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Clustering Orders [chapter]

Toshihiro Kamishima, Jun Fujiki
2003 Lecture Notes in Computer Science  
We propose a method of using clustering techniques to partition a set of orders.  ...  We compared our method with the traditional clustering methods, and analyzed its characteristics.  ...  Clustering Orders In this section, we formalize a task of clustering orders.  ... 
doi:10.1007/978-3-540-39644-4_17 fatcat:cu3qe3yukrftpcig4nqdnavkbe

Variable Order Panel Clustering

Stefan Sauter
2000 Computing  
Furthermore, a variable order of approximation is used depending on the size of blocks.  ...  Note that the block cluster tree T (2) is fully determined by the cluster tree T.  ...  In this case, the order distribution m only depends on the level`. The variable order panel clustering algorithm In this section, we will de ne the panel clustering algorithm.  ... 
doi:10.1007/s006070050045 fatcat:ousibvvr5bfenjfvc5wvaksbfy

Ordering Effects in Clustering [chapter]

Douglas Fisher, Ling Xu, Nazih Zard
1992 Machine Learning Proceedings 1992  
Incremental systems often suffer from ordering effects: the knowledge structures that they form may vary with the presentation of objects.  ...  ORDERING EFFECTS Incremental clustering has some benefits from a data analysis standpoint.  ...  Dissimilarity ordering is one way to mitigate (or exploit) ordering effects. This procedure is external to the actual clustering algorithm.  ... 
doi:10.1016/b978-1-55860-247-2.50026-7 dblp:conf/icml/FisherXZ92 fatcat:bugebt374zhqpp6vdbeuyweeym

Efficient Clustering for Orders

Toshihiro Kamishima, Shotaro Akaho
2006 Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06)  
To cluster orders, hierarchical clustering methods have been used together with dissimilarities defined between pairs of orders.  ...  We therefore propose a new method (k-o'means-EBC), grounded on a theory of order statistics. We further propose several techniques to analyze acquired clusters of orders.  ...  Clustering Orders In this section, we formalize the task of clustering orders. We start by defining our basic notations regarding orders.  ... 
doi:10.1109/icdmw.2006.66 dblp:conf/icdm/KamishimaA06a fatcat:eto6m4wknncexjpeykf33o75zq

Order preserving hierarchical agglomerative clustering [article]

Daniel Bakkelund
2021 arXiv   pre-print
We study the problem of order preserving hierarchical clustering of this kind of ordered data.  ...  When compared to existing methods, the experiments show that our method excels both in cluster quality and order preservation.  ...  clustering of ordered sets.  ... 
arXiv:2004.12488v3 fatcat:mtj2kk4gcjcubimbdrwylki7ee

Clustering in ordered dissimilarity data

Timothy C. Havens, James C. Bezdek, James M. Keller, Mihail Popescu
2009 International Journal of Intelligent Systems  
D is reordered to D * using a visual assessment of cluster tendency algorithm.  ...  This paper presents a new technique for clustering either object or relational data. First, the data are represented as a matrix D of dissimilarity values.  ...  (second-order clusters).  ... 
doi:10.1002/int.20344 fatcat:t2qte53ul5edxdfsvks5lf6vgi

Local Higher-Order Graph Clustering

Hao Yin, Austin R. Benson, Jure Leskovec, David F. Gleich
2017 Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD '17  
Present work: Local higher-order clustering-In this paper we develop local algorithms for finding clusters of nodes based on higher-order network structures (also called network motifs, Figure 1 ).  ...  Second, it provides new avenues for higher-order structures to guide seeded graph clustering.  ...  Background on higher-order clustering coefficients-First, we introduce the definition of higher-order clustering coefficients proposed by Yin et. al [49] .  ... 
doi:10.1145/3097983.3098069 pmid:29770258 pmcid:PMC5951164 dblp:conf/kdd/YinBLG17 fatcat:logzwli35rfi5koy7r5puxiao4

Lexicographically Ordered Multi-Objective Clustering [article]

Sainyam Galhotra, Sandhya Saisubramanian, Shlomo Zilberstein
2019 arXiv   pre-print
We introduce a rich model for multi-objective clustering with lexicographic ordering over objectives and a slack.  ...  The makeshift fine tunes the clusters formed by the processed objectives so as to improve the clustering with respect to the unprocessed objectives, given the slack.  ...  Conclusion and Future Work We introduce the relaxed multi-objective clustering, a general model for clustering with multiple objectives, given a lexicographic order and slack.  ... 
arXiv:1903.00750v1 fatcat:s4kppyagjjdbhi75sq2fasunx4

