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Wisdom of Crowds cluster ensemble

Hosein Alizadeh, Muhammad Yousefnezhad, Behrouz Minaei Bidgoli
2015 Intelligent Data Analysis  
Inspired by this concept, we present a novel feedback framework for the cluster ensemble problem, which we call Wisdom of Crowds Cluster Ensemble (WOCCE).  ...  The Wisdom of Crowds is a phenomenon described in social science that suggests four criteria applicable to groups of people.  ...  The Wisdom of Crowds The Wisdom of Crowds (Surowiecki, 2004) presents numerous case studies, primarily in economics and psychology, to illustrate how the prediction performance of a crowd is better than  ... 
doi:10.3233/ida-150728 fatcat:nsughad2fvf27bc5fqx6f5vlru

WoCE: a framework for clustering ensemble by exploiting the wisdom of Crowds theory [article]

Muhammad Yousefnezhad, Sheng-Jun Huang, Daoqiang Zhang
2016 arXiv   pre-print
The Wisdom of Crowds (WOC), as a theory in the social science, gets a new paradigm in computer science.  ...  ., diversity, independency, decentralization and aggregation, to guide both the constructing of individual clustering results and the final combination for clustering ensemble.  ...  This work was supported in part by the National Natural Science Foundation of China (61422204, 61473149, and 61503182), Jiangsu Natural Science Foundation (BK20130034 and BK2015042628), and NUAA Fundamental  ... 
arXiv:1612.06598v1 fatcat:bzn3jt7ldrby5dh6v2ai2677bm

A Service Clustering Method Based on Wisdom of Crowds

Hui Gao, Karolina K. Dluzniak, Hong Xia, Wei Jie, Yanping Chen, Wei Xing, Xin Wang, Zhongmin Wang
2019 2019 IEEE International Congress on Big Data (BigDataCongress)  
In this paper, we proposed SWOC a service clustering method based on wisdom of crowd. Firstly, by using SWOC we calculated document similarity.  ...  At present, clustering method of web services adopted single or traditional clustering algorithms. However, accuracy and stability of single or traditional clustering algorithms is poor.  ...  Clustering Ensemble Based on Wisdom Crowd Surowiecki [14] introduced the concept of wisdom of crowds.  ... 
doi:10.1109/bigdatacongress.2019.00026 dblp:conf/bigdata/GaoDXJCXWW19 fatcat:alnjvgbffje55db7t6g6eg7r3m

Ensemble-driven support vector clustering: From ensemble learning to automatic parameter estimation [article]

Dong Huang, Chang-Dong Wang, Jian-Huang Lai, Yun Liang, Shan Bian, Yu Chen
2016 arXiv   pre-print
for SVC based on ensemble learning, and is capable of producing robust clustering results in a purely unsupervised manner.  ...  Support vector clustering (SVC) is a versatile clustering technique that is able to identify clusters of arbitrary shapes by exploiting the kernel trick.  ...  Without the expert, we appeal to the wisdom of the crowd and learn the parameters under the guidance of a crowd of individual clusterings.  ... 
arXiv:1608.01198v2 fatcat:c4zytmagrjfrfhxfxb5xwcbcdi

Image Clustering without Ground Truth [article]

Abhisek Dash, Sujoy Chatterjee, Tripti Prasad, Malay Bhattacharyya
2016 arXiv   pre-print
In this paper, we introduce a crowd-powered model to collect solutions of image clustering from the general crowd and pose it as a clustering ensemble problem with variable number of clusters.  ...  Given multiple such clustering solutions, it is a challenging task to obtain an ensemble of these solutions.  ...  All the authors would like to thank the crowd contributors involved in this work.  ... 
arXiv:1610.07758v1 fatcat:hy2dlik3wzhiznn4rrhtx753k4

Combining multiple clusterings via crowd agreement estimation and multi-granularity link analysis

Dong Huang, Jian-Huang Lai, Chang-Dong Wang
2015 Neurocomputing  
There are mainly two aspects of limitations in the existing clustering ensemble approaches.  ...  We present the normalized crowd agreement index (NCAI) to evaluate the quality of base clusterings in an unsupervised manner and thus weight the base clusterings in accordance with their clustering validity  ...  This work was supported by NSFC (61173084 and 61128009), National Science & Technology Pillar Program (No. 2012BAK16B06) and the Research Training Program of SMIE of Sun Yat-sen University.  ... 
doi:10.1016/j.neucom.2014.05.094 fatcat:j6jwkavz6zedjhcfkgavvdvtli

Break and Conquer: Efficient Correlation Clustering for Image Segmentation [chapter]

Amir Alush, Jacob Goldberger
2013 Lecture Notes in Computer Science  
Ensemble Segmentation The goal is to find a point in the "space of segmentations" which is close to all the individual segmentations. (Alush & Goldberger.  ...  = b 1−θ, if y lij = b The likelihood of the entire observation set y : Likelihood: p(y ) = ij b=0,1 l p θ (y lij |x ij = b) Computing the Most Likely Clustering Log Likelihood log p(y |x) = ij log p  ...  Wisdom of the Crowds • Each algorithm has its strengths (hopefully) & weaknesses. Goal: • Improving the final segmentation result by combining several segmentations.  ... 
doi:10.1007/978-3-642-39140-8_9 fatcat:2wud5gn4fjdjhjhycj72ulhvba

