Robert Andrei Buchmann

An Approach to the Semantization of ERP Systems

The paper promotes a methodology and application model for extending traditional, data-centric Enterprise Resource Planning Systems with semantics-oriented data models, in order to enrich interaction and reporting capabilities. The proposal includes a method of automating data semantization using a mix of semantic modeling and formal concept analysis, and an extended ERP architecture which integrates legacy systems in a Semantic Web wrapper system, providing new dimensions to traditional interaction and reports in a business environment, with specific examples regarding human resources management.

Integration of Association Rule Detection with Rule-Based Ontological Support for Product Recommendation

Recommender systems can increase the sales by suggesting to users additional products, that were selected by their preferences. Availability of efficient mechanisms for generating the adequate products and for capturing the eligible information are the most important challenges of Web users. The Apriori algorithm is the best-known association rules mining algorithm, whose objective is to find all co-occurrence relationships between data items. In order to obtain a well defined information in an open standard format, we propose, an ontology-based recommender system, which describes the item features in terms of semantic concepts. In this paper, a methodology that combines the Apriori algorithm with a domain-specific ontology is proposed. The proposed model transfers the association rules on custom OWLIM rules, and by using OWLIM semantic repositories the detected associations will become public and can be interconnected with other information from the Internet. In this way, new facts can be deduced, therefore new relationships and rules between product items will be generated.

Mapping a Relational Database into a RDF Repository

Lately, we hear more and more about Semantic Web and the benefits that it brings to the current Web. But just a few companies are adopting solutions based on semantic web technologies, one reason being that their currently information technology systems are generally based on data stored in relational databases. Replicating a relational database, only with the public information, in a RDF repository, would require additional efforts for the company. This paper presents a solution for mapping a relational database, used to manage the human resources of a company, into a RDF repository, which offers portability and easy integration with other knowledge bases and which can be useful to manage public information about employees. Our approach also highlights the integration of the resulting ontology with PHP to provide a user interface.

Temporary Belief Sets Management in Adaptive Training Systems

The paper proposes a semantic view on the notion of ,,learning object” and an application model based on RDF-based learning objects and learning processes. Direct feedback is individualized for test subjects and learning tasks, according to requirements defined for corporate training. The knowledge model allows contextualization and subjectivity, which, in turn, are used to dynamically generate temporary belief sets, compare them to the (theoretically) objective belief set underlying the learning content and adapt learning recommendations to each particular user. The semantic models also determine learning prerequisites and the screen flow adapted to each individual learner, thus influencing usability.

Capturing Eye Tracking Data for Customer Profiling

In the context of user-centric design and customer profiling based on the persona paradigm, the paper proposes a Web application model focused on integrating eye tracking data and user-defined metadata with a profile repository. During user-computer interaction through an AJAX-driven graphic interface or interactive document, the user attention map is captured with eye tracking tools and converted in formats that are fit for mining and inferring on relationships between the key concepts that attracted the user’s attention. For facile integration of metadata with HTML dynamically generated pages, solutions such as microformats and RDF in attributes are employed.

An Eye Tracking Semantic Repository for User Profiling

The paper details the modeling and processing of a semantic behavior repository for Web users/customers in the context of an application model that involves the capturing of eye tracking during the user-interface interaction, AJAX-style communication between the client and the server, and the conversion of user attention maps to convenient data structures. Due to the problem complexity, the client-side mechanism for capturing attention nodes were presented in a previously published paper, thus the current paper covers strictly the server-side details regarding the semantic modeling and programming, with a brief presentation of the context, for coherence reasons.