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Non-negative Laplacian Embedding

Dijun Luo, Chris Ding, Heng Huang, Tao Li
<span title="">2009</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/gckg3mzs4fhxhbrvmbsa54bccm" style="color: black;">2009 Ninth IEEE International Conference on Data Mining</a> </i> &nbsp;
The true power of Laplacian embedding is that it provides an approximation of the Ratio Cut clustering. However, Ratio Cut clustering requires the solution to be nonnegative.  ...  Empirical studies on many real world datasets show that our approach leads to more accurate Ratio Cut solution and improves clustering accuracy at the same time.  ...  Shi and Malik [24] further developed this into normalized cut clustering. Ding et al, [9] further developed this into the min-max cut clustering.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/icdm.2009.74">doi:10.1109/icdm.2009.74</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/icdm/LuoDHL09.html">dblp:conf/icdm/LuoDHL09</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/wtbte77nf5fabi5qunqwinxpde">fatcat:wtbte77nf5fabi5qunqwinxpde</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170705100124/http://users.cs.fiu.edu/~taoli/pub/ICDM10-3895a337.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/34/a1/34a1d075e6f4a9cea93b916ebac2f3bbdc2c5ab8.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/icdm.2009.74"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

A survey on graph partitioning approach to spectral clustering

Subhanshu Goyal, M A ZAVERI, SUSHIL KUMAR, A K SHUKLA
<span title="2015-03-31">2015</span> <i title="Publishing House for Science and Technology, Vietnam Academy of Science and Technology"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/x6rvdhhbgrgmrbjsa2vpyeos5e" style="color: black;">Journal of Computer Science and Cybernetics</a> </i> &nbsp;
This study uses different graph cluster formulations based on graph cut and partitioning problems.  ...  The clustering problem can be formulated as a graph cut problem where a suitable objective function has to be optimized.  ...  ACKNOWLEDGMENT The first author thanks to Prof. Unni Krishnan A. for helpful conversations about this study.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.15625/1813-9663/31/1/4108">doi:10.15625/1813-9663/31/1/4108</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/pj64oxkbm5ajlei4wsgshzufei">fatcat:pj64oxkbm5ajlei4wsgshzufei</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190430073344/http://vjs.ac.vn/index.php/jcc/article/download/4108/5406" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/f2/19/f219b37c677663d15b5a1503bb836f30febcdcbf.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.15625/1813-9663/31/1/4108"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

An Improved Multi-Class Spectral Clustering Based on Normalized Cuts [chapter]

Diego Hernán Peluffo-Ordóñez, Carlos Daniel Acosta-Medina, César Germáan Castellanos-Domínguez
<span title="">2012</span> <i title="Springer Berlin Heidelberg"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
In this work, we present an improved multi-class spectral clustering (MCSC) that represents an alternative to the standard k-way normalized clustering, avoiding the use of an iterative algorithm for tuning  ...  The performance of proposed method is compared with the conventional MCSC and k-means in terms of different clustering quality indicators.  ...  This research is carried out within the projects: "Beca para estudiantes sobresalientes de posgrado de la Universidad Nacional de Colombia" and "Programa de financiación para Doctorados Nacionales de Colciencias  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-33275-3_16">doi:10.1007/978-3-642-33275-3_16</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/rufrnzk7gjbtto57ygvzdgvjqy">fatcat:rufrnzk7gjbtto57ygvzdgvjqy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20181030071308/https://link.springer.com/content/pdf/10.1007%2F978-3-642-33275-3_16.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/3d/7c/3d7cde1e313e1989d4f568c5f82030f3381cb52e.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-33275-3_16"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Towards highly scalable X10 based spectral clustering

Hidefumi Ogata, Miyuru Dayarathna, Toyotaro Suzumura
<span title="">2012</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/zwrt4lmoffgrpejt4mmp2p34kq" style="color: black;">2012 19th International Conference on High Performance Computing</a> </i> &nbsp;
To solve this problem, we implemented spectral clustering in X10, that is a programming language aimed for developing highly scalable applications on Post-Petascale supercomputers.  ...  Clustering is one of the most important types of analysis that has versatile applications such as community detection in social networks, image segmentation, graph partitioning, etc.  ...  Because of this, we can evaluate the precision of spectral clustering results by the value of the normalized cut (i.e. the smaller normalized cut is, the better result is.)  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/hipc.2012.6507522">doi:10.1109/hipc.2012.6507522</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/hipc/OgataDS12.html">dblp:conf/hipc/OgataDS12</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/2wliwia6wvakzmzf3hv5gaumw4">fatcat:2wliwia6wvakzmzf3hv5gaumw4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170830095601/https://www.computer.org/csdl/proceedings/hipc/2012/2372/00/06507522.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/cb/d7/cbd7cdf964fe9e27e03783afef0359529ec00f05.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/hipc.2012.6507522"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

