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The most important task of clustering process is the validation of results obtained from clustering algorithms. There are many cluster validation criteria's but the most commonly used approaches are founded on internal validity indices. There are numerous indices that have been suggested from time to time but there are only some of them that have been popularly used. In this paper we have drawn a...
In previous works of ours [1-3], we proposed a neural network-based face detection and facial expression analysis system, which was able to classify three expressions in frontal view face images. In the present work, we examine the possibility of classifying these expressions in side view face images. Specifically, we evaluate the extracted facial feature discrimination power of three image acquisition...
Nowadays, client likes to take suggestions before spending on a new product. For this they go to online item review webpage for perusing other's encounters and saying for that item. A real issue which was disregarded so far is the investigation of review spammers. However, numerous scientists gave their productive commitment in this field of exploration from 2007. The situation now asks for, conspicuous...
Classification is the category that consists of identification of class labels of records that are typically described by set of features in dataset. The paper describes a system that uses a set of data pre-processing activities which includes Feature Selection and Discretization. Feature selection and dimension reduction are common data mining approaches in large datasets. Here the high data dimensionality...
Online social network has obtained a significant increase in recent years. Making friends is a way of creating social relationships with others in online social network to be in contact with their friends in the real world and to have access to the information they are interested in. Therefore friend recommendation is becoming a very important aspect and attracting extensive attention in visual communities...
Today there is huge amount of data available on World Wide Web. One way to manage data is web page classification. One of the issues of web page classification considered in this paper is high dimensionality. Dimensionality refers to number of terms in a web page. High dimensionality of web pages causes problem while classifying them. The main objective of reducing dimensionality of web pages is to...
In this paper, a study of the problem of shopping center layout design is presented. Assignment of shops to locations in a shopping center should be performed in a way that ensures balance in the distribution of flow across all shopping center areas. This can lead to the success of the shopping center, and consequently raise its rent return. This study proposes a facility layout assignment model for...
Due to ever growing demand for the Internet resources, the Internet is facing ossification problem. Network virtualization is a promising way of supporting multiple heterogeneous networks onto a single substrate physical network offering solution to the problem. However, embedding Virtual Networks (VN) on a Substrate Network (SN) meeting the resource requirements of VNs and resource constraints of...
Discovering the hidden knowledge from large volume of educational data and applying it properly for decision making is essential for ensuring high quality education in any academic institution. This knowledge is extractable through data mining techniques. Association Rule Mining technique aims at discovering implicative tendencies that can provide valuable information for the decision maker. In this...
Intrusion Detection System (IDS) is a software or hardware tool that repeatedly scans and monitors events that took place in a computer or a network. A set of rules are used by Signature based Network Intrusion Detection Systems (NIDS) to detect hostile traffic in network segments or packets, which are so important in detecting malicious and anomalous behavior over the network like known attacks that...
People rely on data mining techniques like text categorization more and more to explore valuable information, due to the ever-increasing electronic documents produced. Although the energy consumed by text categorization increases with the data, people usually pay attention to its effectiveness and there is little research about its energy cost. In this paper, we evaluate the energy cost of different...
Intrusion detection is the problem of identifying unauthorized use, misuse, and abuse of computer systems or network resources by both system insiders and external penetrators. The proliferation of heterogeneous computer networks provides additional implications for the intrusion detection problem. The increased connectivity of computer systems gives greater access to outsiders, and makes it easier...
This paper proposes a method for simulating human opinions about graphical artistic expressions like calligraphy using computers. Scanned images of handwriting texts from a large database are labeled as "beautiful writing" or "ugly writing" by two persons based on their own likes. Our objective is to replicate these opinions using machine learning techniques. Shape features are...
Imbalanced data-set Classification has become a hotspot problem in Data Mining. The essential assumption of the traditional classification algorithms is that the distribution of the classes is balanced, therefore the algorithms used in Imbalanced data-set Classification cannot achieve an ideal effect. In view of imbalance date-set classification, we propose an over sampling method based on support...
In this paper is presented a solution based on a bi-dimensional cellular automata (CA) for image density classification task (DCT). The two necessary properties: density preserving and translation are combined together to obtain the DCT solution. These two properties are achieved using a combination of nine fundamental 2D-CA rules and the proposed solution for DCT has two phases: preprocessing phase...
The exponential growth of the data may lead us to the information explosion era, an era where most of the data cannot be managed easily. Text mining study is believed to prevent the world from entering that era. One of the text mining studies that may prevent the explosion era is text classification. It is a way to classify articles into several predefined categories. In this research, the classifier...
In artificial intelligence field, dynamic optimization problem under uncertain environment has always been a main topic and been widely researched these years. How to find the optimal solution around the goals to be solved is the key problem. As a typical case of uncertainty environment, maze has an important research value. In this paper we design a complex maze of random scene simulation system...
We introduce a novel algorithm to detect unknown attacks, based on the Communicating Ant for Clustering (CAC) [1], which despite the other ants algorithm, lead to a better detection rate (DR). Secondly, having noted the low DR of R2L attacks, we improve this approach by hybridizing it with association rules approach. In addition to the measure of similarity calculated using continuous attributes of...
Nowadays, the web is the most relevant data source. Its size does not stop growing day by day. Web page classification becomes crucial due to this overwhelming amount of data. Web pages contain many noisy contents that bias textual classifiers and lead them to lose focus on their main subject. Web pages are related to each other either implicitly by users' intuitive judgments or explicitly by hyperlinks...
This paper proposes an artificial intelligence algorithm that uses the k-nearest neighbor algorithm to predict its opponent's attack action and a game simulator to deduce a countermeasure action for controlling an in-game character in a fighting game. This AI algorithm (AI) aims at achieving good results in the fighting-game AI competition having been organized by our laboratory since 2013. It is...
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