Nethept Dataset


This dataset was the main dataset used in my Ph. covered communities, we test SCD on both synthesized datasets and real-world social traces, including the NetHEPT collaboration, Foursquare, Twitter and Facebook social networks, in reference to the consensus of other state-of-the-art detection methods. NET DataSets. K is set to 15 for the C. A new algorithm, named ComPath, is proposed based on the linear threshold model. The vehicle is outfitted with a professional (Applanix POS LV) and consumer (Xsens MTI-G) Inertial Measuring Unit (IMU), a Velodyne 3D-lidar scanner, two push-broom forward looking Riegl lidars, and a Point Grey Ladybug3 omnidirectional camera system. Flexible Data Ingestion. It is created by use of “High Energy Physics (Theory)” part of arXiv3 which is the collaboration network of paper authors. It's a great way to get started. TVSum Dataset. 4 maximal degree 64 1065 3079 number of connected com1781 24 11 ponents largest compo6794 7066 76K nent size average compo8. TheNetHEPTdataset [36] is extensively usedin many. 발표자: 고윤용(한양대 박사과정) 발표일: 2018. NetHEPT dataset: •collaboration network from physics archive •15K nodes, 31K edges Epinions dataset: •who -trust whom network of Epinions. Looking for a historical road network dataset for my bachelors'. one algorithm to achieve different efficiency-effectiveness tradeoff needs by properly tuning the parameters. In the remainder of the paper, we pro-vide an overview of the existing change detection datasets as well as survey papers, and summarize the 2012 CDnet dataset. Socable Influence Maximization 1. Static Face Images for all the identities in VoxCeleb2 can be found in the VGGFace2 dataset. And we adopt the Amazon dataset and the DBLP dataset provided in the SNAP project for our example. I've never used a DataSet correctly (hooked up to an SQL Server), but it was useful for a particular need once. , 2010a, Chen et al. Flexible Data Ingestion. Please click on the dataset name to find out more information about it. 内容提示: Wei Chen Microsoft Research Asia In collaboration with Chi Wang University of Illinois at Urbana-Champaign Yajun Wang Microsoft Research Asia KDD'10, July 27, 2010 1 Scalable Influence Maximization for Prevalent Viral Marketing in Large-Scale Social Networks Outline KDD'10, July 27, 2010 2 Background and problem definition Maximum Influence Arborescence (MIA) heuristic. Project StatLog (Esprit Project 5170) was concerned with comparative studies of different machine learning, neural and statistical classification algorithms. In the remainder of the paper, we pro-vide an overview of the existing change detection datasets as well as survey papers, and summarize the 2012 CDnet dataset. Scalable Bicriteria Algorithms for the Threshold Activation Problem in Online Social Networks † † thanks: ©2017 IEEE. Please sign up to review new features, functionality and page designs. 现在一土建工地做工长一职,多年管理经验!. Explore Popular Topics Like Government, Sports, Medicine, Fintech, Food, More. A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Vinod Chandra, K. 04, not easily speed up Greedy by reducing the number of sim- 0. zip into C:/IPA Demo/Data (optional to handle dataset from Stanford Large Network Dataset Collection). cy, michael. On the NetS and NetHEPT dataset, our STMB algorithm is roughly two times faster than the PageRank , High - Degree and 800- 3500 times faster than the Greedy. The experimental results showed that BNII performed significantly better than the other well-known imputation techniques. It is created by use of "High Energy Physics (Theory)" part of arXiv3 which is the collaboration network of paper authors. We study the problem of profit maximization in social networks through influence diffusion. ComPath is faster and more efficient than the state of the art algorithms. one algorithm to achieve different efficiency-effectiveness tradeoff needs by properly tuning the parameters. zip into C:/IPA Demo/Data (optional to handle dataset from Stanford Large Network Dataset Collection). zip into C:/IPA Demo/Desktop App. It provides detailed information about datasets ranging from censuses and surveys to health records and vital statistics, globally. Debunking the Myths of Influence Maximization Akhil Arora1, Sainyam Galhotra1, Sayan Ranu [email protected] NetHEPT: This dataset is derived from "High Energy Physics" and is a web-based data about authors of articles. Experiments: Datasets & Results 34. RSS Feeds for scholarly journal Tables of Contents (TOCs). arora, srinivas. Time vs seeds for di®erent datasets CELF++ (NetHept) ASIM (NetHept) CELF++ (HepPH) ASIM (HepPH) FUTURE DIRECTIONS Extension to the LT model Prove approximation. Influence maximization (IM) is the problem of finding a seed set composed of k nodes that maximize their influence spread over …. A new algorithm, named ComPath, is proposed based on the linear threshold model. elegans dataset. 