In this paper, we propose a rule management system for data cleaning that is based on knowledge. This system combines features of both rule based systems and rule based data cleaning frameworks. The important advantag...In this paper, we propose a rule management system for data cleaning that is based on knowledge. This system combines features of both rule based systems and rule based data cleaning frameworks. The important advantages of our system are threefold. First, it aims at proposing a strong and unified rule form based on first order structure that permits the representation and management of all the types of rules and their quality via some characteristics. Second, it leads to increase the quality of rules which conditions the quality of data cleaning. Third, it uses an appropriate knowledge acquisition process, which is the weakest task in the current rule and knowledge based systems. As several research works have shown that data cleaning is rather driven by domain knowledge than by data, we have identified and analyzed the properties that distinguish knowledge and rules from data for better determining the most components of the proposed system. In order to illustrate our system, we also present a first experiment with a case study at health sector where we demonstrate how the system is useful for the improvement of data quality. The autonomy, extensibility and platform-independency of the proposed rule management system facilitate its incorporation in any system that is interested in data quality management.展开更多
Web information system(WIS)is frequently-used and indispensable in daily social life.WIS provides information services in many scenarios,such as electronic commerce,communities,and edutainment.Data cleaning plays an e...Web information system(WIS)is frequently-used and indispensable in daily social life.WIS provides information services in many scenarios,such as electronic commerce,communities,and edutainment.Data cleaning plays an essential role in various WIS scenarios to improve the quality of data service.In this paper,we present a review of the state-of-the-art methods for data cleaning in WIS.According to the characteristics of data cleaning,we extract the critical elements of WIS,such as interactive objects,application scenarios,and core technology,to classify the existing works.Then,after elaborating and analyzing each category,we summarize the descriptions and challenges of data cleaning methods with sub-elements such as data&user interaction,data quality rule,model,crowdsourcing,and privacy preservation.Finally,we analyze various types of problems and provide suggestions for future research on data cleaning in WIS from the technology and interactive perspective.展开更多
The cleaning parameters affecting cleaning rate using pure waterjets to clean road surface was researched. A mathematical model for predicting cleaning rate was established using fuzzy mathematical method. A fuzzy rul...The cleaning parameters affecting cleaning rate using pure waterjets to clean road surface was researched. A mathematical model for predicting cleaning rate was established using fuzzy mathematical method. A fuzzy rule base character-izing the relationship between input and output parameters was built through experiments. The prediction of cleaning rate was achieved under the condition of given input parameters by rule-based fuzzy reasoning. The prediction results were analyzed through experimental verification.展开更多
文摘In this paper, we propose a rule management system for data cleaning that is based on knowledge. This system combines features of both rule based systems and rule based data cleaning frameworks. The important advantages of our system are threefold. First, it aims at proposing a strong and unified rule form based on first order structure that permits the representation and management of all the types of rules and their quality via some characteristics. Second, it leads to increase the quality of rules which conditions the quality of data cleaning. Third, it uses an appropriate knowledge acquisition process, which is the weakest task in the current rule and knowledge based systems. As several research works have shown that data cleaning is rather driven by domain knowledge than by data, we have identified and analyzed the properties that distinguish knowledge and rules from data for better determining the most components of the proposed system. In order to illustrate our system, we also present a first experiment with a case study at health sector where we demonstrate how the system is useful for the improvement of data quality. The autonomy, extensibility and platform-independency of the proposed rule management system facilitate its incorporation in any system that is interested in data quality management.
文摘Web information system(WIS)is frequently-used and indispensable in daily social life.WIS provides information services in many scenarios,such as electronic commerce,communities,and edutainment.Data cleaning plays an essential role in various WIS scenarios to improve the quality of data service.In this paper,we present a review of the state-of-the-art methods for data cleaning in WIS.According to the characteristics of data cleaning,we extract the critical elements of WIS,such as interactive objects,application scenarios,and core technology,to classify the existing works.Then,after elaborating and analyzing each category,we summarize the descriptions and challenges of data cleaning methods with sub-elements such as data&user interaction,data quality rule,model,crowdsourcing,and privacy preservation.Finally,we analyze various types of problems and provide suggestions for future research on data cleaning in WIS from the technology and interactive perspective.
文摘The cleaning parameters affecting cleaning rate using pure waterjets to clean road surface was researched. A mathematical model for predicting cleaning rate was established using fuzzy mathematical method. A fuzzy rule base character-izing the relationship between input and output parameters was built through experiments. The prediction of cleaning rate was achieved under the condition of given input parameters by rule-based fuzzy reasoning. The prediction results were analyzed through experimental verification.
