Titlebook: Agents and Data Mining Interaction; 9th International Wo Longbing Cao,Yifeng Zeng,Philip S. Yu Conference proceedings 2014 Springer-Verlag

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书目名称Agents and Data Mining Interaction影响因子(影响力)学科排名




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书目名称Agents and Data Mining Interaction网络公开度学科排名




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书目名称Agents and Data Mining Interaction被引频次学科排名




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书目名称Agents and Data Mining Interaction年度引用学科排名




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书目名称Agents and Data Mining Interaction读者反馈学科排名

aesthetician

Diverticulitis

Towards Mining Norms in Open Source Software Repositoriested. Open source communities offer exciting new application opportunities for extracting norms since such communities involve developers from different geographical regions, background and cultures. Investigating the types of norms that exist in open source projects and their efficacy (i.e. .) in en

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Redundant Feature Selection for Telemetry Dataity of agents that use the data [.]. Supervised feature selection aims to overcome this problem by selecting features that are highly related to the class labels, yet unrelated to each other. One proposed technique to select good features with few inter-dependencies is minimal Redundancy Maximal Rel

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疼死我了

Learning Heterogeneous Coupling Relationships Between Non-IID Termsthe text data has increased its importance, a variety of text mining and process algorithms have been created in the recent years such as classification, clustering, similarity comparison. Most previous research uses a vector-space model for text representation and analysis. However, the vector-spac

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COWER

A Spectral Clustering Algorithm Based on Hierarchical Methodomplex structures. In the past few years, several spectral clustering algorithms were proposed to cluster arbitrarily shaped data in various real applications including image processing and web analysis. However, most of these algorithms were based on k-means, which is a randomized algorithm and mak

茁壮成长

Transitive Identity Mapping Using Force-Based Clusteringtantiates each record as an agent that actively self-organizes with other agents (including queries). Imitating the movement of bodies under physical forces, we describe a distributed algorithm (“force-based clustering,” or FBC) for dynamically clustering and querying large, heterogeneous, dynamic c