Comparison of Cluster Algorithms for the Analysis of Text Data Using Kolmogorov Complexity
نویسندگان
چکیده
In this paper we present a comparison of multiple cluster algorithms and their suitability for clustering text data. The clustering is based on similarities only, employing the Kolmogorov complexity as a similiarity measure. This motivates the set of considered clustering algorithms which take into account the similarity between objects exclusively. Compared cluster algorithms are Median kMeans, Median Neural Gas, Relational Neural Gas, Spectral Clustering and Affinity Propagation. keywords: cluster algorithm, similarity data, neural gas, spectral clustering, message passing, kMeans, Kolmogorov complexity
منابع مشابه
Designing a System for Trend Analysis of Users in Website Surfing in Iran Using Data Mining and Text Mining Algorithms
Background and Aim: As of the entrance of web surfing to the lifestyle of a vast majority of people in the society and the need for a more accurate social and cultural policy making in the field, authors intended to analyze the behavior of the society users in viewing different websites so as to help politicians and practitioners. Methods: Design science research method is used in this research...
متن کاملGraph 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 کاملMulti-layer Clustering Topology Design in Densely Deployed Wireless Sensor Network using Evolutionary Algorithms
Due to the resource constraint and dynamic parameters, reducing energy consumption became the most important issues of wireless sensor networks topology design. All proposed hierarchy methods cluster a WSN in different cluster layers in one step of evolutionary algorithm usage with complicated parameters which may lead to reducing efficiency and performance. In fact, in WSNs topology, increasin...
متن کاملIntrinsic Plagiarism Detection using Complexity Analysis
We introduce Kolmogorov Complexity measures as a way of extracting structural information from texts for Intrinsic Plagiarism Detection. Kolmogorov complexity measures have been used as features in a variety of machine learning tasks including image recognition, radar signal classification, EEG classification, DNA analysis, speech recognition and some text classification tasks (Chi and Kong, 19...
متن کاملAssessment 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