Hierarchical Clustering of Composite Objects with a Variable Number of Components

نویسندگان

  • Alain Ketterlin
  • Pierre Gançarski
  • Jerzy J. Korczak
چکیده

This paper examines the problem of clustering a sequence of objects that cannot be described with a predeened list of attributes (or variables). In many applications, such a crisp representation cannot be determined. An extension of the traditionnal propositionnal formalism is thus proposed, which allows objects to be represented as a set of components. The algorithm used for clustering is brieey illustrated, and mechanisms to handle sets are described. Some empirical evaluations are also provided, to assess the validity of the approach.

برای دانلود 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

Choosing the Best Hierarchical Clustering Technique Based on Principal Components Analysis for Suspended Sediment Load Estimation

1- INTRODUCTION The assessment of watershed sediment load is necessary for controling soil erosion and reducing the potential of sediment production. Different estimates of sediment amounts along with the lack of long-term measurements limits the accessibility to reliable data series of erosion rate and sediment yield. Therefore, the observed data of suspended sediment load could be used to ...

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

روش نوین خوشه‌بندی ترکیبی با استفاده از سیستم ایمنی مصنوعی و سلسله مراتبی

Artificial immune system (AIS) is one of the most meta-heuristic algorithms to solve complex problems. With a large number of data, creating a rapid decision and stable results are the most challenging tasks due to the rapid variation in real world. Clustering technique is a possible solution for overcoming these problems. The goal of clustering analysis is to group similar objects. AIS algor...

متن کامل

Robust Method for E-Maximization and Hierarchical Clustering of Image Classification

We developed a new semi-supervised EM-like algorithm that is given the set of objects present in eachtraining image, but does not know which regions correspond to which objects. We have tested thealgorithm on a dataset of 860 hand-labeled color images using only color and texture features, and theresults show that our EM variant is able to break the symmetry in the initial solution. We compared...

متن کامل

Hierarchical Model-Based Clustering for Relational Data

Relational data mining deals with datasets containing multiple types of objects and relationships that are presented in relational formats, e.g. relational databases that have multiple tables. This paper proposes a propositional hierarchical model-based method for clustering relational data. We first define an object-relational star schema to model composite objects, and present a method of fla...

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

برای دانلود 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

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 1995