期刊簡(jiǎn)介預(yù)計(jì)審稿時(shí)間： 約3.0個(gè)月

TKDD welcomes papers on a full range of research in the knowledge discovery and analysis of diverse forms of data. Such subjects include, but are not limited to: scalable and effective algorithms for data mining and big data analysis, mining brain networks, mining data streams, mining multi-media data, mining high-dimensional data, mining text, Web, and semi-structured data, mining spatial and temporal data, data mining for community generation, social network analysis, and graph structured data, security and privacy issues in data mining, visual, interactive and online data mining, pre-processing and post-processing for data mining, robust and scalable statistical methods, data mining languages, foundations of data mining, KDD framework and process, and novel applications and infrastructures exploiting data mining technology including massively parallel processing and cloud computing platforms. TKDD encourages papers that explore the above subjects in the context of large distributed networks of computers, parallel or multiprocessing computers, or new data devices. TKDD also encourages papers that describe emerging data mining applications that cannot be satisfied by the current data mining technology.

TKDD 歡迎關(guān)于知識(shí)發(fā)現(xiàn)和分析各種不同形式數(shù)據(jù)的各種研究的論文。這些主題包括但不限于：可擴(kuò)展且有效的數(shù)據(jù)挖掘和大數(shù)據(jù)分析算法、挖掘腦網(wǎng)絡(luò)、挖掘數(shù)據(jù)流、挖掘多媒體數(shù)據(jù)、挖掘高維數(shù)據(jù)、挖掘文本、Web 和半結(jié)構(gòu)化數(shù)據(jù)、挖掘空間和時(shí)間數(shù)據(jù)、社區(qū)生成的數(shù)據(jù)挖掘、社交網(wǎng)絡(luò)分析和圖形結(jié)構(gòu)化數(shù)據(jù)、數(shù)據(jù)挖掘中的安全和隱私問題、可視化、交互式和在線數(shù)據(jù)挖掘、數(shù)據(jù)挖掘的預(yù)處理和后處理、穩(wěn)健且可擴(kuò)展的統(tǒng)計(jì)方法、數(shù)據(jù)挖掘語言、數(shù)據(jù)挖掘的基礎(chǔ)、KDD 框架和流程，以及利用數(shù)據(jù)挖掘技術(shù)（包括大規(guī)模并行處理和云計(jì)算平臺(tái)）的新型應(yīng)用程序和基礎(chǔ)設(shè)施。TKDD 鼓勵(lì)在大型分布式計(jì)算機(jī)網(wǎng)絡(luò)、并行或多處理計(jì)算機(jī)或新數(shù)據(jù)設(shè)備的背景下探索上述主題的論文。TKDD 還鼓勵(lì)描述當(dāng)前數(shù)據(jù)挖掘技術(shù)無法滿足的新興數(shù)據(jù)挖掘應(yīng)用的論文。

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