encyclopedia Wikipedia in conjunction with 11 millions patent documents to develop an online technology recommendation system for prospective clients of IBM. The live system demands not only the fast response time but also a set of highly relevant patent documents which are technically interesting to a query prospective client.
Keywords :
Web sites; patents; query processing; recommender systems; IBM; Wikipedia; human labor intensive task; large-scale encyclopedia; massive data sources; online technology recommendation system; patent documents; patent licensing; prospective client driven technology recommendation; query prospective client; value presentation; Companies; Electronic publishing; Encyclopedias; Internet; Patents; Training data; IP licensing; SPAR; literature; patent; prospective; recom- mendation; technology;
Conference_Titel :
SRII Global Conference (SRII), 2012 Annual
Conference_Location :
San Jose, CA
Print_ISBN :
978-1-4673-2318-5
Electronic_ISBN :
2166-0778
DOI :
10.1109/SRII.2012.23
