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Scalable Spectral Clustering with Weighted PageRank [chapter]

Dimitrios Rafailidis, Eleni Constantinou, Yannis Manolopoulos
2014 Lecture Notes in Computer Science  
According to the weighted PageRank algorithm, the most important nodes of the data affinity graph are selected as landmarks.  ...  The selected landmarks are provided to a landmark spectral clustering technique to achieve scalable and accurate clustering.  ...  -The complexity of the proposed spectral clustering method is preserved low, by following the landmark selection strategy of weighted PageRank and a landmark-based spectral clustering technique.  ... 
doi:10.1007/978-3-319-11587-0_27 fatcat:pgeusqowpzcbtaohaom6acphke

Searching the wikipedia with contextual information

Antti Ukkonen, Carlos Castillo, Debora Donato, Aristides Gionis
2008 Proceeding of the 17th ACM conference on Information and knowledge mining - CIKM '08  
We then use RankSVM (Joachims 2002) to learn weights for the individual features given suitably constructed training data.  ...  We propose a framework for searching the Wikipedia with contextual information.  ...  Of the approximate context-sensitive PageRank measures the one based on graph clustering outperforms the one using randomly selected landmarks.  ... 
doi:10.1145/1458082.1458274 dblp:conf/cikm/UkkonenCDG08 fatcat:7sd3le4xofa7dk2lt5nhz6qoyy

Link Prediction in Social Networks based on Spectral Clustering using k-medoids and Landmark

Asmaa M., Lamiaa M., Neveen I.
2017 International Journal of Computer Applications  
So two link prediction methods based on spectral clustering using k-medoids and landmark are proposed.  ...  General Terms Link prediction, landmark based spectral clustering, k-medoids algorithm  ...  Landmark Based Spectral Clustering Landmark based Spectral Clustering (LSC) depends on the recent progress of sparse coding [28] .  ... 
doi:10.5120/ijca2017914441 fatcat:zjubpl2mrzerlk4qyoog7dxzfa

Network Essence: PageRank Completion and Centrality-Conforming Markov Chains [chapter]

Shang-Hua Teng
2017 A Journey Through Discrete Mathematics  
I will discuss a simple result which summarizes some basic algebraic properties of personalized PageRank matrices.  ...  In this short exploration article, I will first share with readers my initial encounter with Jirka and discuss one of his fundamental geometric results from the early 1990s.  ...  They showed that for any cluster S ⊂ V , if one selects a random node v ∈ S with probability proportional to the weighted degree d v of the node, then, with probability at least 1/2, one can identify a  ... 
doi:10.1007/978-3-319-44479-6_31 fatcat:6pt6d3uxr5a63i67yb737q3ylm

Network Essence: PageRank Completion and Centrality-Conforming Markov Chains [article]

Shang-Hua Teng
2017 arXiv   pre-print
I will discuss a simple result which summarizes some basic algebraic properties of personalized PageRank matrices.  ...  In this short exploration article, I will first share with readers my initial encounter with Jirka and discuss one of his fundamental geometric results from the early 1990s.  ...  They showed that for any cluster S ⊂ V , if one selects a random node v ∈ S with probability proportional to the weighted degree d v of the node, then, with probability at least 1/2, one can identify a  ... 
arXiv:1708.07906v1 fatcat:hdzxzf2icjd3bjrc2nn2zo4the

Latent visual context learning for web image applications

Wengang Zhou, Qi Tian, Yijuan Lu, Linjun Yang, Houqiang Li
2011 Pattern Recognition  
We validate our approach on text-query based search results returned by Google Image.  ...  Recently, image representation based on bag-of-visual-words (BoW) model has been popularly applied in image and vision domains.  ...  Acknowledgement This work was supported in part by NSFC under contract No. 60632040 and 60672161, Program for New Century Excellent Talents in University (NCET), Research Enhancement Program (REP) and  ... 
doi:10.1016/j.patcog.2010.08.016 fatcat:lpckt5x4tbax5k2mbrrol5n6vu

Mode-seeking on graphs via random walks

Minsu Cho, Kyoung Mu Lee
2012 2012 IEEE Conference on Computer Vision and Pattern Recognition  
Mode-seeking has been widely used as a powerful data analysis technique for clustering and filtering in a metric feature space.  ...  We demonstrate our method on various synthetic experiments and real applications dealing with noisy and complex data such as scene summarization and object-based image matching.  ...  In (a), based on cluster authority values, AAS distinguishes inlier clusters from outlier ones.  ... 
doi:10.1109/cvpr.2012.6247727 dblp:conf/cvpr/ChoL12a fatcat:xyvrqdc5xfg5dj27jpdmvkhrpi

Clustered embedding of massive social networks

Han Hee Song, Berkant Savas, Tae Won Cho, Vacha Dave, Zhengdong Lu, Inderjit S. Dhillon, Yin Zhang, Lili Qiu
2012 Proceedings of the 12th ACM SIGMETRICS/PERFORMANCE joint international conference on Measurement and Modeling of Computer Systems - SIGMETRICS '12  
We show that the embedded graph captures the essential clustering and spectral structure of the original graph and allow a wide range of analysis to be performed on massive social graphs.  ...  In this paper, we embed the original massive social graph into a much smaller graph, using a novel dimensionality reduction technique termed Clustered Spectral Graph Embedding.  ...  We thank Vijay Erramilli and anonymous reviewers for their valuable comments.  ... 
doi:10.1145/2254756.2254796 dblp:conf/sigmetrics/SongSCDLDZQ12 fatcat:wa6jnlkpqfaypjo4l47xa3rbuu

