Prospective Client Driven Technology Recommendation

Qi He, W. Spangler, Bin He, Ying Chen, Linda Kato
{"title":"Prospective Client Driven Technology Recommendation","authors":"Qi He, W. Spangler, Bin He, Ying Chen, Linda Kato","doi":"10.1109/SRII.2012.23","DOIUrl":null,"url":null,"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.","PeriodicalId":110778,"journal":{"name":"2012 Annual SRII Global Conference","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Annual SRII Global Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SRII.2012.23","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

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.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
潜在客户驱动的技术推荐
帮助找到合适的技术专利并授权给潜在客户是IBM每年超过10亿美元的业务。然而,在过去,从多个海量数据源中搜索正确的技术以向客户展示价值是一项典型的人力劳动密集型任务。本文设计了一个潜在客户驱动的技术推荐系统,实现专利许可技术的自动检索。IBM的想法是,利用大型百科全书维基百科中的知识,结合1100万份专利文件,为IBM的潜在客户开发在线技术推荐系统。实时系统不仅需要快速的响应时间,还需要一组高度相关的专利文件,这些专利文件在技术上对查询的潜在客户很感兴趣。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Optimizing Service Selection in Dynamic Workflow Composition: Using Social Media to Develop Recommendations Model Driven Provisioning in Multi-tenant Clouds An Innovative System for Remote and Automated Testing of Mobile Phone Applications How Japanese Traditional "Omonpakari" Services are Delivered - A Multidisciplinary Approach Characterizing Service Assurance for Cloud-Based Implementations: Augmenting Assurance via Operations
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1