56 Result(s)
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Semisupervised learning from different information sources
This paper studies the use of a semisupervised learning algorithm from different information sources. We first offer a theoretical explanation as to why minimising the disagreement between individual models co...
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Optimizing complex queries based on similarities of subqueries
As database technology is applied to more and more application domains, user queries are becoming increasingly complex (e.g. involving a large number of joins and a complex query structure). Query optimizers i...
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Using discriminant analysis for multi-class classification: an experimental investigation
Many supervised machine learning tasks can be cast as multi-class classification problems. Support vector machines (SVMs) excel at binary classification problems, but the elegant theory behind large-margin hyp...
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Supervised tensor learning
Tensor representation is helpful to reduce the small sample size problem in discriminative subspace selection. As pointed by this paper, this is mainly because the structure information of objects in computer ...
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Hierarchical document classification using automatically generated hierarchy
Automated text categorization has witnessed a booming interest with the exponential growth of information and the ever-increasing needs for organizations. The underlying hierarchical structure identifies the r...
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SVM based adaptive learning method for text classification from positive and unlabeled documents
Automatic text classification is one of the most important tools in Information Retrieval. This paper presents a novel text classifier using positive and unlabeled examples. The primary challenge of this probl...
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Clustering based on matrix approximation: a unifying view
Clustering is the problem of identifying the distribution of patterns and intrinsic correlations in large data sets by partitioning the data points into similarity classes. Recently, a number of methods have b...
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A new approach to discover interlacing data structures in high-dimensional space
The discovery of structures hidden in high-dimensional data space is of great significance for understanding and further processing of the data. Real world datasets are often composed of multiple low dimension...
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Hierarchical associative classifier (HAC) for malware detection from the large and imbalanced gray list
Nowadays, numerous attacks made by the malware (e.g., viruses, backdoors, spyware, trojans and worms) have presented a major security threat to computer users. Currently, the most significant line of defense a...
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Resource service optimal-selection based on intuitionistic fuzzy set and non-functionality QoS in manufacturing grid system
In manufacturing grid (MGrid) system, according to functional requirements of a task, there exist a lot of resource services which have similar functional characteristics. Multiple resource services with simil...
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Temporal relation co-clustering on directional social network and author-topic evolution
Analyzing three-way data has attracted a lot of attention recently because such data have intrinsic rich structures and naturally appear in many real-world applications. One typical type of three-way data is m...
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Open AccessCorrecting evaluation bias of relational classifiers with network cross validation
Recently, a number of modeling techniques have been developed for data mining and machine learning in relational and network domains where the instances are not independent and identically distributed (i.i.d.)...
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Open AccessThe path to openness: letter from the editors
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Efficient processing of top-k queries: selective NRA algorithms
Efficient processing of top-k queries has drawn increasing attention from both industry and academia due to its varied applications. Lower access cost is a crucial concern for a top-k query processing. Typically,...
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Article
Non-negative Tri-factor tensor decomposition with applications
Non-negative matrix factorization (NMF) mainly focuses on the hidden pattern discovery behind a series of vectors for two-way data. Here, we propose a tensor decomposition model Tri-ONTD to analyze three-way d...
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Article
Does aspect-oriented modeling help improve the readability of UML state machines?
Aspect-oriented modeling (AOM) is a relatively recent and very active field of research, whose application has, however, been limited in practice. AOM is assumed to yield several potential benefits such as enh...
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Understanding continuance usage intention of mobile internet sites
Due to the high acquisition costs and low switching costs, retaining users and facilitating their continuance usage are crucial for mobile service providers. Integrating both perspectives of perceived utility ...
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Applying UML/MARTE on industrial projects: challenges, experiences, and guidelines
Modeling and Analysis of Real-Time and Embedded Systems (MARTE) is a Unified Modeling Language (UML) profile, which has been developed to model concepts specific to Real-Time and Embedded Systems (RTES). In th...
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SAMM: an architecture modeling methodology for ship command and control systems
Ship command and control systems (SCCSs) are composed of large-scale, complex, real-time and software-intensive systems that complete tasks collaboratively. Open architecture has been introduced to design the ...
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Article
Empirically evaluating OCL and Java for specifying constraints on UML models
The Object Constraint Language (OCL) has been applied, along with UML models, for various purposes such as supporting model-based testing, code generation, and automated consistency checking of UML models. How...
