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Titlebook: Big Data Analytics; Second International Vasudha Bhatnagar,Srinath Srinivasa Conference proceedings 2013 Springer International Publishing

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41#
發(fā)表于 2025-3-28 16:49:39 | 只看該作者
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/b/image/185599.jpg
42#
發(fā)表于 2025-3-28 20:24:03 | 只看該作者
Tutorial : Social Media Analyticsiew the state of the art as well as present new ideas on handling common research problems like Event Detection from Social Media, Summarization, Location Inference and fusing external data sources with social data. The tutorial would assume basic knowledge of Data Mining, Text Analytics and NLP Methods.
43#
發(fā)表于 2025-3-29 02:04:54 | 只看該作者
Conference proceedings 2013ysore, India, in December 2013. The 13 revised full papers were carefully reviewed and selected from 49 submissions and cover topics on mining social media data, perspectives on big data analysis, graph analysis, big data in practice.
44#
發(fā)表于 2025-3-29 04:19:35 | 只看該作者
45#
發(fā)表于 2025-3-29 10:21:50 | 只看該作者
John Kingdom,Philip Baker,Eve Blairiew the state of the art as well as present new ideas on handling common research problems like Event Detection from Social Media, Summarization, Location Inference and fusing external data sources with social data. The tutorial would assume basic knowledge of Data Mining, Text Analytics and NLP Methods.
46#
發(fā)表于 2025-3-29 12:16:55 | 只看該作者
https://doi.org/10.1007/978-3-319-03689-2Twitter; complex networks; graph algorithms; machine learning; social web; algorithm analysis and problem
47#
發(fā)表于 2025-3-29 19:13:26 | 只看該作者
978-3-319-03688-5Springer International Publishing Switzerland 2013
48#
發(fā)表于 2025-3-29 23:39:02 | 只看該作者
49#
發(fā)表于 2025-3-30 02:23:36 | 只看該作者
The Role of Incentive-Based Crowd-Driven Data Collection in Big Data Analytics: A Perspectivee also provide some directions about the kind of analytics that can be done on the crowd-collected data in case of different application scenarios. Furthermore, we discuss some of the open research issues in this area.
50#
發(fā)表于 2025-3-30 07:35:47 | 只看該作者
Discovering Quasi-Periodic-Frequent Patterns in Transactional Databasesled quasi-periodic-frequent patterns. Informally, a frequent pattern is said to be . if most of its occurrences are periodic in a database. We propose a model and a pattern-growth algorithm to discover these patterns. The proposed patterns do not satisfy the downward closure property. We have introd
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