標(biāo)題: Titlebook: Data Mining for Social Network Data; Nasrullah Memon,Jennifer Jie Xu,Hsinchun Chen Book 2010 Springer Science+Business Media, LLC 2010 Map [打印本頁] 作者: 密度 時間: 2025-3-21 16:34
書目名稱Data Mining for Social Network Data影響因子(影響力)
書目名稱Data Mining for Social Network Data影響因子(影響力)學(xué)科排名
書目名稱Data Mining for Social Network Data網(wǎng)絡(luò)公開度
書目名稱Data Mining for Social Network Data網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Data Mining for Social Network Data被引頻次
書目名稱Data Mining for Social Network Data被引頻次學(xué)科排名
書目名稱Data Mining for Social Network Data年度引用
書目名稱Data Mining for Social Network Data年度引用學(xué)科排名
書目名稱Data Mining for Social Network Data讀者反饋
書目名稱Data Mining for Social Network Data讀者反饋學(xué)科排名
作者: transdermal 時間: 2025-3-22 00:03 作者: 歌唱隊(duì) 時間: 2025-3-22 03:37 作者: 蒙太奇 時間: 2025-3-22 04:48 作者: 仲裁者 時間: 2025-3-22 10:22 作者: Cabg318 時間: 2025-3-22 14:53 作者: Cabg318 時間: 2025-3-22 19:16
Modularity for Bipartite Networks,orks. Discovering communities from such bipartite networks is important for finding similar items and for understanding overall network structures. In order to evaluate the quality of divisions of normal (unipartite) networks, Newman’s modularity is widely used. Recently, modularities for bipartite 作者: 拱形大橋 時間: 2025-3-22 21:42
Framework for Fast Identification of Community Structures in Large-Scale Social Networks,other when compared to the rest of the networks, which encode the information about the organization and functionality of the nodes. Social networking sites (SNS), which allow the interaction of millions of users, have important scientific and practical implications; however, they require the develo作者: 爭吵加 時間: 2025-3-23 03:46 作者: Ophthalmologist 時間: 2025-3-23 08:14
Integrating Genetic Algorithms and Fuzzy Logic for Web Structure Optimization,ges of the considered Website. Fuzzy logic gives a degree of a membership to a problem and, hence, more adequately describes reasoning to a problem than a numeric deviation value does (the difference between the WPR index and log rank index), which does not give accurate human reasoning. Using fuzzy作者: DNR215 時間: 2025-3-23 10:03
https://doi.org/10.1007/978-1-4419-6287-4Mapping; Simulation; algorithms; calculus; data mining; information science; learning; machine learning; mod作者: aggressor 時間: 2025-3-23 17:14
978-1-4419-6286-7Springer Science+Business Media, LLC 2010作者: 寬大 時間: 2025-3-23 20:58 作者: theta-waves 時間: 2025-3-24 01:16 作者: 膠狀 時間: 2025-3-24 04:40 作者: Enliven 時間: 2025-3-24 09:39
Christliche Sagen (Exempel und Legenden),s are labeled with the polarity of the attitudes among them (positive, negative, and neutral). Our algorithm accepts as its input two social networks extracted via unsupervised algorithms: (1) a small signed network labeled with attitude polarities (see Tanev, ., Borovets, Bulgaria. pp. 33–40, 2007)作者: FAR 時間: 2025-3-24 13:24
https://doi.org/10.1007/978-3-476-99405-9entification from large volumes of text, this research mined the social networks among the cabinets of Presidents Reagan, G.H.W. Bush, Clinton, and G.W. Bush based on the members’ co-occurrence in news stories. Each administration’s data was sliced into time intervals corresponding to the Gallup pre作者: 北極熊 時間: 2025-3-24 15:05 作者: 相同 時間: 2025-3-24 22:58
Soil Environment in Sago Palm Forestynamics and complexity. This study focuses on the US air transportation network, which is one of the most diverse and dynamic transportation networks in the world. All of the data are drawn from the US Bureau of Transportation Statistics (BTS). The topology features show that the network is a scale-作者: 反感 時間: 2025-3-24 23:40
Life and Livelihood in Sago-Growing Areasworks are likely to attract more links and influence the use of knowledge by nodes connected directly or indirectly to them. In this study, we model knowledge flow within an innovative organization and contend that it exhibits unique characteristics not incorporated in most social network measures d作者: craving 時間: 2025-3-25 04:00
https://doi.org/10.1007/978-981-10-5269-9orks. Discovering communities from such bipartite networks is important for finding similar items and for understanding overall network structures. In order to evaluate the quality of divisions of normal (unipartite) networks, Newman’s modularity is widely used. Recently, modularities for bipartite 作者: 知識分子 時間: 2025-3-25 10:04 作者: 織物 時間: 2025-3-25 13:03 作者: Visual-Acuity 時間: 2025-3-25 19:13 作者: 廚師 時間: 2025-3-25 21:10
Data Mining for Social Network Data978-1-4419-6287-4Series ISSN 1934-3221 Series E-ISSN 1934-3213 作者: 言外之意 時間: 2025-3-26 02:34
