SEWEBAR-CMS: semantic analytical report authoring for data mining results

作者:Tomáš Kliegr, Vojtěch Svátek, Martin Ralbovský, Milan Šimůnek

摘要

SEWEBAR-CMS is a set of extensions for the Joomla! Content Management System (CMS) that extends it with functionality required to serve as a communication platform between the data analyst, domain expert and the report user. SEWEBAR-CMS integrates with existing data mining software through PMML. Background knowledge is entered via a web-based elicitation interface and is preserved in documents conforming to the proposed Background Knowledge Exchange Format (BKEF) specification. SEWEBAR-CMS offers web service integration with semantic knowledge bases, into which PMML and BKEF data are stored. Combining domain knowledge and mining model visualizations with results of queries against the knowledge base, the data analyst conveys the results of the mining through a semi-automatically generated textual analytical report to the end user. The paper demonstrates the use of SEWEBAR-CMS on a real-world task from the cardiological domain and presents a user study showing that the proposed report authoring support leads to a statistically significant decrease in the time needed to author the analytical report.

论文关键词:Data mining, Association rules, Background knowledge, Semantic web, Content management systems, Topic maps

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论文官网地址:https://doi.org/10.1007/s10844-010-0137-0