Clustered embedding of massive social networks

Han Hee Song, Berkant Savas, Tae Won Cho, Vacha Dave, Zhengdong Lu, Inderjit S. Dhillon, Yin Zhang, Lili Qiu
2012 Performance Evaluation Review  
We show that the embedded graph captures the essential clustering and spectral structure of the original graph and allow a wide range of analysis to be performed on massive social graphs.  ...  In this paper, we embed the original massive social graph into a much smaller graph, using a novel dimensionality reduction technique termed Clustered Spectral Graph Embedding.  ...  We thank Vijay Erramilli and anonymous reviewers for their valuable comments.  ... 
doi:10.1145/2318857.2254796 fatcat:pdneff76mzenplvuqlbwlvduzq

Image webs: Computing and exploiting connectivity in image collections

Kyle Heath, Natasha Gelfand, Maks Ovsjanikov, Mridul Aanjaneya, Leonidas J. Guibas
2010 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition  
Our technique can link together tens of thousands of images in a few minutes using a computer cluster. We also demonstrate applications for exploring collections based on global topological analysis.  ...  We show how to efficiently construct Image Webs that capture the connectivity in an image collection using spectral graph theory.  ...  Thanks to Dmitriy Morozov for many helpful discussions and to Daniel Vaquero and Dingding Liu for helping collect data.  ... 
doi:10.1109/cvpr.2010.5539991 dblp:conf/cvpr/HeathGOAG10 fatcat:to35olhmundkrbdqxv7q754jym

Onomatology and content analysis of ergodic literature

Eugenia-Maria Kontopoulou, Maria Predari, Efstratios Gallopoulos
2013 Proceedings of the 3rd Narrative and Hypertext Workshop on - NHT '13  
We then consider some steps towards the construction of concept maps for CYOA-type ergodic literature. Our analysis is based on modeling ergodic literature using digraphs and matrices.  ...  Promising preliminary results are obtained using content to refine link-based ranking.  ...  These relied strictly on the link structure of these books to induce a ranking and were based on methods such as PageRank.  ... 
doi:10.1145/2462216.2462221 dblp:conf/ht/KontopoulouPG13 fatcat:53qk6udktrdbtifjz7imxmevsy

Evolving Networks and Social Network Analysis Methods and Techniques [chapter]

Mário Cordeiro, Rui P. Sarmento, Pavel Brazdil, João Gama
2018 Social Media and Journalism - Trends, Connections, Implications  
This chapter reviews the state of the art in selected aspects of evolving social networks presenting open research challenges related to OSNs.  ...  adding or by removing nodes or links over time: elementary actor-level network measures like network centrality change as a function of time, popularity and influence of individuals grow or fade depending on  ...  The authors also want to thank the reviewers for the constructive reviews provided in the development of this publication.  ... 
doi:10.5772/intechopen.79041 fatcat:x4m2g5borjfijknqck54ierppq

Query-Adaptive Hash Code Ranking for Large-Scale Multi-View Visual Search [article]

Xianglong Liu, Lei Huang, Cheng Deng, Bo Lang, Dacheng Tao
2019 arXiv   pre-print
For each hash table, a query-adaptive bitwise weighting is introduced to alleviate the quantization loss by simultaneously exploiting the quality of hash functions and their complement for nearest neighbor  ...  Comprehensive experiments on image search over three well-known benchmarks show that the proposed method achieves up to 17.11% and 20.28% performance gains on single and multiple table search over state-of-the-art  ...  For instance, these methods are usually designed for projection based hashing algorithms rather than cluster based ones like K-means hashing [49] .  ... 
arXiv:1904.08623v1 fatcat:v3xewtao3fetlcehfyfhs3kot4

Entailment and Spectral Clustering based Single and Multiple Document Summarization

Anand Gupta, Manpreet Kaur, Ahsaas Bajaj, Ansh Khanna
2019 International Journal of Intelligent Systems and Applications  
The experiments conducted on DUC 2003 and 2004 datasets reveal that the notion of Textual Entailment along with Spectral Clustering algorithm proves to be an effective duo for redundancy removal and generating  ...  In literature, Analog Textual Entailment and Spectral Clustering (ATESC) is one such method which has used TE to compute inter-sentence connectedness scores.  ...  Clustering based on Connectedness: The clustering of data points is based on finding some connected regions in data such as single link clustering [9] and spectral clustering [13] .  ... 
doi:10.5815/ijisa.2019.04.04 fatcat:obg2yrtbhrck3dewfshqk46taa

Combining co-clustering with noise detection for theme-based summarization

Xiaoyan Cai, Wenjie Li, Renxian Zhang
2013 ACM Transactions on Speech and Language Processing  
clusters and one noise sentence cluster.  ...  Moreover, noting that realworld datasets always contain noises which inevitably degrade the clustering performance, we incorporate noise detection with spectral clustering to generate ordinary sentence  ...  Then spectral clustering is applied based on this constrain-affinity matrix. We generate summaries from those clusters containing the query sentence(s).  ... 
doi:10.1145/2513563 dblp:journals/tslp/CaiLZ13 fatcat:k4j5v5stujclhpiqfeegz6ov7m
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