Soil Environment in Sago Palm Forestry. A discrete dynamic model is constructed to investigate the evolution of the network. Our analysis offers direct confirmation for the existence of preferential attachment in the air transportation network. We conclude that both an aging effect and preferential attachment are the two mechanisms driving the network evolution.作者: Harpoon 時間: 2025-3-26 06:41 作者: 極微小 時間: 2025-3-26 09:50
1934-3221 dents in sociology, computer science and statistics.The reseDriven by counter-terrorism efforts, marketing analysis and an explosion in online social networking in recent years, data mining has moved to the forefront of information science. This proposed Special Issue on Data Mining for Social Netwo作者: Volatile-Oils 時間: 2025-3-26 15:51 作者: molest 時間: 2025-3-26 16:57
Christliche Sagen (Exempel und Legenden), been accompanied by the increasing popularity of social networking sites such as FaceBook and MySpace. As a result, research on ., or simply ., has attracted much attention from both academics and practitioners.作者: 有害 時間: 2025-3-26 21:36
Life and Livelihood in Sago-Growing Areasesigned to determine node status. Based on the model, we propose the use of a new measure based on team identification and random walks to determine status in knowledge networks. Using data obtained on collaborative patent networks, we find that the new measure performs better than others in identifying high-status inventors.作者: MAIM 時間: 2025-3-27 03:26
Running in the World Upside Down. Accordingly, we have shown how genetic algorithms (GA) can be applied to optimize the fuzzy membership functions. This chapter demonstrates how fuzzy logic can be applied to a deviation value to better represent the degree of restructuring.作者: Itinerant 時間: 2025-3-27 05:38
Integrating Genetic Algorithms and Fuzzy Logic for Web Structure Optimization,. Accordingly, we have shown how genetic algorithms (GA) can be applied to optimize the fuzzy membership functions. This chapter demonstrates how fuzzy logic can be applied to a deviation value to better represent the degree of restructuring.作者: 絆住 時間: 2025-3-27 12:38 作者: AMPLE 時間: 2025-3-27 15:53
Identifying High-Status Nodes in Knowledge Networks,esigned to determine node status. Based on the model, we propose the use of a new measure based on team identification and random walks to determine status in knowledge networks. Using data obtained on collaborative patent networks, we find that the new measure performs better than others in identifying high-status inventors.作者: 古代 時間: 2025-3-27 20:35 作者: Immunoglobulin 時間: 2025-3-27 22:26 作者: MEET 時間: 2025-3-28 05:11 作者: 礦石 時間: 2025-3-28 06:58
A Social Network-Based Recommender System (SNRS),our system by applying semantic filtering of social networks and validate its improvement via a class project experiment. In this experiment we demonstrate how relevant friends can be selected for inference based on the semantics of friend relationships and finer-grained user ratings. Such technolog作者: Headstrong 時間: 2025-3-28 12:00
Modularity for Bipartite Networks,proposes a new bipartite modularity for evaluating community extraction from bipartite networks. Experimental results show that our new bipartite modularity is appropriate for discovering close-knit communities, and it is also useful for characterizing the communities.作者: gene-therapy 時間: 2025-3-28 14:53
Framework for Fast Identification of Community Structures in Large-Scale Social Networks,improvement of CNM that considers the NIC and a new implementation framework to accelerate CNM. Our improvements were compared with the former CNM and its variations when applied to large-scale networks from seven real data sets (Mixi, Facebook, Flickr, LiveJournal, Orkut, YouTube, and Delicious) an作者: dialect 時間: 2025-3-28 19:36 作者: 欲望 時間: 2025-3-29 00:18
Book 2010very, social network analysis, and information infrastructures, and are anchored by Springer author/editor Hsinchun Chen (Terrorism Informatics; Medical Informatics; Digital Government), who is one of the most prominent intelligence analysis and data mining experts in the world.作者: Landlocked 時間: 2025-3-29 03:18
Christliche Sagen (Exempel und Legenden),quotations of P. about P.. The obtained set of labeled quotations is used to train a Na?ve Bayes classifier which then labels part of the remaining quotation network and adds it to the initial signed network. Since the social networks taken as the input are extracted in an unsupervised way, the whol作者: abduction 時間: 2025-3-29 07:41 作者: Exploit 時間: 2025-3-29 14:14
Soil Environment in Sago Palm Forestour system by applying semantic filtering of social networks and validate its improvement via a class project experiment. In this experiment we demonstrate how relevant friends can be selected for inference based on the semantics of friend relationships and finer-grained user ratings. Such technolog作者: 煉油廠 時間: 2025-3-29 18:15