External reviewers

<span title="">2005</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/v5fagqotxjcn3jsjkqi336dzse" style="color: black;">Third European Conference on Web Services (ECOWS&#39;05)</a> </i> &nbsp;
Here we focus on minimizing the normalized cut, but other minimization problems are tractable in the same way.  ...  Spectral Clustering uses simple tools of Linear Algebra and gives heuristic algorithms for combinatorial, usually NP-complete, problems arising in many applications of image segmentation, clustering and  ...  of the normalized cut problem.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/ecows.2005.15">doi:10.1109/ecows.2005.15</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/icws/X05k.html">dblp:conf/icws/X05k</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/atnxumrm4nbujjiplk3rbsyjci">fatcat:atnxumrm4nbujjiplk3rbsyjci</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190225110928/http://pdfs.semanticscholar.org/5ea4/213727c7d786447c6e05f12c17e7fe084a63.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/5e/a4/5ea4213727c7d786447c6e05f12c17e7fe084a63.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/ecows.2005.15"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Locality Preserving Clustering for Image Database

Xin Zheng
<span title="">2006</span> <i title="China Science Publishing &amp; Media Ltd."> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/5koq3u7tlndvfiokviviotumli" style="color: black;">Journal of Computer Research and Development</a> </i> &nbsp;
Spectral clustering method has been one of the most promising clustering methods in the last few years, because it can cluster data with complex structure, and the (near) global optimum is guaranteed.  ...  However, existing spectral clustering algorithms, like Normalized Cut, are difficult to handle data points out of training set.  ...  Technically, LPP solves a generalized eigenvalue problem, but the original LPP algorithm stated in [8] may mix true solutions (eigenvectors) with pseudo solutions and the trivial solution.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1360/crad20060314">doi:10.1360/crad20060314</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/rilsk66buvccffduz6zbroi2ke">fatcat:rilsk66buvccffduz6zbroi2ke</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170921234146/http://people.cs.uchicago.edu/%7Exiaofei/conference-21.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/e9/a3/e9a30d3af3db29eb1039016f8ca9f963013de2e8.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1360/crad20060314"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Semi-Supervised Normalized Cuts for Image Segmentation

Selene E. Chew, Nathan D. Cahill
<span title="">2015</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/753trptklbb4nj6jquqadzwwdu" style="color: black;">2015 IEEE International Conference on Computer Vision (ICCV)</a> </i> &nbsp;
An approximate spectral solution to the reformulated problem exists without requiring explicit construction of a large, dense matrix; hence, computation time is comparable to that of unconstrained NCuts  ...  Since its introduction as a powerful graph-based method for image segmentation, the Normalized Cuts (NCuts) algorithm has been generalized to incorporate expert knowledge about how certain pixels or regions  ...  Acknowledgements Thanks to Paul Wenger and the anonymous reviewers for helpful comments. Selene Chew was supported by RIT's Honors Summer Undergraduate Research Program.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/iccv.2015.200">doi:10.1109/iccv.2015.200</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/iccv/ChewC15.html">dblp:conf/iccv/ChewC15</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/c7rlwlfhbjg55duyzlkcqvhovy">fatcat:c7rlwlfhbjg55duyzlkcqvhovy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20160128064407/http://www.cv-foundation.org/openaccess/content_iccv_2015/papers/Chew_Semi-Supervised_Normalized_Cuts_ICCV_2015_paper.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/7e/6a/7e6aace92f8caaee4fbce488fc35f03baf30ff1b.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/iccv.2015.200"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Fast approximate Random Walker segmentation using eigenvector precomputation

