Titlebook: Advances in Knowledge Discovery and Data Mining; 13th Pacific-Asia Co Thanaruk Theeramunkong,Boonserm Kijsirikul,Tu-Bao Conference proceed

卑賤

書目名稱Advances in Knowledge Discovery and Data Mining影響因子(影響力)




書目名稱Advances in Knowledge Discovery and Data Mining影響因子(影響力)學(xué)科排名




書目名稱Advances in Knowledge Discovery and Data Mining網(wǎng)絡(luò)公開度




書目名稱Advances in Knowledge Discovery and Data Mining網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Advances in Knowledge Discovery and Data Mining被引頻次




書目名稱Advances in Knowledge Discovery and Data Mining被引頻次學(xué)科排名




書目名稱Advances in Knowledge Discovery and Data Mining年度引用




書目名稱Advances in Knowledge Discovery and Data Mining年度引用學(xué)科排名




書目名稱Advances in Knowledge Discovery and Data Mining讀者反饋




書目名稱Advances in Knowledge Discovery and Data Mining讀者反饋學(xué)科排名

友好關(guān)系

POWER

Lecture Notes in Computer Sciencehttp://image.papertrans.cn/a/image/148638.jpg

巨大沒有

口訣

https://doi.org/10.1007/978-3-319-78521-9ge relational databases. By hidden structural information we mean the information that cannot be easily found using a traditional query language SQL. In this talk, we discuss how to find hidden structural information in a relational database by viewing a relational database as a large directed graph

散步

Weight Disorders in Short Children,of magnitude more content is created daily to flow through social networks, with as much as two more orders of magnitude still to come as user engagement increases. Content is diversifying in creation, consumption, and nature. Web search engines provide rapid targeted access to this page content, an

Stricture

廣告

Pathological Findings for Esophageal Varicesepresent any interaction among entities, for example between people or even bank accounts. The need for link discovery arises in many applications including law enforcement, counter-terrorism, social network analysis, intrusion detection, and fraud detection. Given the sensitive nature of informatio

熔巖

Liver and Spleen Stiffness Measurement work showed that the simple technique of anonymizing graphs by replacing the identifying information of the nodes with random ids does not guarantee privacy since the identification of the nodes can be seriously jeopardized by applying subgraph queries. In this paper, we investigate how well an edg

Monocle