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Titlebook: Information Retrieval Technology; 14th Asia Informatio Yuen-Hsien Tseng,Tetsuya Sakai,Zhi-Hong Chen Conference proceedings 2018 Springer Na

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Minoru Yoshida,Kazuyuki Matsumoto,Kenji KitaBlack..Berry Native Development, you‘ll learn how to quicklyYou‘ve developed a killer app for one mobile device—now it’s time to maximize your intellectual investment and develop for the full spectrum of mobile platforms and devices. With .Cracking Windows Phone and BlackBerry Native Development., y
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rted to finding a career.Also highlights other career optionThis book offers valuable insights into completing your Ph.D., and subsequently finding and excelling at a job. Further, it highlights other opportunities that a Ph.D. can offer, aside from the research and academic aspects. The book focuse
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Chong Chen,Min Zhang,Yiqun Liu,Shaoping Marted to finding a career.Also highlights other career optionThis book offers valuable insights into completing your Ph.D., and subsequently finding and excelling at a job. Further, it highlights other opportunities that a Ph.D. can offer, aside from the research and academic aspects. The book focuse
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Wai Chung Wong,Sunny Lai,Wai Lam,Kwong Sak Leungrted to finding a career.Also highlights other career optionThis book offers valuable insights into completing your Ph.D., and subsequently finding and excelling at a job. Further, it highlights other opportunities that a Ph.D. can offer, aside from the research and academic aspects. The book focuse
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rted to finding a career.Also highlights other career optionThis book offers valuable insights into completing your Ph.D., and subsequently finding and excelling at a job. Further, it highlights other opportunities that a Ph.D. can offer, aside from the research and academic aspects. The book focuse
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Chinese Governmental Named Entity Recognition, short text NER etc. In this paper, we study the problem of Chinese governmental NER (CGNER). CGNER serves as the basis for automatic governmental text analysis, which can greatly benefit the public. Considering the characteristics of the governmental text, we first formulate the task of CGNER, add
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Personalized Social Search Based on Agglomerative Hierarchical Graph Clusteringl network service (SNS). The proposed algorithm generates cluster information on users in the social network by using an agglomerative hierarchical graph clustering, and stores it to a contents database (DB). Retrieved contents are sorted by scores calculated according to similarities of cluster inf
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