標(biāo)題: Titlebook: Big Data Analytics; Second International Vasudha Bhatnagar,Srinath Srinivasa Conference proceedings 2013 Springer International Publishing [打印本頁] 作者: 去是公開 時(shí)間: 2025-3-21 18:47
書目名稱Big Data Analytics影響因子(影響力)
書目名稱Big Data Analytics影響因子(影響力)學(xué)科排名
書目名稱Big Data Analytics網(wǎng)絡(luò)公開度
書目名稱Big Data Analytics網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Big Data Analytics被引頻次
書目名稱Big Data Analytics被引頻次學(xué)科排名
書目名稱Big Data Analytics年度引用
書目名稱Big Data Analytics年度引用學(xué)科排名
書目名稱Big Data Analytics讀者反饋
書目名稱Big Data Analytics讀者反饋學(xué)科排名
作者: Asperity 時(shí)間: 2025-3-21 20:25 作者: Grating 時(shí)間: 2025-3-22 03:46 作者: 抑制 時(shí)間: 2025-3-22 07:19 作者: 領(lǐng)帶 時(shí)間: 2025-3-22 09:43 作者: Override 時(shí)間: 2025-3-22 13:56 作者: 富饒 時(shí)間: 2025-3-22 17:04 作者: arabesque 時(shí)間: 2025-3-23 00:49
Challenges and Approaches for Large Graph Analysis Using Map/Reduce Paradigmively parallel ways (e.g., Map/Reduce, Bulk Synchronous Parallelization), as well as the ability to process unstructured data. This has allowed one to solve problems that were not possible (or extremely time consuming) earlier. Many algorithms are being mapped to new paradigms to deal with larger ve作者: 怒目而視 時(shí)間: 2025-3-23 02:11 作者: 打包 時(shí)間: 2025-3-23 07:32
Visualization of Small World Networks Using Similarity Matrices” Generally networks are represented using graph layouts and images of adjacency matrices, which have shortcomings of occlusion and spatial complexity in its direct form. These shortcomings are usually alleviated using pixel displays, hierarchical representations in the graph layout, and sampling an作者: 現(xiàn)存 時(shí)間: 2025-3-23 09:41
Demonstrator of a Tourist Recommendation Systemr. The gps positions are lined to the gps positions of the tourist sites (restaurants, beaches, museums ...). [9] These links are presented as a summary of the data. This summary is used to run specific versions of machine learning algorithms because of their geo-graphical dimension. This experiment作者: 敏捷 時(shí)間: 2025-3-23 14:35 作者: Blood-Vessels 時(shí)間: 2025-3-23 21:59
Pattern Recognition in Large-Scale Data Sets: Application in Integrated Circuit Manufacturingeters measured on a wafer. Linear discriminant analysis and artificial neural networks are used to classify a signature of test electrical measurements of a failed chip to one of several pre-determined root cause categories. An optimal decision rule that assigns a new incoming signature of a chip to作者: Atrium 時(shí)間: 2025-3-23 23:20
Performance Comparison of Hadoop Based Tools with Commercial ETL Tools – A Case Studyer and faster than commercial prevalent ETL tools. This paper presents a case study where experimental metric results have been presented in support of the claim. The reduction of cost makes it viable for small and large organizations alike and reduction in execution time makes it possible to provide online data services.作者: fulmination 時(shí)間: 2025-3-24 03:56
https://doi.org/10.1007/978-3-030-01364-6word-of-mouth diffusion mechanism through the network by defining a “copying” behavior. When a follower of a user tweets on the same topic as the user, the follower is said to have copied. We further make the definition time-dependent by imposing temporal thresholds on it.作者: COST 時(shí)間: 2025-3-24 07:24 作者: 精密 時(shí)間: 2025-3-24 10:41 作者: Neutropenia 時(shí)間: 2025-3-24 16:32 作者: dapper 時(shí)間: 2025-3-24 19:48
Stylometric Analysis for Authorship Attribution on Twittertwo stage process, where in the first stage, stylometric information is extracted from the collected dataset and in the second stage different classification algorithms are trained to predict authors of unseen text. The effort is towards maximizing the accuracy of predictions with optimum amount of data and users under consideration.作者: 事與愿違 時(shí)間: 2025-3-25 01:02 作者: 水土 時(shí)間: 2025-3-25 04:44 作者: 跳脫衣舞的人 時(shí)間: 2025-3-25 10:43
0302-9743 edings of the Second International Conference on Big Data Analytics, BDA 2013, held in Mysore, 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,作者: 確定無疑 時(shí)間: 2025-3-25 14:34 作者: 花費(fèi) 時(shí)間: 2025-3-25 19:30
