In this paper we show the potential of contextual itemset mining in the context of Linked Open Data. Contextual itemset mining extracts frequent associations among items considering background information. In the case of Linked Open Data, the background information is represented by an Ontology defined over the data. Each resulting itemset is specific to a particular context and contexts can be...

World wide technological advancement has brought in a widespread change in adoption and utilization of open source tools. Since, most of the organizations across the globe deal with a large amount of data to be updated online and transactions are made every second, managing, mining and processing this dynamic data is very complex. Successful implementation of the data mining technique requires ...

INTRODUCTION There is still interest in a unified methodology to quantify the mass of particulate material emitted into the atmosphere by activities inherent to open-pit mining. For the case of total suspended particles (TSP), the current practice is to estimate such emissions by developing inventories based on the emission factors recommended by the USEPA for this purpose. However, there are d...

This paper develops tests and validates a model for the antecedents of open source software (OSS) defects, using Data and Text Mining. The public archives of OSS projects are used to access historical data on over 5,000 active and mature OSS projects. Using domain knowledge and exploratory analysis, a wide range of variables is identified from the process, product, resource, and end-user charac...

This study uses Cohesion Network Analysis (CNA) indices to identify student patterns related to course completion in a massive open online course (MOOC). This analysis examines a subsample of 320 students who completed at least one graded assignment and produced at least 50 words in discussion forums in a MOOC on educational data mining. The findings indicate that CNA indices predict with subst...