Leo Grady, Ali Kemal Sinop
<span title="">2008</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ilwxppn4d5hizekyd3ndvy2mii" style="color: black;">2008 IEEE Conference on Computer Vision and Pattern Recognition</a> </i> &nbsp;
Specifically, we show that one may precompute several eigenvectors of the weighted Laplacian matrix of a graph and use this information to produce a linear-time approximation of the Random Walker segmentation  ...  Finally, we also show that this procedure may be interpreted as a seeded (interactive) Normalized Cuts algorithm.  ...  We then develop the connection between this precomputed Random Walker algorithm and Normalized Cuts.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/cvpr.2008.4587487">doi:10.1109/cvpr.2008.4587487</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/cvpr/GradyS08.html">dblp:conf/cvpr/GradyS08</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/jtoz44nv2bfgdp7z5bhhtzmdvi">fatcat:jtoz44nv2bfgdp7z5bhhtzmdvi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20131123011155/http://www.math.ias.edu/~asinop/pubs/approximate_rw-gs08.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/fb/17/fb17dc3a24946cde446bb2b4ac83667a98f64040.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/cvpr.2008.4587487"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Piecewise Flat Embedding for Image Segmentation

Chaowei Fang, Zicheng Liao, Yizhou Yu
<span title="">2018</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/3px634ph3vhrtmtuip6xznraqi" style="color: black;">IEEE Transactions on Pattern Analysis and Machine Intelligence</a> </i> &nbsp;
of the input image.  ...  We adopt an L 1 -regularized energy term in the formulation to promote sparse solutions.  ...  Spectral clustering and the original Normalized Cut use the same eigenvectors, but differ in the way they use these eigenvectors.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tpami.2018.2839733">doi:10.1109/tpami.2018.2839733</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/29994301">pmid:29994301</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/hyro23ksnnghhal7gtcruc4vve">fatcat:hyro23ksnnghhal7gtcruc4vve</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190224032816/http://pdfs.semanticscholar.org/4fe5/d4e7b943657b710c82d1f57aeea4869a1ae5.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/4f/e5/4fe5d4e7b943657b710c82d1f57aeea4869a1ae5.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tpami.2018.2839733"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Piecewise Flat Embedding for Image Segmentation

Yizhou Yu, Chaowei Fang, Zicheng Liao
<span title="">2015</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/753trptklbb4nj6jquqadzwwdu" style="color: black;">2015 IEEE International Conference on Computer Vision (ICCV)</a> </i> &nbsp;
of the input image.  ...  We adopt an L 1 -regularized energy term in the formulation to promote sparse solutions.  ...  Spectral clustering and the original Normalized Cut use the same eigenvectors, but differ in the way they use these eigenvectors.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/iccv.2015.161">doi:10.1109/iccv.2015.161</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/iccv/YuFL15.html">dblp:conf/iccv/YuFL15</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/7thljv7z4ngzle2aoaarynoz2i">fatcat:7thljv7z4ngzle2aoaarynoz2i</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170809062310/http://i.cs.hku.hk/~yzyu/publication/PFE-iccv2015.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/ab/71/ab71467ccbf4a963ad0ce03abd0796620d1daa5a.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/iccv.2015.161"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Application of Spectral Clustering Methods in Pipeline Systems Graph Models

Gul'naz I. Galimova, Il'nur D. Galimyanov, Dinar T. Yakupov, Vladimir V. Mokshin
<span title="2019-10-31">2019</span> <i title="BioAxis DNA Research Centre"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/grcyvowbjbbnfdmv2azpa6ltf4" style="color: black;">Helix</a> </i> &nbsp;
In this paper, we consider the basic principles of the theory of spectral clustering, describe the main approach of normalized spectral clustering of graphs.  ...  To solve this problem, the authors propose an algorithm for the priority distribution of nodes based on iterative transfer of nodes of isolated areas to the most priority neighboring subgraphs.  ...  Acknowledgements The work is performed according to the Russian Government Program of Competitive Growth of Kazan Federal University.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.29042/2019-5607-5614">doi:10.29042/2019-5607-5614</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/3h5d4a3vn5duvowvsqaifsi3zq">fatcat:3h5d4a3vn5duvowvsqaifsi3zq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220223130203/http://helix.dnares.in/wp-content/uploads/2019/11/5607-5614.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/1d/d1/1dd1e1f6cc81dca20d56e28fcf3a17cfbbf6364b.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.29042/2019-5607-5614"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Improving document clustering using automated machine translation