2M Average Degree 4. On the NetS and NetHEPT dataset, our STMB algorithm is roughly two times faster than the PageRank , High - Degree and 800- 3500 times faster than the Greedy. A consideration of citation distribution by subfield shows that the citation patterns of high energy physics form a remarkably homogeneous network. We carried out extensive experiments on real-world dynamic social networks including Facebook, NetHEPT, and Flickr. APHA FOI & EIR Information Requests Received 2017 Published by: Animal and Plant Health Agency Last updated: 16 May 2018. It contains close to the minimum number of header fields that need to be set in nifti1 dataset and have it still conform to the nifti1 standard. jj (NetHEPT) Simulation Results. Required period -- mimid-1980s (1983, to be precise) until today. The dataset is so huge – it can’t be loaded all in memory. Abstract: This is a transnational data set which contains all the transactions occurring between 01/12/2010 and 09/12/2011 for a UK-based and registered non-store online retail. NetHEPT dataset: •collaboration network from physics archive •15K nodes, 31K edges Epinions dataset: •who -trust whom network of Epinions. SWAPNIL DHAMAL. 4 Maximal Degree 64 588 3079 425 #Connected Com1781 73K 11 1 ponent Largest Component 6794 517K 76K 262K Size Average Compo8. This can been seen for NetHEPT (WC) dataset in Figure 2. "The Dataset Catalog is publicly accessible and you can browse dataset details without logging in. One noticeable result is the knee in the curve of our algorithm. We're upgrading the ACM DL, and would like your input. Slight increase of the total number of events by fixing errors in the dataset preprocessing. A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Given a new graph, randomly sample a small portion of nodes in the graph to compute the average arborescence sizes with varying 1/, and nd a point where the change of arborescence size slows down, and use the value at that point for the. [email protected] If we do not require a very tight approximation ratio, we could choose a larger …. It contains close to the minimum number of header fields that need to be set in nifti1 dataset and have it still conform to the nifti1 standard. It takes MixGreedy more than as much as 6 hours to identify the top-50 influential nodes on the final NetHEPT dataset, while the time is even longer on the larger dataset Facebook. Moreover, MixGreedy is not feasible to run on the largest dataset Flickr due to the unbearably long running time. Conclusion 51. , 2010a, Chen et al. TheNetHEPTdataset [36] is extensively usedin many. Explore Popular Topics Like Government, Sports, Medicine, Fintech, Food, More. 발표자: 고윤용(한양대 박사과정) 발표일: 2018. Dataset Description node edge Flixster movie social 29357 212614 NetHEPT author/co-author 15233 62774 50. Influence maximization (IM) is the problem of finding a seed set composed of k nodes that maximize their influence spread over …. , 2010a, Chen et al. It contains 34 nodes, 78 edges Each node indicates the club member Edge indicates the two members take the. Abstract: This is a transnational data set which contains all the transactions occurring between 01/12/2010 and 09/12/2011 for a UK-based and registered non-store online retail. Permission f. img and minimal. php: 2019-07-24 10:33. 2) Extract the data set from a Zachary's karate club network. Community expansion in social networks. On the NetS and NetHEPT dataset, our STMB algorithm is roughly two times faster than the PageRank , High - Degree and 800- 3500 times faster than the Greedy. Public: This dataset is intended for public access and use. CELF++: Optimizing the Greedy Algorithm for. covered communities, we test SCD on both synthesized datasets and real-world social traces, including the NetHEPT collaboration, Foursquare, Twitter and Facebook social networks, in reference to the consensus of other state-of-the-art detection methods. A large-scale, high-quality dataset of URL links to approximately 650,000 video clips that covers 700 human action classes, including human-object interactions such as playing instruments, as well as human-human interactions such as shaking hands and hugging. Detailed simulation setup is provided in [11]. Scalable Bicriteria Algorithms for the Threshold Activation Problem in Online Social Networks † † thanks: ©2017 IEEE. 3 Empirical Analysis We have conducted experiments in real-world datasets in order to evaluate. TVSum Dataset. When … = 0. It represents a complete set of data including the tables that contain, order, and constrain the data, as well as the relationships between the tables. •Datasets KDD'2016, Aug. Lakshmanan Dept. msr-tr-2010-2_v2_工学_高等教育_教育专区。