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On goodness-of-fit measure for dendrogram-based analyses

ECOLOGY 2010年第6期91卷 1850-1859页

作者： Merigot, Bastien Durbec, Jean-Pierre Gaertner, Jean-Claude Univ Mediterranee Ctr Oceanol Marseille CNRS LMGEMUMR 6117 FR-13009 Marseille France

Clustering methods are widely used tools in many aspects of science, such as ecology, medicine, or even market research, that commonly deal with dendrogram-based analyses. In such analyses, for a given initial dissimilarity matrix, the resulting dendrogram may strongly vary according to the selected clustering methods. However, numerous dendrogram-based analyses require adequate measurement for assessing of which of the clustering methods preserves most faithfully the initial dissimilarity matrix. While cophenetic correlation coefficient-based measures have been widely used for this purpose, we emphasize here that it is not always a suitable approach. We thus propose a measure based on a matrix norm, the 2-norm, to adequately check which of the resulting ultrametric distance matrices related to the dendrograms is the closest to the initial dissimilarity matrix. In addition, we also propose an objective way to define a benchmark value (threshold value) in order to assess whether the degree of conformity between the ultrametric distance matrix selected and the initial dissimilarity matrix is satisfactory. Our proposal may notably be incorporated within a recently proposed approach that involves the use of clustering methods in environmental science and beyond. In ecology, various functional diversity indices based on clustering species from their functional dissimilarities may benefit from this overall approach.

关键词： clustering dendrogram functional classification functional diversity matrix norm

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GelClust: A software tool for gel electrophoresis images analysis and dendrogram generation

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COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2013年第2期111卷 512-518页

作者： Khakabimamaghani, Sahand Najafi, Ali Ranjbar, Reza Raam, Monireh Baqiyatallah Univ Med Sci Mol Biol Res Ctr Tehran Iran Univ Tehran Inst Biochem & Biophys Lab Syst Biol & Bioinformat LBB Tehran Iran

This paper presents GelClust, a new software that is designed for processing gel electrophoresis images and generating the corresponding phylogenetic trees. Unlike the most of commercial and non-commercial related softwares, we found that GelClust is very user-friendly and guides the user from image toward dendrogram through seven simple steps. Furthermore, the software, which is implemented in C# programming language under Windows operating system, is more accurate than similar software regarding image processing and is the only software able to detect and correct gel 'smile' effects completely automatically. These claims are supported with experiments. (C) 2013 Elsevier Ireland Ltd. All rights reserved.

关键词： Gel electrophoresis images Image processing dendrogram Software Phylogenetic trees

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dendrogram Based Algorithm for Dominated Graph Flooding

Dendrogram Based Algorithm for Dominated Graph Flooding

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14th Annual International Conference on Computational Science

作者： Tadonki, Claude Meyer, Fernand Irigoin, Francois Mines ParisTech CRI 35 Rue St Honore F-77305 Fontainebleau France Mines ParisTech Ctr Morphol Math F-77305 Fontainebleau France

In this paper, we are concerned with the problem of flooding undirected weighted graphs under ceiling constraints. We provide a new algorithm based on a hierarchical structure called dendrogram, which offers the significant advantage that it can be used for multiple flooding with various scenarios of the ceiling values. In addition, when exploring the graph through its dendrogram structure in order to calculate the flooding levels, independent sub-dendrograms are generated, thus offering a natural way for parallel processing. We provide an efficient implementation of our algorithm through suitable data structures and optimal organisation of the computations. Experimental results show that our algorithm outperforms well established classical algorithms, and reveal that the cost of building the dendrogram highly predominates over the total running time, thus validating both the efficiency and the hallmark of our method. Moreover, we exploit the potential parallelism exposed by the flooding procedure to design a multi-thread implementation. As the underlying parallelism is created on the fly, we use a queue to store the list of the sub-dendrograms to be explored, and then use a cyclic distribution to assign them to the participating threads. This yields a load balanced and scalable process as shown by additional benchmark results. Our program runs in few seconds on an ordinary computer to flood graphs with more that 20 millions of nodes.

