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Data mining plays a central role in knowledge discovery. It involves applying specific algorithms to extract patterns or rules from data sets in a particular representation. Many researchers in database and machine-learning fields are interested in this new research topic since it offers opportunities to discover useful information and important relevant patterns in large databases, thus helping decision-makers...
For the development of distance education, the update of interactive means is one of the important symbols. This paper mainly probes into the technology of Web page annotation for e-learning, studies on the key technologies of resource annotation and how to implement the interaction between learners and learning resources. In this paper, the model of resource interaction is put forward and the main...
We study the problem of detecting and profiling terrorists using a combination of ordinary flat classifiers and relational information. Our starting point is a database for a set of individuals characterized by both ldquolocalrdquo attributes such as age and criminal background, and ldquorelationalrdquo information such as communications among a subset of the individuals. A subset of the individuals...
Great many Websites exist present. These Websites are developing various services to accommodate many customers. This time, several kinds of links exist to website. But, size of early service Web page increased as numbers of this service increase greatly. A lot of links give load to Web server. When several users approached for Web page, a lot of links can give decline in the service speed. We made...
Semantic similarity measure plays an important role in semantic search. However, Intention in educational resources search with semantic similarity has been rarely. In this paper, we proposed ontology based semantic similarity method to compute the user query and provided educational resources, so as to improve the search efficiency. A prototype system has been implemented in light of this approach...
A hypergraph model of granular computing is proposed. In this model, a vertex refers to an object, a hyperedge corresponds to a granule, a hypergraph relates to a set of granules and their relations in a specific granularity, and a series of hypergraphs correspond to a hierarchical structure. The mapping between hypergraphs presents the relations of the granules in different levels. One can solve...
Incremental learning is attracting more and more interest in the field of machine learning due to its wide potential applications in many scientific and engineering areas. Negative correlation learning (NCL) (Liu and Yao; 1999a,b) is a successful approach to construct neural network ensembles. By encouraging the diversity of ensembles, it makes different neural networks to learn different knowledge...
The paper mainly supplements the definition of Granular sets which was proposed by predecessors. If let X be given, X is the subset of one or more granules and each granule is not the subset of X on the tolerance relation of Gr, we define some concepts of lower and upper approximation of X, and discuss its properties.
To improve adaptability and flexibility of heterogeneous database integration system, the paper proposed a heterogeneous database integration framework based on Web services composition which is implemented by Web services composition template. The paper also adopted granular computing to optimize Web services composition to improve efficiency and quality of heterogeneous integration systems. The...
The layout of a Web page commonly offers a limited variety of elements arranged in a number of ways, for example, in navigation panels, or as advertisements, text content, and images. Presumably, the layout of a Web page will influence the way it is used, and this may or may not match the intentions of its designers. In this paper, we propose a novel graph mining algorithm and apply it to study the...
As NETWORK attackers become more and more sophisticated and wireless communications make the potential risks in data protection more serious, we come to need much stronger authentication and access control systems. In this paper, we propose a combined authentication method including biometric and access control system based on attribute-wise encryption in wireless environment for ubiquitous computing...
Feature extraction and feature selection have become an apparent need in many bioinformatics applications. In this paper, the features are extracted from protein primary single sequence database, based on amino acid composition and k-mer patterns or k-tuples and then feature selection is carried out from the extracted features. Since the rough QuickReduct is not yet applied for protein sequence data...
In the paper, we introduce the notion of an formal contexts homomorphisms, which is a powerful tool to study the relation between two formal contexts. Based on the notion of homomorphisms of formal contexts, we discuss the invariant characters of formal contexts under homomorphisms, and reveal the relation of attributes characters and formal concepts between two formal contexts under homomorphisms...
In this paper, a new concept of up-to-date patterns is proposed, which is a hybrid of the association rules and temporal mining. An up-to-date pattern is composed of an item set and its up-to-date lifetime, in which the user-defined minimum support threshold must be satisfied. The proposed approach can mine more useful large itemsets than the conventional ones which discover large itemsets valid only...
Because of the exponential growth in worldwide information, companies have to deal with an ever growing amount of digital information. One of the most important challenges for data mining is quickly and correctly finding the relationship between data. The Apriori algorithm is the most popular technique in association rules mining; however, when applying this method, a database has to be scanned many...
Recommender systems use various types of information to help customers find products of personalized interest. To increase the usefulness of recommender systems in certain circumstances, it could be desirable to merge recommender system databases between companies, thus expanding the data pool. This can lead to privacy disclosure hazards that this paper addresses by constructing an efficient privacy-preserving...
We discuss the set of all Boolean association rules. By defining special partial order on the set, we get an isomorphism between the set and a special finite ranked poset. Through discussing some basic properties of the finite ranked poset, we can clearly represent the hierarchical structure of all Boolean association rules. Meanwhile, the Hasse diagram of the poset offers a visualization view of...
Formal concept analysis (FCA) is a method mainly used for the analysis of data, which identifies conceptual structures among data sets. Central to FCA is the notion of formal context. A formal context is usually defined as a binary relation between a set of objects and a set of attributes. But in real world, it is more meaningful to consider the direct relations between objects (or individuals). In...
Granular transform of original data, can obtain the userspsila expected results in their interested level, and can decrease the size of data at the same time. So, it has become an important research issue in data mining area. In this paper, a model of granular transform is constructed based on domain knowledge. Then, it is integrated with classification rules learning. A generalization algorithm is...
Scene classification is valuable in image retrieval from databases because an understanding of the scene content can be used for efficient and effective database organization and browsing. a scene classification based on rough set method features selection for outdoor images is developed in this paper, support vector machines and k-nearest neighbors classification model are used, experiments on University...
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