social fluence. Creates a dataset named Cultural Context Content (CCC) for each language edition with the articles that relate to its cultural context (geography, people, traditions, history, companies, etc. Therefore, we can use Figure 7: Running time and average arborescence size of PMIA vs. This research is supported by the National Research Foundation, Prime Minister's Office, Singapore, under its IDM Futures Funding Initiative, and by Singapore Ministry of Education Academic Research Fund Tier 1 under Grant 2017-T1-002-024 and Tier 2 under Grant MOE2015-T2-2-114. This dataset includes States, Counties or Boroughs, Congressional Districts, Alaska Recording Districts, County Subdivisions, and Places boundaries that are derived from the latest official Census Bureau and Alaska Department of Natural Resources datasets. The release of the 2004-2006 data marks the beginning of a new phase of data collection, Phase V. Figure 8: maximal inuence spread by 50 seeds w. Abstract: Given a budget and arbitrary cost for selecting each node, the budgeted influence maximization (BIM) problem concerns selecting a set of seed nodes to disseminate some information that maximizes the total number of nodes influenced (termed as influence spread) in social networks at a total cost no more than the budget. CELF++: Optimizing the Greedy Algorithm for Influence Maximization in Social Networks Amit Goyal Dept. Please sign up to review new features, functionality and page designs. This dataset was the main dataset used in my Ph. Minimizing Seed Set Selection with Probabilistic Coverage Guarantee in a Social Network Peng Zhang1, Wei Chen2, Xiaoming Sun3, Yajun Wang2, Jialin Zhang3 1. 3 Empirical Analysis We have conducted experiments in real-world datasets in order to evaluate. It is a test network. The dataset does not contain information that identifies patients, EMS agencies, receiving hospitals, or reporting states. [email protected] In the remainder of the paper, we pro-vide an overview of the existing change detection datasets as well as survey papers, and summarize the 2012 CDnet dataset. I found DataSet and DataView to be pretty handy and functional base classes for implementing a data/BLL tier until I could put something really thought-out in place. Our dataset consists of the personality profiles and Facebook profile data of 180,000 users. For 2 phases on NetHEPT dataset (15,233 nodes) [6, 7, 25], Figure 1(a) presents optimal budget allotted for phase 1 as a function of w0 jj (assuming equal w 0 jj,∀j ∈N) with kд = kb =100(U=1andv (0) i = 0,∀i∈N). Febrary 21, 2018 Page 21/22 • Diffusion model - Independent cascade (IC) model The weight of edge (u, v) = 1/𝑖𝑑𝑒𝑔𝑟𝑒𝑒 𝑣 𝑖𝑑𝑒𝑔𝑟𝑒𝑒 𝑣 : the number of in-coming edges of node v • Dataset Experimental setup Dataset NetHEPT NetPHY Stanford DBLP # of Nodes 15K 37K 281K 655K # of Edges 58K 231K 2. MAR Quantitative Current MAR Data. Get complete information about SAP Authorization Object S_DATASET Authorization For File Access including related authorization fields and connections to other authorization objects. We make use of structural communities of the input network. Influence maximization (IM) is the problem of finding a seed set composed of k nodes that maximize their influence spread over …. 内容提示: Wei Chen Microsoft Research Asia In collaboration with Chi Wang University of Illinois at Urbana-Champaign Yajun Wang Microsoft Research Asia KDD'10, July 27, 2010 1 Scalable Influence Maximization for Prevalent Viral Marketing in Large-Scale Social Networks Outline KDD'10, July 27, 2010 2 Background and problem definition Maximum Influence Arborescence (MIA) heuristic. Once the DataSet has been filled, the connection can be closed and the DataSet's contents can still be examined and manipulated. C# Dataset Tutorial The ADO. 03461v3 [cs. Hence credit distribution is not a bigissue. It is created by use of “High Energy Physics (Theory)” part of arXiv3 which is the collaboration network of paper authors. , 2009, Chen et al. Permission f. Personal use of this material is permitted. When … = 0. covered communities, we test SCD on both synthesized datasets and real-world social traces, including the NetHEPT collaboration, Foursquare, Twitter and Facebook social networks, in reference to the consensus of other state-of-the-art detection methods. the optimization introduced in CELF++ is orthogonal to the method used for estimating the spread, our idea can be combined with the heuristic approaches that are based on the greedy algorithm to obtain highly scalable algorithms for influence maximization. WikiVote NetHEPT EpinionsEmail-EuAll 10-2 100 102 104 106 Running time (s) Greedy SimPath LDAG MATI Degree (a) (b) Fig. dataset: the 2014 CDnet. 