Higher-order clustering in networks

Hao Yin, Austin R. Benson, Jure Leskovec
2018 Physical review. E  
Our higher-order clustering coefficients are a natural generalization of the traditional clustering coefficient.  ...  Here we introduce higher-order clustering coefficients that measure the closure probability of higher-order network cliques and provide a more comprehensive view of how the edges of complex networks cluster  ...  higher-order clustering coefficients describe local clustering in graphs.  ... 
doi:10.1103/physreve.97.052306 pmid:29906904 fatcat:z2gbqqx7c5egfa5ymdlqw5342m

Clustering with Feature Order Preferences [chapter]

Jun Sun, Wenbo Zhao, Jiangwei Xue, Zhiyong Shen, Yidong Shen
2008 Lecture Notes in Computer Science  
Our clustering formulation aims to incorporate feature order preferences into prototype-based clustering.  ...  We propose a clustering algorithm that effectively utilizes feature order preferences, which have the form that feature s is more important than feature t.  ...  . / Clustering with feature order preferences  ... 
doi:10.1007/978-3-540-89197-0_36 fatcat:iu2qa4md5vcwplatgywxef63mm

Cluster-Based Partial-Order Reduction

Twan Basten, Dragan Bošnački, Marc Geilen
2004 Automated Software Engineering : An International Journal  
Our technique tries to contain dependencies between actions within clusters of processes, capitalizing on the independence of actions in different clusters to reduce the state space to be verified while  ...  Partial-order reduction is a well-known technique to tackle this problem.  ...  The enhancement of partial-order reduction via process clustering fits with current trends in software engineering.  ... 
doi:10.1023/b:ause.0000038937.18006.3d fatcat:ri2wnanrandqdh4oklvz3r2vki

Coresets for Ordered Weighted Clustering [article]

Vladimir Braverman and Shaofeng H.-C. Jiang and Robert Krauthgamer and Xuan Wu
2019 arXiv   pre-print
We design coresets for Ordered k-Median, a generalization of classical clustering problems such as k-Median and k-Center, that offers a more flexible data analysis, like easily combining multiple objectives  ...  Its objective function is defined via the Ordered Weighted Averaging (OWA) paradigm of Yager (1988), where data points are weighted according to a predefined weight vector, but in order of their contribution  ...  The above coreset definition readily applies to ordered weighted clustering.  ... 
arXiv:1903.04351v1 fatcat:lx2y75xyzfgkdmvgrv2cmdtwky

Clusters from higher order correlations

L.S. Schulman
2010 Physics Letters A  
For two of them the 3^rd order correlations are significant for getting the clusters right.  ...  Given a set of variables and the correlations among them, we develop a method for finding clustering among the variables.  ...  Note the clustering involving 1-4-7, etc., a clustering that was evident when J alone was used. ("R"), and therefore can reflect information about long-range relations between the points.  ... 
doi:10.1016/j.physleta.2010.02.021 fatcat:gzn4q2jycvhlvkful2snsn5k64

An objective function for order preserving hierarchical clustering [article]

Daniel Bakkelund
2022 arXiv   pre-print
We present an objective function for similarity based hierarchical clustering of partially ordered data that preserves the partial order.  ...  That is, if x ≤ y, and if [x] and [y] are the respective clusters of x and y, then there is an order relation ≤' on the clusters for which [x] ≤' |y].  ...  And, while the constraints in clustering with constraints are provided, for example, by domain experts in order to adjust the clustering, the order relations used in order preserving hierarchical clustering  ... 
arXiv:2109.04266v3 fatcat:7g36k4tb4jfttlnz73qo3ezkru

Incremental Method for Spectral Clustering of Increasing Orders [article]

Pin-Yu Chen, Baichuan Zhang, Mohammad Al Hasan, Alfred O. Hero
2016 arXiv   pre-print
As a practical application, we consider user-guided spectral clustering.  ...  Consequently, the majority of the existing methods either choose K heuristically or they repeat the clustering method with different choices of K and accept the best clustering result.  ...  , in order to provide users with clustering information to stop the incremental computation process.  ... 
arXiv:1512.07349v4 fatcat:jzinqf357feftdrfcvjxwx72vi
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