نتایج جستجو برای: fuzzy mining

تعداد نتایج: 174051  

2013
T. VIJAYA

Web Usage Mining is the application of data mining techniques to learn usage patterns from Web server log file in order to understand and better serve the requirements of web based applications. Web Usage Mining includes three most important steps namely Data Preprocessing, Pattern discovery and Analysis of the discovered patterns. One of the most important tasks in Web usage mining is to find ...

Journal: :CoRR 2013
Hossein Rashmanlou Madhumangal Pal

Concepts of graph theory have applications in many areas of computer science including data mining, image segmentation, clustering, image capturing, networks, etc . An interval-valued fuzzy set is a generalization of the notion of a fuzzy set. Interval-valued fuzzy models give more precision, flexibility and compatibility to the system as compared to the fuzzy models. In this paper, we introduc...

2007
Zengchang Qin Jonathan Lawry

Generally, there are two main streams of theories for studying uncertainties. One is probability theory and the other is fuzzy set theory. One of the basic ideas of fuzzy set theory is how to define and interpret membership functions. In this paper, we will study tree-structured data mining model based on a new interpretation of fuzzy theory. In this new theory, fuzzy labels will be used for mo...

Journal: :international journal of information, security and systems management 0

text classification is an important research field in information retrieval and text mining. the main task in text classification is to assign text documents in predefined categories based on documents’ contents and labeled-training samples. since word detection is a difficult and time consuming task in persian language, bayesian text classifier is an appropriate approach to deal with different...

2011
J Vellingiri

World Wide Web is a huge repository of web pages and links. It provides abundance information for the Internet users. The growth of web is incredible as it can be seen in present days. Users’ accesses are recorded in web logs. From the user’s perspective, it is very difficult to extract useful knowledge from the huge amount of information and secondly, it is also difficult to extract for the us...

2014
Nadejda Yarushkina Tatiana Afanasieva Irina Timina

The article is devoted to the problem of applying the formal data mining tool – forecasting – for the developing of new software and for reengineering the present software. We propose the algorithm adjustments of the time series forecasting. This algorithm takes into account the dependence of the current state of time series from the previous one, the influence of basic fuzzy projected trends i...

Journal: :Knowl.-Based Syst. 2013
Stephen G. Matthews Mario A. Góngora Adrian A. Hopgood Samad Ahmadi

In Web usage mining, fuzzy association rules that have a temporal property can provide useful knowledge about when associations occur. However, there is a problem with traditional temporal fuzzy association rule mining algorithms. Some rules occur at the intersection of fuzzy sets’ boundaries where there is less support (lower membership), so the rules are lost. A genetic algorithm (GA)-based s...

Journal: :Soft Comput. 2012
José Manuel Cadenas M. Carmen Garrido Raquel Martínez Piero P. Bonissone

The discretization of values plays a critical role in data mining and knowledge discovery. The representation of information through intervals is more concise and easier to understand at certain levels of knowledge than the representation by mean continuous values. In this paper, we propose a method for discretizing continuous attributes by means of a series of fuzzy sets, which constitutes a f...

2016
Kamaldeep Kaur Navjot Kaur

This paper describes a hybrid approach of Fuzzy C-means clustering and Genetic Algorithm (GA) is proposed that provides better accuracy & increases the intrusion detection rate. This approach provides better accuracy of detection as compared to K-means and FCM Clustering. With this proposed approach intrusion detection rate is improved considerably.A brief overview of a hybrid approach of genet...

2009
Roy Gelbard Avichai Meged

Representing and consequently processing fuzzy data in standard and binary databases is problematic. The problem is further amplified in binary databases where continuous data is represented by means of discrete ‘1’ and ‘0’ bits. As regards classification, the problem becomes even more acute. In these cases, we may want to group objects based on some fuzzy attributes, but unfortunately, an appr...

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