15, 2014 23 graph # of nodes # of edges edge probabilities description Wiki-Vote 7,115 103,689 synthetic, weighted cascade voting network in Wikipedia NetHEPT 15,233 58,891 synthetic, weighted cascade collaboration network in arxiv. the threshold 1 /θ in the WC model, for NetHEPT dataset. virinchi, shourya. Multiple advertisers are willing to p. NetHEPT: a well-known dataset that has been used in many studies (Chen et al. •Datasets KDD'2016, Aug. Analyzing Competitive Influence Maximization Problems with Partial Information Yishi Lin, John C. It is created by use of "High Energy Physics (Theory)" part of arXiv3 which is the collaboration network of paper authors. I Node Level feedback (NL) has results comparable to Edge Level feedback (EL) for all algorithms across datasets. Identifying the most influential individuals can provide invaluable help in developing and deploying effective viral marketing strategies. In 2017, Atlanta, GA had a population of 486k people with a median age of 33. 발표자: 고윤용(한양대 박사과정) 발표일: 2018. NetHEPT: This dataset is derived from "High Energy Physics" and is a web-based data about authors of articles. It contains 34 nodes, 78 edges Each node indicates the club member Edge indicates the two members take the. img and minimal. Problem Motivation Problem Formulation Models Adopter Model Benefit Model Combine Model Algorithm Experiments Conclusion. of Sci andTech of China This work was done during the internships of Wei Lu and Ning Zhang at Microsoft Research Asia. CELF++: Optimizing the Greedy Algorithm for Influence Maximization in Social Networks (Technical Report) Amit Goyal Dept. All the datasets are taken from KONECT except NetHEPT which is a scientific collaboration network taken from the High Energy Physics - Theory citations from arXiv. Amit Goyal. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U. SWAPNIL DHAMAL. NetHEPT dataset: •collaboration network from physics archive •15K nodes, 31K edges Epinions dataset: •who -trust whom network of Epinions. This dataset provides a list of the requests handled by APHA under Freedom of Information legislation and Environmental Information Regulations during 2017. Purdue University. the graph to compute the average arborescence sizes with varying 1 /θ, and find a point where the change of arborescence size slows down, and use the θ value at that point for the PMIA algorithm. Holistic Influence Maximization: Combining Scalability and Efficiency with Opinion-Aware Models Sainyam Galhotra∗ Akhil Arora∗ Shourya Roy Text and Graph Analytics (TGA), Xerox Research Centre India (XRCI), Bangalore, India. It is not the very minimum, because one could create 1 dimensional image. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U. Phase V includes data on 71 variables. [email protected] Online Retail Data Set Download: Data Folder, Data Set Description. The project performed a comparative study between Statistical, Neural and Symbolic learning algorithms. Abstract: Given a budget and arbitrary cost for selecting each node, the budgeted influence maximization (BIM) problem concerns selecting a set of seed nodes to disseminate some information that maximizes the total number of nodes influenced (termed as influence spread) in social networks at a total cost no more than the budget. It contains close to the minimum number of header fields that need to be set in nifti1 dataset and have it still conform to the nifti1 standard. Millions of images and YouTube videos, linked and tagged to teach computers what a spoon is. Keywords—mobile social networks (MSNs), mobile ad hoc networks (MANETs), influence maximization, distributed. The dataset consists of over 20,000 face images with annotations of age, gender, and ethnicity. We carried out extensive experiments on real-world dynamic social networks including Facebook, NetHEPT, and Flickr. Then, we present the 2014 CDnet dataset. CELF++ Algorithm 1 describes the CELF++ algorithm. Online Retail Data Set Download: Data Folder, Data Set Description. Detailed simulation setup is provided in [11]. ResearchArticle On the Shoulders of Giants: Incremental Influence Maximization in Evolving Social Networks XiaodongLiu,XiangkeLiao,ShanshanLi,SiZheng,BinLin,JingyingZhang,LisongShao,. The DataSet is a memory-resident representation of data that provides a consistent relational programming model regardless of the data source. Flexible Data Ingestion. The experiments are conducted on three real-world social networks, and the experimental results show that more accurate partitions according to influence propagation can be obtained using our algorithms rather than using some classic community partition algorithms. We report the results of the first world-scale social-network graph-distance computations, using the entire Facebook network of active users (≈ 721 million users, ≈ 69 billion friendship links). The most frequently used is the degree-. 