منابع مشابه
A Technique for Improving Web Mining using Enhanced Genetic Algorithm
World Wide Web is growing at a very fast pace and makes a lot of information available to the public. Search engines used conventional methods to retrieve information on the Web; however, the search results of these engines are still able to be refined and their accuracy is not high enough. One of the methods for web mining is evolutionary algorithms which search according to the user interests...
متن کاملLow-complexity fuzzy relational clustering algorithms for Web mining
This paper presents new algorithms (Fuzzy c-Medoids or FCMdd and Robust Fuzzy c-Medoids or RFCMdd) for fuzzy clustering of relational data. The objective functions are based on selecting c representative objects (medoids) from the data set in such a way that the total fuzzy dissimilarity within each cluster is minimized. A comparison of FCMdd with the well-known Relational Fuzzy c-Means algorit...
متن کاملAn Effective fuzzy Clustering Algorithm for Web Document Classification: a Case Study in Cultural Content Mining
This article presents a novel crawling and clustering method for extracting and processing cultural data from the web in a fully automated fashion. Our architecture relies upon a ‘focused’ web crawler to download web documents relevant to culture. The term ‘focused crawler’ refers to web crawlers that search and process only those web pages that are relevant to a particular topic. After downloa...
متن کاملA Scalable Hierarchical Fuzzy Clustering Algorithm for Text Mining
Clustering techniques are generally applied for finding unobvious relations and structures in data sets. In this paper, we propose a novel scalable hierarchical fuzzy clustering algorithm to discover relationships between information resources based on their textual content, as well as to represent knowledge through the association of topics covered by those resources. The algorithm addresses t...
متن کاملA Fuzzy C-means Algorithm for Clustering Fuzzy Data and Its Application in Clustering Incomplete Data
The fuzzy c-means clustering algorithm is a useful tool for clustering; but it is convenient only for crisp complete data. In this article, an enhancement of the algorithm is proposed which is suitable for clustering trapezoidal fuzzy data. A linear ranking function is used to define a distance for trapezoidal fuzzy data. Then, as an application, a method based on the proposed algorithm is pres...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Korean Institute of Intelligent Systems
سال: 2002
ISSN: 1976-9172
DOI: 10.5391/jkiis.2002.12.3.219