Ref HAL: hal-00712547_v1
DOI: 10.1007/s10796-012-9405-6
Abstract: Today, the Web is the largest source of information in the world. There is currently an increasing demand that decision-making applications such as Data Warehousing (DW) and Business Intelligence (BI) move onto the Web, especially in the cloud. Integrating data into the DW/BI applications is still the most critical and time-consuming task. To make better decisions in DW/BI applications, next generation data integration poses new requirements to data integration systems, over those posed by traditional data integration. From these requirements is to integrate data in real-time and autonomously with minimal user intervention. Therefore, we propose in this paper a metadata-based, event-driven, and service-oriented framework for integrating real-time data autonomously. The framework utilizes Web standards to integrate data, from heterogeneous and distributed sources. It exploits the XML language to address data heterogeneity, Web services to tackle data distribution, and Active XML (AXML) to store integrated data. The framework is also subscribed to Web services for real-time change data capture. Moreover, beside logging different framework events into a specified repository for on-line analysis and reporting, we propose a novel Frequency XML-based Tree (FXT) structure for mining association rules from logged event streams using XQuery. The framework is also incorporates active rules to automate and activate different integration services. Finally, we have a web application prototype as a proof of concept.

Comments: Special issue on Business Intelligence and the Web

Ref HAL: hal-00686001_v1
Abstract: Data integration is a critical problem in data warehousing and decision-support systems. Traditional data integration systems are very successful in integrating structured data, but structured data represent only a small subset of interesting data that could be warehoused by many enterprises. Current data integration systems also lack of self-managing capabilities. Therefore, we propose a data integration framework for integrating complex data actively. The purpose of our framework is twofold. Firstly, it integrates complex data using Web standards into an Active XML (AXML) repository. Secondly, beside warehousing logged events into event repository, it exploits active rules and framework events mining to self-manage, automate and activate different data integration tasks. Finally, we have implemented a prototype framework as a web application.

Ref HAL: hal-00631198_v1
Ref Arxiv: 1110.3158
Abstract: Many applications log a large amount of events continuously. Extracting interesting knowledge from logged events is an emerging active research area in data mining. In this context, we propose an approach for mining frequent events and association rules from logged events in XML format. This approach is composed of two-main phases: I) constructing a novel tree structure called Frequency XML-based Tree (FXT), which contains the frequency of events to be mined; II) querying the constructed FXT using XQuery to discover frequent itemsets and association rules. The FXT is constructed with a single-pass over logged data. We implement the proposed algorithm and study various performance issues. The performance study shows that the algorithm is efficient, for both constructing the FXT and discovering association rules.

Ref HAL: hal-00560970_v1
Abstract: Relevant data for decision support systems are available everywhere and in various formats. Such data must be integrated into a unified format. Traditional data integration approaches are not adapted to handle complex data. Thus, we exploit the Active XML language for integrating complex data. Its XML part allows to unify, model and store complex data. Moreover, its services part tackles the distributed issue of data sources. Accordingly, different integration tasks are proposed as services. These services are managed via a set of active rules that are built upon metadata and events of the integration system. In this paper, we design an architecture for integrating complex data autonomously. We have also designed the workflow for data integration tasks.

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Ref HAL: hal-00503963_v1
Abstract: Warehousing data is not a trivial task, particularly when dealing with huge amounts of distributed and heterogeneous data. Moreover, traditional de- cision support systems do not feature intelligent capabilities for integrating such complex data. Therefore, we propose an approach for intelligent decision sup- port based on active XML warehousing. We exploit XML as a pivot language in order to unify, model and store complex data. Furthermore, Web services tackle the distribution and interoperability problems of data sources. They are employed for complex data integration and react with active rules for realizing intelligent ETL. In this paper, we focus on the integration phase and propose an architecture for integrating complex data into a repository of Active XML documents, based onWeb services and event-driven rules. We have finally developed a software prototype to validate this approach.

Comments: medes09s