Titlebook: Innovation Networks; Concepts and Challen Knut Koschatzky,Marianne Kulicke,Andrea Zenker Conference proceedings 2001 Springer-Verlag Berlin

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書目名稱Innovation Networks影響因子(影響力)




書目名稱Innovation Networks影響因子(影響力)學(xué)科排名




書目名稱Innovation Networks網(wǎng)絡(luò)公開度




書目名稱Innovation Networks網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Innovation Networks被引頻次




書目名稱Innovation Networks被引頻次學(xué)科排名




書目名稱Innovation Networks年度引用




書目名稱Innovation Networks年度引用學(xué)科排名




書目名稱Innovation Networks讀者反饋




書目名稱Innovation Networks讀者反饋學(xué)科排名

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scene, and its difference for different users, as well as the travel time limitation. In this paper, we provide two approximate algorithms: a local optimization algorithm and a global optimization algorithm. Finally, we give an experimental evaluation of the proposed algorithms using real datasets i

Etymology

Knut Koschatzkychical semantic representation model of news comments using multiple information sources, called Hierarchical Semantic Neural Network (HSNN). In particular, we begin with a novel neural network model to learn document representation in a bottom-up way, capturing not only the semantics within sentenc

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e of level-wise coverage patterns to allocate incoming search queries to advertisers in an efficient manner by utilizing the long tail. Experimental results on AOL search query data set show improvement in ad space utilization and reach of advertisers.

senile-dementia

Emmanuel Muller and processes queries in several small sets to retrieve more diverse results. The balance of similarity and diversity is determined through setting a threshold, which has a default value and can be adjusted according to users’ preference. The performance and efficiency of our system are demonstrate

prodrome

Simone Strambachchical semantic representation model of news comments using multiple information sources, called Hierarchical Semantic Neural Network (HSNN). In particular, we begin with a novel neural network model to learn document representation in a bottom-up way, capturing not only the semantics within sentenc

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