발표자: 고윤용(한양대 박사과정) 발표일: 2018. This is a collection of DataTables. Further, we utilize the knowledge of the citation distributions to demonstrate the extreme improbability that the citation records of selected individuals and institutions have been obtained by a. Empirical results indicate that our methods are among the best ones for hinting out those important nodes in comparison with other available methods. msr-tr-2010-2_v2_工学_高等教育_教育专区。social fluence. Social Problems Final inference inference in bayesian networks. Experimental evaluations are carried out by use of NetHEPT and Epinion datasets. Note that NetHEPT has only 15K nodes, which is the smallest among all datasets. Clearly, DEGREE is the fastest algorithm. The first dataset, NetHEPT, is an ery node, which takes O(n) time. Fixed incorrect timing information that has crashed the Java processing. UTKFace dataset is a large-scale face dataset with long age span (range from 0 to 116 years old). Search the history of over 371 billion web pages on the Internet. IV-Greedy significantly outperforms Top-K. Project StatLog (Esprit Project 5170) was concerned with comparative studies of different machine learning, neural and statistical classification algorithms. Detailed simulation setup is provided in [11]. msr-tr-2010-2_v2_工学_高等教育_教育专区 67人阅读|3次下载. This can been seen for NetHEPT (WC) dataset in Figure 2. I found DataSet and DataView to be pretty handy and functional base classes for implementing a data/BLL tier until I could put something really thought-out in place. Additional source code and datasets (for other publications) can be made available. , 2010b, Goyal et al. We use the DataSet type to store many DataTables in a single collection. Simulation results in real and synthetic datasets manifest that the message overhead can be significantly reduced compared with the existing approaches. NetHEPT: a well-known dataset that has been used in many studies (Chen et al. Over the past several months we have had a look at a number of top Github repository collections, such as: Top 10 Machine Learning Projects on Github Top. However, real-world datasets are not accessible in many cases due to privacy concerns and business competition. SWAPNIL DHAMAL. (a) NetHEPT (b) Flixster (c) Flickr I Pure Exploitation (PE), -Greedy (EG) are e ective and able to decrease the regret across all datasets. This page summarizes the netCDF-Java API use of URLs. , 2011b, Kempe et al. , 2010a, Chen et al. Identifying the most influential individuals can provide invaluable help in developing and deploying effective viral marketing strategies. ComPath is faster and more efficient. Emotion labels obtained using an automatic classifier can be found for the faces in VoxCeleb1 here as part of the 'EmoVoxCeleb' dataset. Please sign up to review new features, functionality and page designs. Analyzing Competitive Influence Maximization Problems with Partial Information Yishi Lin, John C. Data are based on information from all resident death certificates filed in the 50 states and the District of Columbia using demographic and medical characteristics. We compare the performance of IV-Greedy against a set of baseline algorithms in terms of both influence spread and time efficiency. Conclusion 51. Experimental results demonstrate that, compared with the state-of-the-art static heuristic, IncInf achieves as much as 21 \(\times \) speedup in execution time while maintaining matching performance in terms of influence spread. CELF++: Optimizing the Greedy Algorithm for. 03461v3 [cs. Conceptually, the DataSet acts as a set of DataTable instances. com •76K nodes, 509K edges 104 times >103 times speed up speed up Running time is for selecting 50 seeds. for audio-visual speech recognition), also consider using the LRS dataset. Agent-based multi-edge network simulation model for knowledge diffusion through board interlocks. of Computer Science. CELF++: Optimizing the Greedy Algorithm for Influence Maximization in Social Networks (Technical Report) Amit Goyal Dept. If you require text annotation (e. zip from Wei Chen's project page extract ipa-preprocessor. jj (NetHEPT) Simulation Results. The dataset consists of over 20,000 face images with annotations of age, gender, and ethnicity. 