Xiang Wang, Buyue Qian, Ian Davidson
<span title="">2012</span> <i title="ACM Press"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/6g37zvjwwrhv3dizi6ffue642m" style="color: black;">Proceedings of the 21st ACM international conference on Information and knowledge management - CIKM &#39;12</a> </i> &nbsp;
With the development of statistical machine translation, we have ready-to-use tools that can translate documents from one language to many other languages.  ...  In this work, we propose an alternative approach to address this problem using the constrained clustering framework.  ...  and NSF Grant NSF IIS-0801528 Knowledge Enhanced Clustering.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/2396761.2396844">doi:10.1145/2396761.2396844</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/cikm/WangQD12.html">dblp:conf/cikm/WangQD12</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/k3idu2evvvexxhpb23gvezvgam">fatcat:k3idu2evvvexxhpb23gvezvgam</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20160501232556/http://www.buyueqian.info/papers/Buyue_CIKM12.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/4f/db/4fdb7467939a03427226327f565a2a2d0d9a4fb3.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/2396761.2396844"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> acm.org </button> </a>

Document clustering with prior knowledge

Xiang Ji, Wei Xu
<span title="">2006</span> <i title="ACM Press"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ibcfmixrofb3piydwg5wvir3t4" style="color: black;">Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR &#39;06</a> </i> &nbsp;
The document clustering task is accomplished by finding the best cuts of the graph under the constraints. We apply the model to the Normalized Cut method to demonstrate the idea and concept.  ...  We propose to incorporate prior knowledge of cluster membership for document cluster analysis and develop a novel semi-supervised document clustering model.  ...  ACKNOWLEDGMENT The authors want to thank Mei Han for her valuable comments, Yihong Gong for his help on editing, and the reviewers for their constructive comments and suggestions.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/1148170.1148241">doi:10.1145/1148170.1148241</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/sigir/JiX06.html">dblp:conf/sigir/JiX06</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/4dem3wc2rrewnlbef3jdy3vyse">fatcat:4dem3wc2rrewnlbef3jdy3vyse</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190217201012/https://static.aminer.org/pdf/20170130/pdfs/sigir/4nuac7iy1u2my9he3qkz8zvdbhrofrld.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/a0/91/a091201c6ab67c35cba86bfecf542a9eabc2a38f.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/1148170.1148241"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> acm.org </button> </a>

Locality preserving clustering for image database

Xin Zheng, Deng Cai, Xiaofei He, Wei-Ying Ma, Xueyin Lin
<span title="">2004</span> <i title="ACM Press"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/lahlxihmo5fhzpexw7rundu24u" style="color: black;">Proceedings of the 12th annual ACM international conference on Multimedia - MULTIMEDIA &#39;04</a> </i> &nbsp;
Spectral clustering method has been one of the most promising clustering methods in the last few years, because it can cluster data with complex structure, and the (near) global optimum is guaranteed.  ...  However, existing spectral clustering algorithms, like Normalized Cut, are difficult to handle data points out of training set.  ...  Technically, LPP solves a generalized eigenvalue problem, but the original LPP algorithm stated in [8] may mix true solutions (eigenvectors) with pseudo solutions and the trivial solution.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/1027527.1027731">doi:10.1145/1027527.1027731</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/mm/ZhengCHML04.html">dblp:conf/mm/ZhengCHML04</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/u5el5xpl6rdyddvnb5jksuknma">fatcat:u5el5xpl6rdyddvnb5jksuknma</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170921234146/http://people.cs.uchicago.edu/%7Exiaofei/conference-21.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/e9/a3/e9a30d3af3db29eb1039016f8ca9f963013de2e8.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/1027527.1027731"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> acm.org </button> </a>

Kernel k-means

Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis
<span title="">2004</span> <i title="ACM Press"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/fqqihtxlu5bvfaqxjyvqcob35a" style="color: black;">Proceedings of the 2004 ACM SIGKDD international conference on Knowledge discovery and data mining - KDD &#39;04</a> </i> &nbsp;
We show the generality of the weighted kernel k -means objective function, and derive the spectral clustering objective of normalized cut as a special case.  ...  Finally, we present results on several interesting data sets, including diametrical clustering of large geneexpression matrices and a handwriting recognition data set.  ...  Normalized Cuts In [13] , the authors consider the k -way normalized cut problem.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/1014052.1014118">doi:10.1145/1014052.1014118</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/kdd/DhillonGK04.html">dblp:conf/kdd/DhillonGK04</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/fr4t6zydqzhoxbavejilprg36u">fatcat:fr4t6zydqzhoxbavejilprg36u</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170809035633/http://www.stat.washington.edu/courses/stat539/spring13/Resources/dhillon-guan-kulis-kernel-spectral-normalized-2004.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/ca/bc/cabcb931385e08f7b79524e439d32edf68ad6589.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/1014052.1014118"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> acm.org </button> </a>
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