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Clustering of mixed-type data considering concept hierarchies: problem specification and algorithm
2020
International Journal of Data Science and Analytics
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In this paper, we introduce the algorithm ClicoT (CLustering mixed-type data Including COncept Trees) as reported by Behzadi et al. ...
Most clustering algorithms have been designed only for pure numerical or pure categorical data sets, while nowadays many applications generate mixed data. ...
Acknowledgements Open access funding provided by University of Vienna. ...
doi:10.1007/s41060-020-00216-2
fatcat:znwimvsqpzgffdqthjzxdjmqna
A Pattern-Hierarchy Classifier for Reduced Teaching
[article]
2020
arXiv
pre-print
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The upper level is a hierarchical tree, where nodes are linked through individual concepts, so there is a transition from mixed ensemble masses to specific categories. ...
One measure of success is how coherent these ensembles are, which means that every data row in the cluster belongs to the same category. ...
The upper level is a hierarchical tree, where each end node represents an individual DCS 20 October 2020 2 concept, so there is a transition from mixed ensemble masses to specific categories. ...
arXiv:1904.07786v3
fatcat:ony7ma5yhvfsddbnlstpk25afu
Granularity hierarchies
1992
Computers and Mathematics with Applications
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In particular, two types of granularity have been delineated: aggregation and abstraction. ...
We briefly discuss how we have used granularity hierarchies in the recognition of novice LISP programming strategies, and show how this enhances recognition and leads toward planning appropriate feedback ...
data). ...
doi:10.1016/0898-1221(92)90148-b
fatcat:ruvp7xwqfzgjvapjeangafzv4i
A Pattern-Hierarchy Classifier for Reduced Teaching
2020
WSEAS Transactions on Computers
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The upper level is a hierarchical tree, where nodes are linked through individual concepts, so there is a transition from mixed ensemble masses to specific categories. ...
One measure of success is how coherent these ensembles are, which means that every data row in the cluster belongs to the same category. ...
The upper level can be hierarchical, where each end node represents an individual concept, so there is a transition from mixed ensemble masses to specific categories. ...
doi:10.37394/23205.2020.19.23
fatcat:gmjlwan2wfd7fmljjrhfqj3bhi
Learning Unsupervised Hierarchies of Audio Concepts
[article]
2022
arXiv
pre-print
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Evaluations show that the mined hierarchies are aligned with both ground-truth hierarchies of concepts -- when available -- and with proxy sources of concept similarity in the general case. ...
For instance, music concepts are typically non-independent and of mixed nature (e.g. genre, instruments, mood), unlike previous work that assumed disentangled concepts. ...
We have filtered 3635 playlists of mixed types to be used as concepts: all 1498 editorial playlists available -considered thoughtfully curated but biased by popularity, and 2137 public user playlists with ...
arXiv:2207.11231v1
fatcat:mpeqzhg7cbhopngla5rf665kri
Learning Unsupervised Hierarchies of Audio Concepts
2022
Zenodo
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Evaluations show that the mined hierarchies are aligned with both ground-truth hierarchies of concepts -- when available -- and with proxy sources of concept similarity in the general case. ...
For instance, music concepts are typically non-independent and of mixed nature (e.g. genre, instruments, mood), unlike previous work that assumed disentangled concepts.We propose a method to learn numerous ...
We have filtered 3635 playlists of mixed types to be used as concepts: all 1498 editorial playlists available ± considered thoughtfully curated but biased by popularity, and 2137 public user playlists ...
doi:10.5281/zenodo.7316692
fatcat:3hrtv3e3cbbrllby7pzltkrlay
Incremental clustering of mixed data based on distance hierarchy
2008
Expert systems with applications
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The results show that the M-ART algorithm can process the mixed data and has a great effect on clustering. ...
Therefore, this paper proposes a modified adaptive resonance theory network (M-ART) and the conceptual hierarchy tree to solve similar degrees of mixed data. ...
Most of clustering algorithms consider either categorical data or numeric data. However, many mixed datasets including categorical and numeric values existed nowadays. ...
doi:10.1016/j.eswa.2007.08.049
fatcat:kvt6jgptvbbzfiqxylqchcoeem
HSC: A Novel Method for Clustering Hierarchies of Networked Data
[article]
2019
arXiv
pre-print
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2017 pre-print arXiv:1711.11071v1 fatcat:dvp4yfsewjgwzn4n6x3ddcuvme
Hierarchical clustering is one of the most powerful solutions to the problem of clustering, on the grounds that it performs a multi scale organization of the data. ...
Our method is based on the previous research of Meyer and Weissel Stochastic Data Clustering and the theory of Simon and Ando on Variable Aggregation. ...