关键词： graph flooding complexity dendrogram data structure multicore

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dendrogram Seriation Using Simulated Annealing

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Information Visualization 2003年第2期2卷 95-104页

作者： Morris, Steven A. Asnake, Benyam Yen, Gary G. Electrical and Computer Engineering Oklahoma State University Stillwater OK 202 Engineering So. United States

Seriation is the ordering of the leaves of a dendrogram, such that leaves representing similar items are placed near each other according to some metric, within the constraints of the cluster tree. Such ordering greatly aids the interpretation of the relations represented by the dendrogram and reduces visual misinterpretation caused by unrelated items from different sub-trees being placed near each other during random ordering. The seriation method presented here uses simulated annealing to find an approximately optimal dendrogram ordering by minimizing a penalty function. The method employs a ‘similarity weighted distance’ penalty function that tends to avoid artifacts introduced by the traveling salesman problem algorithms commonly used for dendrogram seriation. Examples are given showing the effectiveness of the method in presenting dendrograms of the structure of a social network, and additional examples show an application for interpreting the structure of a network of journal papers covering the subject of anthrax research. © 2003, SAGE Publications. All rights reserved.

关键词： bibliometrics dendrogram seriation simulated annealing social networks visualization

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A fast shape retrieval algorithm based on dendrogram

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Journal of Convergence Information Technology 2012年第16期7卷 126-133页

作者： Shin, Jungpil Kikugawa, Michikazu Graduate School of Computer Science and Engineering The University of Aizu Fukushima Japan

A lot of image data has been digitized and preserved in computers. In order to search for an image, an efficient and accurate retrieval method is needed. This paper is concerned with shape retrieval which is one of the searching methods for finding similar images in a database. Shape, the outer form of a picture, is considered the most promising feature to identify entities in an image. The problem of shape retrieval takes a lot of time because an exhaustive search is mainly used in literatures. This paper suggests the use of a clustering method known as dendrogram for shape retrieval. In addition, we proposed the automatic decision of a threshold to determine a number of clusters in dendrogram. Through the experimental result, the proposed method proved fast retrieval preserving almost the same level accuracy.

关键词： Shape Retrieval dendrogram DP Matching

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A robust method for malware analysis using stacking classifiers and dendrogram visualization

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International Journal of Information Technology (Singapore) 2024年 1-16页

作者： Naveen Kumar, N. Balamurugan, S. Maruthamuthu, R. Devi, P.P. Seshu Kumar, P. Department of Computer Applications Madanapalle Institute of Technology & amp Science Andhra Pradesh Madanapalle India Department of Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R & amp D Institute of Science and Technology Avadi Tamil Nadu Chennai India

Malware analysis is a vital and challenging task in the ever-changing cyber threat landscape. Traditional signature-based methods cannot keep up with the fast-paced evolution of malware variants. This underscores the need for developing a more effective malware classification tool helping in exploring new research directions with solutions. In this research work firstly, we present a comprehensive assessment on malware classification using dendrogram clustering techniques. This work proposes, a robust approach to malware analysis by constructing dendrogram that groups malware samples which works based on their ancestral relationships. Semantic analysis of the code also provides deeper insights into the malware’s behavior and functionality, enabling more precise identification. These methods help to detect new variants as well as enhance the recognition of existing malware families. Our proposed model results shows that, the robustness in accuracy and False Positive Rate when compared with other existing models. © Bharati Vidyapeeth's Institute of Computer Applications and Management 2024.

关键词： Autoencoder decoder dendrogram Malware classification Semantic analysis

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Faster image dendrogram creation: An efficient algorithm for the detection of tumours in digital mammography

Faster image dendrogram creation: An efficient algorithm for...

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25th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society

作者： Mitchell, RA Nguyen, HT Thornton, BS Hung, WT Lee, W Rickard, M Univ Technol Sydney Key Univ Res Ctr Hlth Technol Sydney NSW 2007 Australia

ISBN: (纸本)0780377893

Dendronic image analysis has been shown to provide a robust technique in the detection of tumours within digital mammograms. It provides the capability of fully automated image analysis through hierarchical segmentation. However, its general acceptance in image analysis has not been realised due to computational intensity in creating the image dendrogram. We have developed an efficient technique that can create image dendrograms a great deal faster than traditional repetitive segmentation algorithms, making dendronic analysis of digital mammograms a viable tool in the detection of breast cancer.

