Journal Title：Acm Transactions On Knowledge Discovery From Data

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 歡迎關于知識發現和分析各種不同形式數據的各種研究的論文。這些主題包括但不限于：可擴展且有效的數據挖掘和大數據分析算法、挖掘腦網絡、挖掘數據流、挖掘多媒體數據、挖掘高維數據、挖掘文本、Web 和半結構化數據、挖掘空間和時間數據、社區生成的數據挖掘、社交網絡分析和圖形結構化數據、數據挖掘中的安全和隱私問題、可視化、交互式和在線數據挖掘、數據挖掘的預處理和后處理、穩健且可擴展的統計方法、數據挖掘語言、數據挖掘的基礎、KDD 框架和流程，以及利用數據挖掘技術（包括大規模并行處理和云計算平臺）的新型應用程序和基礎設施。TKDD 鼓勵在大型分布式計算機網絡、并行或多處理計算機或新數據設備的背景下探索上述主題的論文。TKDD 還鼓勵描述當前數據挖掘技術無法滿足的新興數據挖掘應用的論文。

Acm Transactions On Knowledge Discovery From Data創刊于2006年，由Association for Computing Machinery (ACM)出版商出版，收稿方向涵蓋COMPUTER SCIENCE, INFORMATION SYSTEMS - COMPUTER SCIENCE, SOFTWARE ENGINEERING全領域，此刊是中等級別的SCI期刊，所以過審相對來講不是特別難，但是該刊專業認可度不錯，仍然是一本值得選擇的SCI期刊 。平均審稿速度 約3.0個月 ，影響因子指數4，該期刊近期沒有被列入國際期刊預警名單，廣大學者值得一試。