Parallel Algorithms for Hierarchical Clustering and Applications to Split Decomposition and Parity Graph Recognition

نویسنده

  • Elias Dahlhaus
چکیده

Ž . We present efficient parallel algorithms for two hierarchical clustering heuristics. We point out that these heuristics can also be applied to solving some algorithmic problems in graphs, including split decomposition. We show that efficient parallel split decomposition induces an efficient parallel parity graph recognition algorithm. This is a consequence of the result of S. Cicerone and D. Di w x Stefano 7 that parity graphs are exactly those graphs that can be split decomposed into cliques and bipartite graphs. Q 2000 Academic Press

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Angewandte Mathematik Und Informatik Universit at Zu K Oln Parallel Algorithms for Hierarchical Clustering and Applications to Split Decomposition and Parity Graph Recognition

We present eecient (parallel) algorithms for two hierarchical clustering heuristics. We point out that these heuristics can also be applied to solve some algorithmic problems in graphs. This includes split decomposition. We show that eecient parallel split decomposition induces an eecient parallel parity graph recognition algorithm. This is a consequence of the result of 7] that parity graphs a...

متن کامل

Graph Clustering by Hierarchical Singular Value Decomposition with Selectable Range for Number of Clusters Members

Graphs have so many applications in real world problems. When we deal with huge volume of data, analyzing data is difficult or sometimes impossible. In big data problems, clustering data is a useful tool for data analysis. Singular value decomposition(SVD) is one of the best algorithms for clustering graph but we do not have any choice to select the number of clusters and the number of members ...

متن کامل

A partition-based algorithm for clustering large-scale software systems

Clustering techniques are used to extract the structure of software for understanding, maintaining, and refactoring. In the literature, most of the proposed approaches for software clustering are divided into hierarchical algorithms and search-based techniques. In the former, clustering is a process of merging (splitting) similar (non-similar) clusters. These techniques suffered from the drawba...

متن کامل

On the Extension of Bipartite to Parity Graphs

Parity graphs form a superclass of bipartite and distance-hereditary graphs. Since their introduction, all the algorithms proposed as solutions to the recognition problem and other combinatorial problems exploit the structural property of these graphs described by Burlet and Uhry in [8]. This paper introduces a different structural property of parity graphs: split decomposition returns exactly,...

متن کامل

Assessment of the Performance of Clustering Algorithms in the Extraction of Similar Trajectories

In recent years, the tremendous and increasing growth of spatial trajectory data and the necessity of processing and extraction of useful information and meaningful patterns have led to the fact that many researchers have been attracted to the field of spatio-temporal trajectory clustering. The process and analysis of these trajectories have resulted in the extraction of useful information whic...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:
  • J. Algorithms

دوره 36  شماره 

صفحات  -

تاریخ انتشار 2000