关键词： mammogram dendrogram segmentation

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3rd International Conference on Information Technology - New Generations (ITNG)

作者： Hashemi, Ray R. Tyler, Alexander A. Childers, Chris Chausmer, Arthur Armstrong State Coll Dept Comp Sci 11935 Abercorn St Savannah GA 31419 USA Cork Univ Hosp Cork Ireland Moanalua Med Ctr Dept Endocrinol Honolulu HI 96819 USA

ISBN: (纸本)0769524974

Bone mineral density (BMD) measurements are the gold standard by which osteoporosis is diagnosed. Dual Energy X-ray Absorptiometry (DEXA) is the most commonly used measuring technique to assess BMD at both the hip and spine. There are three sites within each hip, collectively called the femoral sites, which are assessed-the femoral neck site, the trochanteric site, and Ward's triangle. It is a known fact that the different areas of the femur are composed of different percentages of cancellous bone. The null hypothesis that we examine in this paper is that there is no difference between the mineralization states at all of these sites. To do so, we introduce and present a dendrogram-based methodology that (1) identifies valid clusters for any two given subsets of the six sites, (2) uses the valid clusters to examine the existence of associations between the two subsets, and (3) the existence of association, if any, is measured by the degree of similarity between the two subsets. The obtained results in this research effort partially reject the null hypothesis.

关键词： dendrogram Valid dendrogram Similarity Analysis Degree of Similarity bone mineral density and Dual Energy X-ray Absorptiometry

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Mining Arbitrary Shaped Clusters and Outputting a High Quality dendrogram 27th

Mining Arbitrary Shaped Clusters and Outputting a High Quali...

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1st International Workshop on Consistency and Inconsistency (COIN) at 27th International Conference on Database and Expert Systems Applications (DEXA)

作者： Huang, Hao Wang, Song Wu, Shuangke Gao, Yunjun Lu, Wei He, Qinming Ying, Shi Wuhan Univ State Key Lab Software Engn Wuhan Peoples R China Zhejiang Univ Coll Comp Sci Hangzhou Zhejiang Peoples R China Renmin Univ China MOE Key Lab Data Engn & Knowledge Engn Beijing Peoples R China

ISBN: (纸本)9783319444031;9783319444024

Hierarchical clustering (HC for short) outputs a dendrogram that offers more topological information than flat clustering(e.g., k-means). However, the existing HC algorithms focus on either the quality of the dendrogram or the ability of mining arbitrary shaped clusters. To address the above two aspects simultaneously, we present HICMEN by adopting (1) the classic agglomerative clustering framework that can generate a complete dendrogram, and (2) a novel similarity measure based on mutual k-nearest neighbors to capture the connectivity of data points and help properly merge up each arbitrary shaped cluster piece by piece. More importantly, we prove that the similarity measure has a nice property called weak monotonicity, which guarantees the quality of the dendrogram generated by HICMEN. Extensive experimental results show that HICMEN is capable of mining arbitrary shaped clusters effectively, and can simultaneously output a high quality dendrogram.

关键词： Clustering Arbitrary shaped clusters dendrogram

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dendrogram Based Algorithm for Dominated Graph Flooding

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Procedia Computer Science 2014年 29卷 586-598页

作者： Claude Tadonki Fernand Meyer François Irigoin Mines ParisTech - Centre de Recherche en Informatique (CRI) 35 rue Saint-Honoré 77305 Fontainebleau Cedex Mines ParisTech - Centre de Morphologie Mathématique (CMM) 35 rue Saint-Honoré 77305 Fontainebleau Cedex

In this paper, we are concerned with the problem of flooding undirected weighted graphs un- der ceiling constraints. We provide a new algorithm based on a hierarchical structure called dendrogram , which offers the significant advantage that it can be used for multiple flooding with various scenarios of the ceiling values. In addition, when exploring the graph through its dendrogram structure in order to calculate the flooding levels, independent sub-dendrograms are generated, thus offering a natural way for parallel processing. We provide an efficient im- plementation of our algorithm through suitable data structures and optimal organisation of the computations. Experimental results show that our algorithm outperforms well established classical algorithms, and reveal that the cost of building the dendrogram highly predominates over the total running time, thus validating both the efficiency and the hallmark of our method. Moreover, we exploit the potential parallelism exposed by the flooding procedure to design a multi-thread implementation. As the underlying parallelism is created on the fly, we use a queue to store the list of the sub-dendrograms to be explored, and then use a cyclic distribution to assign them to the participating threads. This yields a load balanced and scalable process as shown by additional benchmark results. Our program runs in few seconds on an ordinary computer to flood graphs with more that 20 millions of nodes.

关键词： graph flooding complexity dendrogram data structure multicore

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