Harnessing the wisdom of crowds

Xingtian Shi, Zhenglu Yang, Masashi Toyoda, Masaru Kitsuregawa
2011 Proceedings of the 20th international conference companion on World wide web - WWW '11  
By borrowing the power of "the wisdom of crowds", we experimentally demonstrate that our approach can effectively detect video events.  ...  Although there has been a great deal of study on generic event detection in recent years, the performance of existing approaches is still far from satisfactory.  ...  This demonstrates the advantage on the usage of "the wisdom of crowds". CONCLUSION An integrated system on general video event detection is developed.  ... 
doi:10.1145/1963192.1963255 dblp:conf/www/ShiYTK11 fatcat:xjxmvukrzrai5hxjrz4g33hime

Editorial

2015 Intelligent Data Analysis  
The second article by Alizadeh et al. is a cluster ensemble approach in which the authors propose a feedback framework which they call wisdom of crowd cluster ensemble.  ...  Their proposed approach is based on the analysis of conditions necessary for a crowd to exhibit the collective wisdom.  ... 
doi:10.3233/ida-150726 fatcat:ydwsfst2mjdldm6x2wk3cdg2bi

Wisdom of artificial crowds feature selection in untargeted metabolomics: An application to the development of a blood-based diagnostic test for thrombotic myocardial infarction [article]

Patrick J. Trainor, Roman V. Yampolskiy, Andrew P. DeFilippis
2017 bioRxiv   pre-print
Objective: We employed a Wisdom of Artificial Crowds (WoAC) strategy for solving the feature selection problem and evaluated the accuracy and parsimony of downstream classifiers in comparison with embedded  ...  Materials and Methods: Artificial Crowd Wisdom was generated via aggregation of the best solutions from independent and diverse genetic algorithm populations that were initialized with bootstrapping and  ...  The authors thank the members of the Atherosclerosis and Atherothrombosis Research laboratory at the University of Louisville for help with sample processing and Samantha Carlisle, M.S. for her assistance  ... 
doi:10.1101/165977 fatcat:upewkgi3fnfkviwwhsxw74mbuu

Contents [chapter]

2021 Data Science for Supply Chain Forecasting  
of the Crowd and Ensemble Models | 138 15.2 Bagging Trees in a Forest | 139 15.3 Do It Yourself | 141 15.4 Insights | 144 16 Feature Importance | 147 16.1 Do It Yourself | 148 17 Extremely  ...  Do It Yourself | 126 14 Parameter Optimization | 130 14.1 Simple Experiments | 130 14.2 Smarter Experiments | 131 14.3 Do It Yourself | 134 14.4 Recap | 137 15 Forest | 138 15.1 The Wisdom  ... 
doi:10.1515/9783110671124-toc fatcat:xer3h5luanf2hefrekb6hqhi3y

Condorcet's Jury Theorem for Consensus Clustering and its Implications for Diversity [article]

Brijnesh J. Jain
2016 arXiv   pre-print
As an implication of practical relevance, we question the claim that the quality of consensus clustering depends on the diversity of the sample partitions.  ...  Condorcet's Jury Theorem has been invoked for ensemble classifiers to indicate that the combination of many classifiers can have better predictive performance than a single classifier.  ...  9 We show the assertion of Eq. (3) . By assumption, the support SQ is contained in an open subset of the asymmetry ball AZ .  ... 
arXiv:1604.07711v2 fatcat:laz5ba3e75csbcktiix2jqwqaa

Supervised learning of gene-regulatory networks based on graph distance profiles of transcriptomics data

Zahra Razaghi-Moghadam, Zoran Nikoloski
2020 npj Systems Biology and Applications  
Our GRADIS approach offers the possibility for usage of other network-based representations of large-scale data, and can be readily extended to help the characterisation of other cellular networks, including  ...  Characterisation of gene-regulatory network (GRN) interactions provides a stepping stone to understanding how genes affect cellular phenotypes.  ...  This work has been supported by the MELICOMO project 031B0358B of the German Federal Ministry of Science and Education to Z.N.  ... 
doi:10.1038/s41540-020-0140-1 pmid:32606380 fatcat:5zqbvd2ecjb75mkkdf3avv777i

Online Prediction via Continuous Artificial Prediction Markets

Fatemeh Jahedpari, Talal Rahwan, Sattar Hashemi, Tomasz P. Michalak, Marina De Vos, Julian Padget, Wei Lee Woon
2017 IEEE Intelligent Systems  
predictions by reflecting upon the wisdom of the crowd, which is manifested in the collective performance of the market.  ...  Recently, they have been introduced to the machine-learning community in the form of Artificial Prediction Markets, whereby algorithms trade contracts reflecting their levels of confidence.  ...  other agents, thus incorporating the wisdom of the crowd.  ... 
doi:10.1109/mis.2017.12 fatcat:uzpnj6yfk5f4fpfay6lo4um6vi

Identifying Topical Twitter Communities via User List Aggregation [article]

Derek Greene and Derek O'Callaghan and Pádraig Cunningham
2012 arXiv   pre-print
This approach involves the use of ensemble community finding to produce stable groupings of user lists, and by extension, individual Twitter users.  ...  A particular challenge in the area of social media analysis is how to find communities within a larger network of social interactions.  ...  This research was supported by Science Foundation Ireland Grant 08/SRC/I1407 (Clique: Graph and Network Analysis Cluster).  ... 
arXiv:1207.0017v1 fatcat:rpyzetn2rzb4hhahuemf2o4nmm
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