Knowledge discovery in structured databases is very important nowadays. In the last years, graph-based data mining algorithms have used artificial neural networks as tools to support clustering. Several of these algor...
详细信息
ISBN:
(纸本)9781424496365
Knowledge discovery in structured databases is very important nowadays. In the last years, graph-based data mining algorithms have used artificial neural networks as tools to support clustering. Several of these algorithms have obtained promising results, but they show expensive computational costs. In this work we introduce an algorithm for clustering graphs based on a SOM network, which is part of a process for discovering useful frequent patterns in large graph databases. Our algorithm is able to handle non-directed, cyclic graphs with labels in vertices and edges. An important characteristic is that it presents polynomial computational complexity, because it uses as input a feature vector built with the spectra of the Laplacian of an adjacent matrix. Such matrix contains codes representing the labels in the graph, which preserves the semantic information included in the graphs to be grouped. We tested our algorithm in a small set of graphs and in a large structured database, finding that it creates meaningful groups of graphs.
Web-based databases are gaining increased popularity. This has positively influenced the availability of structured and semi-structured databases for access by a variety of users ranging from professionals to naive us...
详细信息
Web-based databases are gaining increased popularity. This has positively influenced the availability of structured and semi-structured databases for access by a variety of users ranging from professionals to naive users. The number of users accessing online databases will continue to increase if the visual tools connected to web-based databases are flexible and user-friendly enough to meet the expectations of naive users and professionals. Further, XML is accepted as the standard for platform independent data exchange. This motivated for the development of the conversion tools between structured databases and XML Realizing that such a need has not been well handled by the available tools, including Clio from IBM, we developed VIREX as a visual tool for converting relational databases into XML, and since then has been empowered with further capabilities to manipulate the produced XML schema including the maintenance of materialized views and schema evolution functions. VIREX provides an interactive approach for querying and integrating relational databases to produce XML documents and the corresponding XML schema(s). VIREX supports VRXQuery as a visual naive users-oriented query language that allows users to specify queries and define views directly on the interactive diagram as a sequence of mouse clicks with minimum keyboard input. As the query result. VIREX displays on the screen the XML schema that satisfies the specified characteristics and generates colored (easy to read) XML document(s). The main contribution described in this paper is the novel approach for turning query results into materialized views which are maintained to remain consistent with the underlying database. VIREX supports deferred update of XML views by keeping an ordered summary of the necessary and sufficient information required for the process. Each view has a corresponding marker in the ordered summary to indicate the start of the information to be reflected onto the view when it is acce
To enable effective access to databases on the Web, it is critical to integrate the large scale deep Web sources. Therefore, schema matching is a basic problem in many database application domains, such as data integr...
详细信息
ISBN:
(纸本)9781424455690
To enable effective access to databases on the Web, it is critical to integrate the large scale deep Web sources. Therefore, schema matching is a basic problem in many database application domains, such as data integration, E-business, data warehousing, and semantic query processing. In current implementations, schema matching has some significant limitations until now. And also, there are some problems of the interfaces which often have some hidden regularities over many sources. These regularities can be essentially leveraged in enabling semantics discover of schema matching. In this paper, we focus on the specific problem of semantic heterogeneity between schema matching. We propose a clustering algorithm to organize similar sources with metadata-labeling. Our system includes a same model representation for all relational databases schemas with their own ontologies. In this paper, we represent the experimental results of semantic mapping for two schemas.
To address the needs of a wider user group than professionals and to increase the accessibility to shared XML documents, this paper presents a system with a CUT query builder which generates XQuery statements that Sup...
详细信息
ISBN:
(纸本)9783642043932
To address the needs of a wider user group than professionals and to increase the accessibility to shared XML documents, this paper presents a system with a CUT query builder which generates XQuery statements that Support for both strict and fuzzy qualifiers. Our motivation is the fact that;XML is rapidly becoming the format of choice to contain information for both storage and transfer. Consequently, as more information is contained in XML there is a need to develop a way for non-technical users to query for information contained in XML documents. In this sense, the human language can be vague in describing queries and hence incorporating fuzziness in the GUI would be more appropriate. This is especially true when we think of naive users who are not expected to understand structured query languages. A user can comfortably specify, a query in simple terms and the developed intermediate layer is responsible to hide the details of the transformation process from the user. The target is a two-fold approach that satisfies the user the best and use XQuery to access the XML documents at the back end.
暂无评论