1: (a) Influence spread in number of nodes under the LT model for the EPINIONS dataset. The problem of influence maximization is to select the most influential individuals in a social network. We're upgrading the ACM DL, and would like your input. Abstract: This is a transnational data set which contains all the transactions occurring between 01/12/2010 and 09/12/2011 for a UK-based and registered non-store online retail. fm, Flixster, and DBLP. It combats the defects of existing mothods, leveraging end-to-end deep learning to make an anology to interpretable factors of Hawkes process. 2 Influence spread of different algorithms on four real datasets 如 图2(a) 、 (b) 所示,在NetHEPT和Facebook数据集上LTDIM和Opt-LTDIM与静态算法的影响范围非常接近。. Time-Critical Influence Maximization in Social Networks withTime-Delayed Diffusion Process Wei Chen Wei Lu Ning Zhang Microsoft ResearchAsia U. The experimental results showed that BNII performed significantly better than the other well-known imputation techniques. The most frequently used is the degree-. A large-scale, high-quality dataset of URL links to approximately 650,000 video clips that covers 700 human action classes, including human-object interactions such as playing instruments, as well as human-human interactions such as shaking hands and hugging. arora, srinivas. running time, for the NetHEPT dataset in the WC model. The problem of influence maximization is to select the most influential individuals in a social network. It is noted that the Y-axis is in logarithmic scale. We make use of structural communities of the input network. zip into C:/IPA Demo/Data (optional to handle dataset from Stanford Large Network Dataset Collection). We use the DataSet type to store many DataTables in a single collection. The experiments are conducted on three real-world social networks, and the experimental results show that more accurate partitions according to influence propagation can be obtained using our algorithms rather than using some classic community partition algorithms. Simulation results in real and synthetic datasets manifest that the message overhead can be significantly reduced compared with the existing approaches. This is a collection of DataTables. Dataset Description node edge Flixster movie social 29357 212614 NetHEPT author/co-author 15233 62774 50. We choose three real-world social networks: Facebook social network, NetHEPT citation network, and Flickr social network (Table 2 summarizes the statistical information of the datasets): (i) Facebook: this dataset is the friendship relationship network among New Orleans regional network on Facebook, spanning from September 2006 to January 2009. The netCDF-Java library can read datasets from a variety of sources. Conceptually, the DataSet acts as a set of DataTable instances. Arts & Humanities; Communications; Marketing; How to influence people with partial incentives Please share. K is set to 15 for the C. Email your request. Emotion labels obtained using an automatic classifier can be found for the faces in VoxCeleb1 here as part of the 'EmoVoxCeleb' dataset. extract graphdata. 2M Average Degree 4. EFFECTIVENESS OF DIFFUSING INFORMATION THROUGH A SOCIAL NETWORK IN MULTIPLE PHASES 8 Our general observation is that an optimal budget split is the one which would lead to an almost equal number of nodes getting influenced in expectation, across the given number of phases. IV-Greedy significantly outperforms Top-K. The release of the 2004-2006 data marks the beginning of a new phase of data collection, Phase V. com NetHEPT A co-authorship network from arxiv. In this dataset, nodes show the authors of papers and links demonstrate the collaboration of two authors in a paper. cy, blackburn. Note that NetHEPT has only 15K nodes, which is the smallest among all datasets. We report the results of the first world-scale social-network graph-distance computations, using the entire Facebook network of active users (≈ 721 million users, ≈ 69 billion friendship links). org High Energey Physics Theory section. , 2011b, Kempe et al. Consider (these are JavaScript examples): [code] var a = [1,2,3], b = [1,2,3,4,5,6], c. EFFECTIVENESS OF DIFFUSING INFORMATION THROUGH A SOCIAL NETWORK IN MULTIPLE PHASES 8 Our general observation is that an optimal budget split is the one which would lead to an almost equal number of nodes getting influenced in expectation, across the given number of phases. UTKFace dataset is a large-scale face dataset with long age span (range from 0 