Demonstrator of a Tourist Recommendation Systemry of the data. This summary is used to run specific versions of machine learning algorithms because of their geo-graphical dimension. This experiment shows how gps summaries of data can be used to extract relationships between stops of a car and touristic places.作者: 前兆 時(shí)間: 2025-3-25 20:34
0302-9743 e 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.978-3-319-03688-5978-3-319-03689-2Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: flammable 時(shí)間: 2025-3-26 02:45 作者: achlorhydria 時(shí)間: 2025-3-26 06:33 作者: 獨(dú)白 時(shí)間: 2025-3-26 11:01
https://doi.org/10.1007/978-3-030-01364-6OSN. Studies have shown that a small number of frequent users are responsible for the maximum percentage of tweets. We further hypothesize that users deviate from their usual tweeting hours when a major event occurs. With these as our underlying concepts, we introduce a new metric called “tweet stre作者: 制定 時(shí)間: 2025-3-26 14:06 作者: Precursor 時(shí)間: 2025-3-26 20:01 作者: Epithelium 時(shí)間: 2025-3-26 22:54 作者: 縱欲 時(shí)間: 2025-3-27 04:02
A?cha BenTaieb,Ghassan Hamarnehexpensive to deploy due to the high initial fixed costs of installing large-scale sensor-based systems. Sensors also require maintenance, thereby further adding to the costs. Moreover, sensors cannot be cost-effectively installed at all possible locations. Furthermore, some data collection scenarios作者: 碎石 時(shí)間: 2025-3-27 07:30
A?cha BenTaieb,Ghassan Hamarnehcan be said . if it appears periodically throughout the database. We have observed that it is difficult to mine periodic-frequent patterns in very large databases. The reason is that the occurrence behavior of the patterns can vary over a period of time causing periodically occurring patterns to be 作者: 違反 時(shí)間: 2025-3-27 09:37
https://doi.org/10.1007/978-94-011-6341-5ively parallel ways (e.g., Map/Reduce, Bulk Synchronous Parallelization), as well as the ability to process unstructured data. This has allowed one to solve problems that were not possible (or extremely time consuming) earlier. Many algorithms are being mapped to new paradigms to deal with larger ve作者: DENT 時(shí)間: 2025-3-27 16:13
https://doi.org/10.1007/978-94-011-6341-5tween players who have scored runs in partnership. Results of these complex network models based on partnership are compared with performance of teams. Our study examines Test cricket, One Day Internationals (ODIs) and T20 cricket matches of the Indian Premier League (IPL). We find that complex netw作者: Sarcoma 時(shí)間: 2025-3-27 21:01 作者: restrain 時(shí)間: 2025-3-28 01:51
https://doi.org/10.1007/978-94-015-8210-0r. The gps positions are lined to the gps positions of the tourist sites (restaurants, beaches, museums ...). [9] These links are presented as a summary of the data. This summary is used to run specific versions of machine learning algorithms because of their geo-graphical dimension. This experiment作者: 去世 時(shí)間: 2025-3-28 03:56
Roy W. Martin,Christopher C. Johnsonact, Transform and Load (ETL). Analytics is run on the DWH. The largest cost and execution time is associated with the ET part of this workflow. Recent approaches based on Hadoop, an open source Apache framework for data intensive scalable computing, provide an alternative for ET which is both cheap作者: 減至最低 時(shí)間: 2025-3-28 08:45 作者: canvass 時(shí)間: 2025-3-28 14:29
Vasudha Bhatnagar,Srinath SrinivasaFast-track conference proceedings.State-of-the-art research.Up to date results作者: 羊欄 時(shí)間: 2025-3-28 16:49
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/b/image/185599.jpg作者: 顧客 時(shí)間: 2025-3-28 20:24
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.作者: output 時(shí)間: 2025-3-29 02:04
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.作者: 自然環(huán)境 時(shí)間: 2025-3-29 04:19 作者: RUPT 時(shí)間: 2025-3-29 10:21
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.作者: animated 時(shí)間: 2025-3-29 12:16
https://doi.org/10.1007/978-3-319-03689-2Twitter; complex networks; graph algorithms; machine learning; social web; algorithm analysis and problem作者: paleolithic 時(shí)間: 2025-3-29 19:13
978-3-319-03688-5Springer International Publishing Switzerland 2013作者: 橡子 時(shí)間: 2025-3-29 23:39 作者: Abrade 時(shí)間: 2025-3-30 02:23
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.作者: 熱情的我 時(shí)間: 2025-3-30 07:35
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
