Online tracking technologies have raised considerable concerns regarding privacy and the protection of personal data of users. In order to help users to regain control over their personal data, Europe has amended its ePrivacy directive towards an opt-in regime. There are however many open questions concerning its implementation, especially regarding the issue of informed consent. This paper exp...

This paper addresses the problem of video-level object instance search, which aims to retrieve the videos in the database that contain a given query object instance. Without prior knowledge about “when” and “where” an object of interest may appear in a video, determining “whether” a video contains the target object is computationally prohibitive, as it requires exhaustively matching the query a...

In this paper we present a query answering system for solving non-standard queries in a distributed knowledge based system (DKBS). Our system is di erent from solving queries on a conventional distributed database or cooperative database in the sense that it discovers rules, if needed, and uses them to resolve unknown attributes. In [12], the rules used to resolve unknown attributes are discove...

Information systems log data during the execution of business processes in so called “event logs”. Process mining aims to improve business processes by extracting knowledge from event logs. Currently, the de-facto standard for storing and managing event data, XES, is tailored towards sequential access of this data. Handling more and more data in process mining applications is an important chall...

Access to stored knowledge is a complex, yet extremely well-studied process. Knowledge management has always concentrated on coding and proposing infrastructures for the explicit storing of knowledge. In this document, we shall study the problems which exist in knowledge mobilization. In turn, we shall present our proposal for dealing with the problems encountered in knowledge mobilization from...

Each business company collects, produces and exploits for its activities and goals large amounts of information. Most of the times this knowledge makes the intellectual capital for creating value and innovation. Knowledge management (KM) systems aim at manipulating knowledge by storing and redistributing corporate information that are acquired from the organizations members. In this context, Vi...

Generally, ontology learning and population is applied as a semi-automatic approach to knowledge acquisition in natural language understanding systems. That means, after the ontology is created or populated, an expert of the domain can still change or refine the newly acquired knowledge. In an incremental ontology learning and population framework (as e.g. applied in open-domain dialog systems)...

Experience Management (EM) is an area that is increasingly gaining importance. Its roots lie in Experimental Software Engineering ("Experience Factory"), in Artificial Intelligence ("Case-Based Reasoning"), and in Knowledge Management. EM is comprised of the dimensions methodology, technical realization, organization, and management. It includes technologies, methods, and tools for identifying,...

In the paper we propose a method of structuring a knowledge base into hierarchically related contexts and present how this arrangement influences the structure of TBox and ABox. We introduce a possibility to attach to a single TBox many ABoxes describing different parts of a domain and we show how to interpret such an ontology. Practical application of the method offers very interesting possibi...

Knowledge representation has long had the insight that one data model, if it is expressive enough, is both necessary and sufficient for adequately storing information. Software engineering, alas, has gone a different way and uses an assortment of models. This model heterogeneity leads to problems of understanding and maintenance, because mappings between them are unavoidable and complicated. We...