to 116 years old). TheNetHEPTdataset [36] is extensively usedin many. ca Wei Lu Dept. Summary and Future Plan • Non-adaptive model. Time Critical Influence Maximization 1. On the NetS and NetHEPT dataset, our STMB algorithm is roughly two times faster than the PageRank , High - Degree and 800- 3500 times faster than the Greedy. This approach is also supported by a key connection between the persistence probability of a community and its local topology. Scalable influence maximization for independent cascade model in large-scale social networks. Since a DataSet represents a separate, disconnected collection of data, it's no surprise that the DataSet's data is both editable and can be accessed randomly, two traits not exhibited by the DataReader. Abstract: Publication date: Available online 20 September 2019Source: Expert Systems with ApplicationsAuthor(s): C. the threshold 1 /θ in the WC model, for NetHEPT dataset. To verify our suggested solutions, we conduct experiments on real world traces including NetHEPT, NetHEPT_WC and Facebook networks. one algorithm to achieve different efficiency-effectiveness tradeoff needs by properly tuning the parameters. The problem of influence maximization is to select the most influential individuals in a social network. dataset: the 2014 CDnet. Moreover, MixGreedy is not feasible to run on the largest dataset Flickr due to the unbearably long running time. ASIM: A Scalable Algorithm for Influence Maximization under the Independent Cascade Model Sainyam Galhotra, Akhil Arora, Srinivas Virinchi, and Shourya Roy Xerox Research Centre India, Bangalore {sainyam. The average distance we observe is 4:74, corresponding to 3:74 intermediaries or "degrees of separation", prompting the title of this paper. The dataset is so huge – it can’t be loaded all in memory. [email protected] To certify the efficiency and stability of the discovered communities, we test SCD on both synthesized datasets and real-world social traces, including the NetHEPT collaboration, Foursquare, Twitter and Facebook social. This dataset was the main dataset used in my Ph. 图2 4个真实数据集上算法的影响范围 Fig. Detailed simulation setup is provided in [11]. We use the learning result of [35] in our ex-periment, which is a graph containing 29357 nodes and 212614 directed edges. of Sci andTech of China This work was done during the internships of Wei Lu and Ning Zhang at Microsoft Research Asia. If you did the training yourself, you probably realized we can’t train the system on the whole dataset (I chose to train it on the first 2000 sentences). 92% increase and its median household income grew from $53,843 to $57,597, a 6. of Computer Science University of British Columbia Vancouver, BC, Canada [email protected] Our dataset consists of the personality profiles and Facebook profile data of 180,000 users. To recognize the valuable role of National Household Travel Survey (NHTS) data in the transportation research process and to facilitate repeatability of the research, users of NHTS data are asked to formally acknowledge the data source. the optimization introduced in CELF++ is orthogonal to the method used for estimating the spread, our idea can be combined with the heuristic approaches that are based on the greedy algorithm to obtain highly scalable algorithms for influence maximization. of Computer Science University of British Columbia Vancouver, BC, Canada [email protected] Acknowledgements. This is a collection of DataTables. ca Wei Lu Dept. Dataset Description node edge Flixster movie social 29357 212614 NetHEPT author/co-author 15233 62774 50. Yuanjun Bi Jan. Online Retail Data Set Download: Data Folder, Data Set Description. datasets on two IC models, while Figure 6 shows the. , 2009, Chen et al. Our dataset consists of the personality profiles and Facebook profile data of 180,000 users. The dataset includes the users that sent or received at least one message (1,899). It is noted that the Y-axis is in logarithmic scale. Abstract: Given a budget and arbitrary cost for selecting each node, the budgeted influence maximization (BIM) problem concerns selecting a set of seed nodes to disseminate some information that maximizes the total number of nodes influenced (termed as influence spread) in social networks at a total cost no more than the budget. [email protected] We examine correlations between users' personality We show how users' activity on Facebook relates to their personality, as measured by the standard Five Factor Model. img and minimal. Therefore, we can use Figure 7: Running time and average arborescence size of PMIA vs. (dh)The DeepHawkes model is proposed to predict the popularity of information.