Digital ecosystems are one of the most important strategic issues in the current digital economy. Digital ecosystems are dynamic and generative. They evolve as new firms join and as heterogeneous systems are integrated into other systems. These features digital ecosystems determine economic and technological success in the competition among…

This dissertation transforms a set of system complexity reduction problems to feature selection problems. Three systems are considered: classification based on association rules, network structure learning, and time series classification. Furthermore, two variable importance measures are proposed to reduce the feature selection bias in tree…

The variety and complexity of potentially-related data resources available for querying--webpages, databases, data warehouses--has been growing ever more rapidly. There is a growing need to pose integrative queries "across" multiple such sources, exploiting foreign keys and other means of interlinking data to merge information from diverse…

An interoperability gap exists between Learning Management Systems (LMSs) and Learning Object Repositories (LORs). Learning Objects (LOs) and the associated Learning Object Metadata (LOM) that is stored within LORs adhere to a variety of LOM standards. A common LOM standard found in LORs is the Sharable Content Object Reference Model (SCORM)…

Purpose: Linking Open Data (LOD) provides a vast amount of well structured semantic information, but many inconsistencies may occur, especially if the data are generated with the help of automated methods. Data cleansing approaches enable detection of inconsistencies and overhauling of affected data sets, but they are difficult to apply…

In various research areas, the availability of open datasets is considered as key for research and application purposes. These datasets are used as benchmarks to develop new algorithms and to compare them to other algorithms in given settings. Finding such available datasets for experimentation can be a challenging task in technology enhanced…

Knowledge discovery is a wide ranged process including data mining, which is used to find out meaningful and useful patterns in large amounts of data. In order to explore the factors having impact on the success of university students, knowledge discovery software, called MUSKUP, has been developed and tested on student data. In this system a…

The notion of a system adapting itself to provide support for learning has always been an important issue of research for technology-enabled learning. One approach to provide adaptivity is to use social navigation approaches and techniques which involve analysing data of what was previously selected by a cluster of users or what worked for…

Existing research on context and context awareness has broadly focused on the technical aspects of context acquisition and interpretation of users' surroundings, also called physical or sensor-based context. Such an approach has lacked from reconciling the perception of real-world context exhibited by humans, also known as user context, and…

Although previous research has demonstrated learning benefits for both instructors and students in the web-based collaborative learning environments, one of them major difficulties is the lack of a practical approach to assist teachers in evaluating the knowledge contribution of learners. A novel method of merging multi-modes of assessment and…

This paper proposes a learning based method that can automatically determine how likely a student is to give a correct answer to a problem in an intelligent tutoring system. Only log files that record students' actions with the system are used to train the model, therefore the modeling process doesn't require expert knowledge for identifying…

The ability to predict a student's performance could be useful in a great number of different ways associated with university-level learning. In this paper, a grammar guided genetic programming algorithm, G3P-MI, has been applied to predict if the student will fail or pass a certain course and identifies activities to promote learning in a…

The Second International Conference on Educational Data Mining (EDM2009) was held at the University of Cordoba, Spain, on July 1-3, 2009. EDM brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large data sets to answer educational research questions. The increase in instrumented…