%0 Book Section %1 duan2012knowledge %A Duan, Yucong %A Lee, Roger %B Studies in Computational Intelligence %D 2012 %E Lee, Roger Y. %I Springer-Verlag %K VLDB cleaning data knowledge management myown %P 143-158 %T Knowledge Management for Model Driven Data Cleaning of Very Large Database %X From a knowledge management perspective, we explore data cleaning of very large databases with focus on semantic rich data and linked data. We identify four aspects of complexity which, if they were not explicitly addressed and fully managed will hinder both the recognizing and attaining of the best result: (a) the in- consistency of solution knowledge due to their partial applicability among multiple concerns; (b) the side effect which is introduced during the introduction of solution knowledge for pursuing a precision relating to the existence of multiple semantics; (c) unconscious ignorance of implicit weights of some parameters for value com- putation; (d) a holism based reasoning which is irreplaceable by simplification for some situations. After analyzing the state of the art, we propose an ongoing Model Driven Engineering (MDE) based knowledge management platform for identify- ing, refining, organizing and evaluating related variants and solutions with mitigated complexity.

@inbook{duan2012knowledge, abstract = {From a knowledge management perspective, we explore data cleaning of very large databases with focus on semantic rich data and linked data. We identify four aspects of complexity which, if they were not explicitly addressed and fully managed will hinder both the recognizing and attaining of the best result: (a) the in- consistency of solution knowledge due to their partial applicability among multiple concerns; (b) the side effect which is introduced during the introduction of solution knowledge for pursuing a precision relating to the existence of multiple semantics; (c) unconscious ignorance of implicit weights of some parameters for value com- putation; (d) a holism based reasoning which is irreplaceable by simplification for some situations. After analyzing the state of the art, we propose an ongoing Model Driven Engineering (MDE) based knowledge management platform for identify- ing, refining, organizing and evaluating related variants and solutions with mitigated complexity.}, added-at = {2012-08-16T10:12:00.000+0200}, author = {Duan, Yucong and Lee, Roger}, biburl = {https://www.bibsonomy.org/bibtex/2d88fb672ec5a9d3b224a655a868609d4/yucongduan}, editor = {Lee, Roger Y.}, interhash = {99181c808528fd3a93fe0ab5bd7aeb99}, intrahash = {d88fb672ec5a9d3b224a655a868609d4}, keywords = {VLDB cleaning data knowledge management myown}, month = {August}, pages = {143-158}, publisher = {Springer-Verlag}, series = {Studies in Computational Intelligence}, timestamp = {2012-08-16T10:12:00.000+0200}, title = {Knowledge Management for Model Driven Data Cleaning of Very Large Database}, year = 2012 }