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The information system classification is a crucial part of data mining, which aims to analysis the information system, extract important message from complex data, and forecast the future development trend of data. At present, there are many methods to classify the data, for example, Rough Set Theory, Decision Tree, Bayesian Network, Genetic Algorithm, etc. The method presented in this paper, based...
The following topics are dealt with: particle swam optimization; evolutionary computation; case based reasoning; language processing, pattern classification; data mining; optimization; intelligence control; robotization; ubiquitous network; pervasive network; information system; network management; steganography; watermarking; image processing and network control.
In this paper we propose a rough classification modeling algorithm based on Ant Colony Optimization (ACO) reduction. We used ACO to compute the rough set reduct and later a modified rules generation method is employed to generate the classification rules. The rules generation algorithm used is the simplification of the Default Rules Generation Framework (DRGF) in order to fit with the ACO reduct....
Action rules are built from atomic expressions called atomic action terms and they describe possible transitions of objects from one state to another. They involve changes of values within one decision attribute. Association action rule is similar to an action rule but it may refer to changes of values involving several attributes listed in its decision part. Action paths are defined as sequences...
In this paper, a course management system has been designed on the basis of data mining methods such as association rules, classification and clustering. This system aims at analyzing the hidden relationship between the students' academic grades and various data of students' performance in class, and the findings can be used as guidance for better teaching and learning in the future.
In the past, the choices of ?? values to be applied to find the ??-reducts in VPRS for an information system are somewhat arbitrary. In this study, a systematic approach to determine the threshold value ?? of VPRS applied to information systems with continuous attributes is presented. The ?? value is directly connected to fuzzy membership functions by implication relations and fuzzy algorithms, in...
13 kind of nationalities crowds' data classification using hierarchical cluster (HC), rough sets (RS), principal component analysis (PCA) and its combination, the result shows: first, rough sets and principal component analysis can dimensionality reduction and de-noising; second, hierarchical cluster after rough sets (RSHC), principal component analysis after rough sets (PCARS), principal component...
Modern information systems consist of many distributed computer and database systems. The integration of such distributed data into a single data warehouse system is confronted with the well known problem of low data quality. In this paper we present an approach that facilitates a dynamic identification of spurious and error-prone data stored in a large data warehouse. The identification of data quality...
In this paper, a new approach of reducing redundancy condition is put forward based on an information consistency relationship of equivalent classification. The best coverage of data coordinated about the decision-table of an information decision system and the significance of attribute to the system is chosen as a rule of heuristic information of the attribute j by way of ant colony optimization...
Variable precision rough set model, as a probabilistic extension of original rough set model, is a very useful approach to inducing probabilistic rules from datasets. In this paper, some anomalies in present definition of attribute reduction based on variable precision rough set model are discussed. Maximum condition entropy is introduced to analyze the mergers of condition classes in the process...
Approximations of a concept in the variable precision rough set model will change when an information system varies with time. Usually, it is an effective method to carry out incremental updating approximations by using existing information in the dynamic environment. This paper focuses on the incremental updating principle of computing approximations while objects in information systems dynamically...
This paper inquired into the technology of mining classification rules based on rough sets. Proposed a method of amalgamating classification rules from distributed database, by which all rules fitting for global data can be gotten. Then, experiment results were given to verify the completeness of these rules. At last, pruning strategy proposed for resolving the problem of over amalgamation.
Security of an information system depends to a large extent on its ability to authenticate legitimate users as well as to withstand attacks of various kinds. Confidence in its ability to provide adequate authentication is, however, waning. This is largely due to the wrongful use of passwords by many users. In this paper, the design and development of keystroke pressure-based typing biometrics for...
The specific mode of practice learning methods and content are given in the hierarchical teaching methods. Combined radix sort algorithm and an example of data structure, it also discusses its application in data classification based on rough sets theory.
The ultimate goal of knowledge discovery (KD) is to extract sets of patterns leading to useful knowledge for obtaining user desirable outcomes. The key characteristics of knowledge usefulness is that these patterns are actionable. In the last decade, KD algorithms such as mining for association rules, clustering, and classification rules, have made a tremendous progress and have been demonstrated...
Rough set theory and formal concept analysis were invented by Pawlak and Wille in the 1980s and have been applied successfully in several domains. In this paper, we propose a new case-based classifier system based on an integrated rough set theory and formal concept analysis technique. We focus on the construction of a better knowledge base to produce the classification rules. Our system employs rough...
The attribute reduction and value reduction of rough set were discussed in this paper. The discernibility matrix was extended to value reduction firstly and the attribute significance was redefined based on attribute dependence. An algorithm for classification rules extraction based on discernibility matrix and attribute significance is proposed, which keeps the same classification ability and the...
This paper proposes an integration system to the logistics enterprise information system in distributed heterogeneous environment. We establish a framework structure of universal data mining system based on logistics data warehouse and apply the proposed system into practical management of logistics and shipping enterprises. Feature extraction and data sample classification from large-scale data warehouse...
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