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Now-a-days privacy has become a major concern; the goals of security like confidentiality, integrity and availability do not ensure privacy. Data mining is a threat to privacy. Researchers today focus on how to ensure privacy while performing data mining task. As Data mining algorithms are typically complex and furthermore the input usually consists of massive data sets, the generic protocols in such...
Considerable progress has been made towards automatic support for one of the principal techniques available to enhance program reliability: equipping programs with extensive contracts. The results of current contract inference tools are still often unsatisfactory in practice, especially for programmers who already apply some kind of basic Design by Contract discipline, since the inferred contracts...
This paper examines a correlation between Croatian equity index CROBEX's value change and Croatian open investment funds share price change by applying data mining techniques. Apart from the type of the fund, in consideration is taken the fact how much funds invest in Croatian equities that is the equities which rate on Zagreb Stock Exchange. While working, the problem was observed in two aspects,...
With high spatial resolution, SPOT5 satellite imagery contains rich texture information, such as geometry and color texture which embodies the details of object surfaces by changing the hue or brightness. However, traditional statistical classification technology based on the spectrum of pixels couldn't make full use of the texture information of SPOT5 satellite imagery because SPOT5-XS imagery only...
In traditional P2P networks, such as Gnutella, peers propagate query messages towards the resource holders by flooding them through the network. However, it is a costly operation since it consumes node and link resources excessively, which are often unnecessarily. There is no reason, for example, for a peer to receive a query message if the peer has no matching resource or is not on the path to a...
Linguistic interface is a group of linguistic terms or fuzzy descriptions that describe variables in a system utilizing corresponding membership functions. Its transparency completely or partly decides the interpretability of fuzzy models. This paper proposes a GRadiEnt-descEnt-based Transparent lInguistic iNterface Generation (GREETING) approach to overcome the disadvantage of traditional linguistic...
Data mining in large databases is one of today's challenges to database technologies. Substantial effort is dedicated to a tight coupling of database and data mining systems leading to database primitives supporting data mining tasks. In order to support a wide range of tasks. In this paper, we describe an algorithm for applying decision tree. Based on the analysis of available algorithms and previous...
This paper presents an analysis of teaching quality improvement in college English language teaching using data mining for developing quality improvement strategies. Based on 1132 survey samples that were collected from a certain grade students during the period from April to June 2008, important factors impacting the teaching quality were identified via the decision tree method for data mining. Findings...
In order to support more value-added services and a larger space for IP addresses, the Internet requries to classify IPv6 packets into flows for specific requirements. High performance IPv6 packet classification (PC) algorithms are therefore in high demand. This paper proposes a new IPv6 PC algorithm based on flow label (FL), called FLIN (Flow Label Initial Noticed). FLIN is fast and scalable with...
This paper presents an information system security evaluation model referring to Common criteria (CC). Analytic Hierarchy Process (AHP) and Grey Relational Analytic Process (GRAP) are applied to this model which combines the qualitative evaluation with the quantitative decision. AHP is used to obtain the indices' weights with respect to the final goal of the security evaluation. GRAP is adapted to...
This work presents a new process for building comprehensible fuzzy systems for classification problems. Firstly, a feature selection procedure based on crisp decision trees is carried out. Secondly, strong fuzzy partitions are generated for all the selected inputs. Thirdly, a set of linguistic rules are defined combining the previously generated linguistic variables. Then, a linguistic simplification...
This paper addresses the decision trees induction with uncertain data. In other words, it presents a novel method, called uncertain decision trees (UDT) to handle the uncertainty during the process of inducing decision trees. Here, uncertainty is depicted via cloud model theory, a quantitative-qualitative transforming model with uncertainty, which can well integrate the fuzziness and randomness of...
This paper improves a method of sample selection based on maximum entropy. Compared with the original method, the improved one takes the probability distribution of unlabeled instances into consideration. It selects the instances which can reduce the uncertainty of the whole unlabeled set to a great extent. The uncertainty reduction of the whole unlabeled set caused by an instance is measured by the...
Unstable angina (UA) is now a severe burden on society and family in both industrialized and developing countries, but the traditional related factors can not explain the whole situations. The effect of treatment is very limited. Determination of treatment based on the symptoms and signs in Traditional Chinese Medicine (TCM) have certain curative effect. But the objective of the syndrome diagnose...
In view of the high operation cost of Gini index for SLIQ algorithm while searching the optimal split scheme, and from the objective distribution of data, the thesis introduces the concept of density of data distribution. The new SLIQ algorithm, improved on the base of Gini index, is adopted in synthetic evaluation. The results in the example demonstrate that the number of the Gini index is reduced...
How to utilize a variety of derivatives so as to obtain positive investment return in different economies concerns the general investors. The present research utilizes a modified APRIORI algorithm called Multi-Dimension Non-Continuous (MDNC), an algorithm by eliminating the limitations imposed by traditional pattern matching of continuous data, to mine the associated rules in the cross-day discrete...
In this paper, we present an efficient and accurate decision tree building method which resolves some problems and reduces the overhead of database scanning in the CAM method. We also build a structure named class-rooted FP-tree. From our simulation, we show that the performance of the proposed class-rooted FP-tree mining method is better than the CAM methods in terms of storage usage, the times of...
Decision tree classification techniques have been used for a wide range of classification problems and becoming an increasingly important tool for classification of remotely sensed data. These techniques have substantial advantages for land use classification problems because of the reflexibility, nonparametric nature, and ability to handle non-linear relations between features and classes. In this...
The article proposes the concept of diagnosing the intuitive skills of the management staff in an enterprise with the use of the expert system. It determines the significance of intuition in management and presents methods of intuitive skills evaluation. The AIM Survey and the rules of using it are included in the study. Moreover, it describes the rules of creating knowledge bases enabling the evaluation...
As the rapid development of economy, increased population and lagged water conservancy, a series of civic ecological environment problems have arisen, for example, water shortage, water pollution, ecological deteriorate, which influences the sustainable development of economy. This paper studied on evaluation of water security. An improved classification algorithm by attribute importance is provided...
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