The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This paper deals with approaches to approximate reduction in inconsistent formal decision contexts. Congruence relations on the object power set are first introduced in a formal context. Then relationships between congruence relations and the corresponding concept lattices are discussed. Based on the congruence relations, notions of lower approximate and upper approximate attribute reduct are then...
Variable analysis and optimization could improve the performance of code migration from CUDA to multi-core. Based on memory mapping, a temporary arrays pruning algorithm is proposed in this paper. By analyzing the live range and def-use relation, the temporary arrays which could be pruned are identified. A function map between the definitions and use of temporary arrays is constructed to replace the...
This paper applies the data mining process to predict hypertension from patient medical records with eight other diseases. A sample with the size of 9862 cases has been studied. The sample was extracted from a real world Healthcare Information System database containing 309383 medical records. We observed that the distribution of patient diseases in the medical database is imbalanced. Under-sampling...
To accurately forecast container throughput is crucial to the success of any port operation policy. In this article, Attribute Theory is used for forecast port container throughput. The method of container throughput forecast based on Attribute Theory is provided. Then the application process of the method is presented in detail combining container throughput forecast of Shanghai Port as an example...
In the application of Web 2.0, some websites usually give the list of something popular for their users. To reach this, they first collect ratings on something from a large number users, and then perform the calculation through some algorithms. The algorithms, however, don't take the credibility of user himself into consideration. The paper proposes a ranking model based on user's credit, which takes...
In this paper, we propose a new method for mining class-association rules using a tree structure. Firstly, we design a tree structure for storing frequent itemsets of datasets. Some theorems for pruning nodes and computing information in the tree are then developed. We then propose an efficient algorithm for mining CARs based on them. Experimental results show that our approach is more efficient than...
In this paper, we propose an efficient projection-based algorithm to discover high sequential utility patterns from quantitative sequence databases. An effective pruning strategy in the proposed algorithm is designed to tighten upper-bounds for subsequences in mining. By using the strategy, a large number of unpromising subsequences could be pruned to improve execution efficiency. Finally, the experimental...
Covering-based rough set (CRS) is a meaningful and important generalization of Pawlak's rough set theory. The primary goal of this paper is to extend the formal study to partial covering (PCov) in terms of the global granular computing model (global/2nd GrC model). The main focus is to investigate the “best” approximations, where “best” was used by Pawlak in his 1982 paper. The study includes a comparison...
Information Classification is the categorization of the huge amount of data in an efficient and useful way. In the current scenario data is growing exponentially due to the rise of internet rich applications. One such source of information is the blogs. Blogs are web logs maintained by their authors that contain information related to a certain topic and also contain authors view about that topic...
LNS is a generalization of topological neighborhood system(TNS) by simply dropping all axioms of topology but the superset axiom. The goal of this paper is to show that LNS is the “correct” granule for granular computing (GrC) and Granular Mathematics (GrM). Here are some high lights 1) Zadeh(1996)suggested that if classical mathematics is viewed as Math(point), GrM is Math(granule). The axiomatization...
Traditional supervised learning deals with problems where one instance is associated with a single class label, whereas in many real tasks, one instance may be associated with multiple class labels simultaneously; for example, an image can be tagged with several keywords, a document may belong to multiple topics, etc. Thus, multi-label learning has attracted great attention [3, 8, 10, 11, 12, 14,...
Graph has been widely used as a data structure to abstract complex relationships among entities in a form on which algorithms are designed and systems are developed to maintain information, understand the complex relationships, and discovery knowledge. In this talk, we explore several research issues over large graphs.We introduce some research problems to be discussed: large graphs matching, graph...
Granular computing, as an emerging computational and mathematical theory which describes and processes uncertain, vague, incomplete, and mass information, has been successfully used in knowledge discovery. At present, granular computing faces the challenges of consuming a huge amount of computational time and memory space in dealing with large-scale and complicated data sets. Feature selection, a...
This paper aims to overview a variety of methods of clustering by introducing the concepts of inductive and non-inductive clustering. These concepts are in parallel with the concepts of inductive and transductive learning in the studies of semi-supervised classification. When the result of clustering naturally induces functions for classification on the whole space of interest, the method is called...
It is shown that the abstracting of sensitivity feature is not only a conversion from quantity into quality, but also can be described by Qualitative Mapping, and wavelet transformation can be defined by qualitative mapping.
The primary goal of this paper is to develop knowledge approximations and representations on binary relation from the view of granular computing (GrC). In rough sets (RS), approximations can be defined by two equivalent views, topology and elementary knowledge. The latter view does not behave well mathematically, so in GrC, topology has often been adopted. Unfortunately, such approximations, called...
The concepts of comparability and credibility of the symmetric similarity relations are proposed. This paper builds a dual-limited symmetric similarity relation and construct the rough set model based on the dual-limited symmetric similarity relation. Then, this paper determine the upper approximation set, and lower approximate set and the boundaries domain to improve the granularity and accuracy...
Integrating resources in e-learning systems and providing smoothly cross-system access can highly extend the learning range and improve learning efficiency. In this paper we made an attempt to establish an e-learning cloud. By reviewing the architecture of traditional e-learning system and concept of cloud computing, we proposed the idea of constructing e-learning cloud to enable e-learning resource...
To get the liver image segmentation from the whole abdominal medical image lays the foundation of liver three-dimensional reconstruction system, in that a good image segmentation result really makes a big difference in the three-dimensional reconstruction. This paper focuses on the research into Graph Cuts image segmentation algorithm, especially its energy function. Improved Gaussian distribution...
Rough set theory has been one of the major mathematical tools in data mining and knowledge discovery. The basic concepts of rough set theory are a pair of non-numerical operators, i.e., lower and upper approximation operators that are exported from the approximation spaces. Set-valued ordered information systems are generalized models of single-valued information systems. The attribute set in an information...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.