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 article explores advances in the data mining arena to solve the fundamental MAXSAT problem. In the proposed approach, the MAXSAT instance is first decomposed and clustered by using data mining decomposition techniques, then every cluster resulting from the decomposition is separately solved to construct a partial solution. All partial solutions are merged into a global one, while managing possible...
The paper presents a new approach for processing of rhinomanometric signals based on F-transform approximation of phase diagrams. Methods of nonlinear dynamics for processing of time series allow us to obtain a significant features of rhinomanometric signals. Research indicated that the results of classification with F-transform approximation is more accurate than results of classification with FFT...
Text attribution and classification, for both information retrieval and analysis, have become one of the main issues in the matter of security, trust and copyright preservation. This paper proposes an innovative approach for text classification using Chebyshev polynomials and holomorphic transforms of the coefficients space. The main advantage of this choice lies in the generality and robustness of...
Data preprocessing describes any type of processing performed on raw data to prepare it for another processing procedure. Commonly used as a preliminary data mining practice, data preprocessing transforms the data into a format that will be more easily and effectively processed. Sequential Pattern Mining finds interesting sequential patterns among the large database. Data acquired from the dataset...
Data marts are nominated to accomplish the role of tactical decision support for managers accountable for a specific business area. The data from data marts is typically gathered and made offered for business analysis. A planned ETL process populates data marts within the focus on precise data warehouse information. Extract-Transform-Load (ETL) functions as a process which is used to receive information...
Sequential pattern mining is an essential data mining technique that has been widely applied to many real world applications. However, traditional algorithms generally suffer from the scalability problem when dealing with big data. In this paper, we aim to significantly upgrade the scale and propose Sequential PAttern Mining algorithm based on MapReduce model on the Cloud (abbreviated as SPAMC). Derived...
The extract, transform and Load (ETL) tool is extracting data from multiple, heterogeneous data source, transforming data, and finally loading data into the data warehouse. It is the foundation of any data warehouse, data mining and business intelligence. The land and resources system usually adopts star schema database, so it is difficult to transform the data from source database to target warehouse...
Semi-supervised classification from pairwise constraints is a challenge in pattern recognition, since the constraints just represent the relationships between data pairs rather than the definite labels. In the last few years, several methods have been proposed, however, they still utilize either the discriminability within the constraints or the abundant unlabeled data insufficiently. In this paper,...
Complex information is prevailing in every sphere of activities This call for the necessity to represent, store and manipulate complex information (e.g. detects correlations and patterns, discover explanations, construct predictive models etc.). Furthermore, being autonomously maintained, data can change in time or even change its base structure, making it difficult for representation systems to accommodate...
In this paper, we propose a pre-processing technique to improve existing string similarity join algorithms using fuzzy clustering. Our approach first identifies groups of related attributes and then, using this information, we apply existing string similarity join algorithms on these attributes. To identify the clustered attributes we use fuzzy techniques. This approach can be applied to the integration...
Data transformation method is well known in Knowledge Discovery in Databases (KDD) process and data mining in order to transform raw data into concepts at higher levels concepts. A number of promising data transformation methods have been studied and developed. Despite the great advantages offered by these data transformation methods, these methods still requires further improvement. In order to handle...
Extenics is a new discipline, it uses formal model research the possibility of expand thinking and the rules and methods of opening innovation and uses to solve the paradoxical problem of science. Extension data mining is a product combining Extenics with data mining. It explores to acquire the knowledge about extension transformations in databases, which is called extension knowledge, taking advantage...
Schema matching is a critical problem for achieving semantic interoperability between heterogeneous information sources, and plays a key role in database applications. The aim of schema matching problem (SMP) is to find semantic correspondences between two schemas and indeed a combinatorial problem. In this paper, we use the labeled graph as the internal schema model, so SMP can be formulized as a...
This paper provides a web content-based image searching engine based on SIFT (Scale Invariant Feature Transform) feature matching. SIFT descriptors, which are invariant to image scaling and transformation and rotation, and partially invariant to illumination changes and affine, present the local features of an image. Therefore, feature keypoints can be extracted more accurately by using SIFT than...
A Method, to locate eye in image by using gray projection, is presented. We utilize the gray differential projection cure of the facial image to locate eye vertically position and utilize the gray integral projection cure to locate eye horizontal position. The method can apply to not only the upright front side face, but also the upright side face, lift up face and low face. When the face in image...
This paper develops a supervised discriminant technique, called margin maximum embedding discriminant (MMED), for dimensionality reduction of high-dimensional data. In graph embedding, our objective is to find a linear transform matrix to make the samples in the same class as compact as possible and the samples belong to the different classes as dispersed as possible. The proposed method effectively...
A novel non-invasive method is proposed to help identify the endangered Pygmy Bluetongue Lizard. This would be preferable to the commonly used, invasive, toe-clipping method, which could be unreliable if the lizard was to lose a toe or foot naturally. Each lizard has a unique and permanent scale pattern which can be used to identify individual lizards. The proposed method involves a novel technique...
E-marketplace activities initiated by users in general require representing the user requirements and preferences matched with a set of offerings. One issue of these activities is the heterogeneity among them, which asks for semantic consistency maintenance. This paper solves this problem by applying collaborative concept exchange technology and developing a novel RuleXPM approach. This approach transforms...
In the recent past, the recognition and localization of objects based on local point features has become a widely accepted and utilized method. Among the most popular features are currently the SIFT features, the more recent SURF features, and region-based features such as the MSER. For time-critical application of object recognition and localization systems operating on such features, the SIFT features...
Active rules allow software systems behave automatically when relevant events take place. Due to unstructured rule processing, it is necessary to inspect behavior characteristics such as termination which guarantees that rule processing finishes. In this paper we introduce potential termination concept which gives valuable information about those rules whose processing may not terminate during execution...
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.