Garofalakis for the assignment of the thesis and all the opportunities I have been given during our collaboration. Special thanks should be given to Dr. Athanasios N. ...
arXiv:1711.11071v2
fatcat:dz4eegkh2bhi3l7ru5pxrzts4u
Modified Adaptive Resonance Theory Network for Mixed Data Based on Distance Hierarchy
[chapter]
2006
Lecture Notes in Computer Science
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The results show that the M-ART algorithm can process the mixed data and has a great effect on clustering. ...
Therefore, this paper proposes a modified adaptive resonance theory network (M-ART) and the conceptual hierarchy tree to solve similar degrees of mixed data. ...
Most of clustering algorithms consider either categorical data or numeric data. However, many mixed datasets including categorical and numeric values existed nowadays. ...
doi:10.1007/11758549_102
fatcat:fh3nezaftvhftccmbk3ld3xwe4
Browsing Hierarchy Construction by Minimum Evolution
2015
ACM Transactions on Information Systems
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This problem derives from the polythetic nature of the features that clustering relies on to build the hierarchy. ...
We argue that clustering algorithms may not be the ideal solution for browsing hierarchy construction, for the following reasons: -Clustering often produces clusters with mixed initiatives. ...
Jamie Callan for in-depth discussions and editors and anonymous reviewers for their valuable comments. ...
doi:10.1145/2714574
fatcat:yveksypedjht3hdrjyiljkq434
Geometric constraints within feature hierarchies
2006
Computer-Aided Design
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We study the problem of enabling general 2D and 3D variational constraint representation to be used in conjunction with a feature hierarchy representation, where some of the features may use procedural ...
incorporation problem for DR-planners, clarify its relationship to other problems, and provide an efficient algorithmic solution. ...
Formal Problem Statement We now describe the algorithmic problem of feature incorporation in a DR-plan as an input-output specification. ...
doi:10.1016/j.cad.2005.05.001
fatcat:i6wiszp5srhnlf6u2dnxodvd4e
Programming the memory hierarchy revisited
2011
SIGPLAN notices
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We have implemented spawn and call-up in Sequoia and we present an experimental evaluation on a number of irregular applications. ...
We describe two novel constructs for programming parallel machines with multi-level memory hierarchies: call-up, which allows a child task to invoke computation on its parent, and spawn, which spawns a ...
Acknowledgments The authors would like to thank Evan Cox for his work on the implementation of Sequoia++, and the Department of Energy for access to the Cerillos supercomputer at Los Alamos National Labs ...
doi:10.1145/2038037.1941558
fatcat:artbk2glznaa5kyxnnnzknkl2u
Hierarchical Semi-supervised Classification with Incomplete Class Hierarchies
2016
Proceedings of the Ninth ACM International Conference on Web Search and Data Mining - WSDM '16
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In an entity classification task, topic or concept hierarchies are often incomplete. ...
We experimented with subsets of the NELL [8] ontology and text, and HTML table datasets derived from the ClueWeb09 corpus. ...
., consider a hierarchical entity classification task, with class hierarchy 'onto-1' shown in Figure 1 (left). There are 2 types of locations defined in it: 'State' and 'Country'. ...
doi:10.1145/2835776.2835810
dblp:conf/wsdm/DalviMC16
fatcat:tongeuchcrem3mky6uyuckikrm
Programming the memory hierarchy revisited
2011
Proceedings of the 16th ACM symposium on Principles and practice of parallel programming - PPoPP '11
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We have implemented spawn and call-up in Sequoia and we present an experimental evaluation on a number of irregular applications. ...
We describe two novel constructs for programming parallel machines with multi-level memory hierarchies: call-up, which allows a child task to invoke computation on its parent, and spawn, which spawns a ...
Acknowledgments The authors would like to thank Evan Cox for his work on the implementation of Sequoia++, and the Department of Energy for access to the Cerillos supercomputer at Los Alamos National Labs ...
doi:10.1145/1941553.1941558
dblp:conf/ppopp/BauerCSA11
fatcat:hvtzhdowfbd2xm3lo7gusnftzm
The Hierarchy of Block Models
[article]
2021
arXiv
pre-print
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There exist various types of network block models such as the Stochastic Block Model (SBM), the Degree Corrected Block Model (DCBM), and the Popularity Adjusted Block Model (PABM). ...
We propose a Nested Block Model (NBM) that treats the SBM, the DCBM and the PABM as its particular cases with specific parameter values, and, in addition, allows a multitude of versions that are more complicated ...
Specifically, we apply Algorithm 2 with k = K l and n = N l to cluster the l-th metacommunity, l = 1, ..., L. ...
arXiv:2002.02610v2
fatcat:j6ib7qcjrvdutkex6ckunw2hii
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