Floris Wiesman

Domain Independent Learning of Ontology Mappings

This paper proposes a domain independent method for handling interoperability problems by learning a mapping between ontologies. The learning method is based on exchanging instances of concepts that are defined in the ontologies. The method starts with identifying pairs of instances of concepts denoting the same entity in the world using information retrieval techniques, followed by proposing and evaluating mappings between the ontologies using the pairs of instances. For each step of this method, the likelihood that a decision is correct is taken into account. Important benefits of the method are that (a) no domain knowledge is required, and (b) the structures of ontologies between which a mapping must be established, play no role.

Information retrieval: an overview of system characteristics

The paper gives an overview of characteristics of information retrieval (IR) systems. The characteristics are identified from the descriptions of 23 IR systems. Four IR models are discussed: the Boolean model, the vector model, the probabilistic model and the connectionistic model. Twelve other characteristics of IR models are identified: search intermediary, domain knowledge, relevance feedback, natural language interface, graphical query language, conceptual queries, full-text IR, field searching, fuzzy queries, hypertext integration, machine learning, and ranked output. Finally, the relevance of IR systems for the World Wide Web is established.

Towards patient-related information needs.

The quality of health care depends, among other factors, on the quality of a physicians domain knowledge. Since it is impossible to keep up with all new findings and developments, physicians usually have gaps in their domain knowledge. To handle exceptional cases, access to the full range of medical literature is required. The specific literature needed for appropriate treatment of the patient is described by a physicians information need. Physicians are often unaware of their information needs. To support them, this paper presents a first step towards automatically formulating patient-related information needs. We start investigating how we can model a physicians information needs in general. Then we propose an approach to instantiate the model into a representation of a physicians information needs using the patient data as stored in a medical record. Our experiments show that this approach is feasible. Since the number of formulated patient-related information needs is rather high, it has to be reduced. To reduce the number of formulated information needs we propose the use of additional knowledge. Four types of knowledge are discussed, viz. (a) knowledge about temporal aspects, (b) domain knowledge, (c) knowledge about a physicians specialism, and (d) a user model. Future research has to clarify which type of knowledge (or combination thereof) is most appropriate for our purpose. It is expected that the resultant set of information needs will have a manageable size and contributes to the quality of health care.

Automatic ontology mapping for agent communication

Agent communication languages provide a standard for agent communication. For the protocol and the language used in the communication, several standards are available. This is not the case for the ontology used in the communication. The ontology depends on the subject of the communication. Since the number of subjects is almost infinite and since the concepts used for a subject can be described by different ontologies, the development of generally accepted standards will take a long time. This lack of standardization, which hampers communication and collaboration between agents, is known as the phinteroperability problem. To overcome the interoperability problem, an approach that enables agents to learn a mapping between their ontologies is proposed

Information retrieval by metabrowsing

This article investigates a new, effective browsing approach called metabrowsing. It is an alternative for current information retrieval systems, which still face six prominent difficulties. We identify and classify the difficulties and show that the metabrowsing approach alleviates the difficulties associated with query formulation and missing domain knowledge. Metabrowsing is a high-level way of browsing through information: instead of browsing through document contents or document surrogates, the user browses through a graphical representation of the documents and their relations to the domain. The approach requires other cognitive skills from the user than what is currently required. Yet, a user evaluation in which the metabrowsing system was compared with an ordinary query-oriented system showed only some small indicatory differences in effectiveness, efficiency, and user satisfaction. We expect that more experience with metabrowsing will result in a significantly better performance difference. Hence, our conclusion is that the development of new cognitive skills requires some time before the technologies are ready to be used.

Information Retrieval in Medicine: The Visual and the Invisible (Information Retrieval im Gesundheitswesen: Das Visuelle und das Unsichtbare)

Summary Especially in knowledge-rich domains such as medicine perfect access to the literature is essential for professionals. Unfortunately, especially in knowledge-rich domains it is difficult to achieve perfect access: it is too difficult and too time consuming for users to formulate queries that yield the maximum of relevant documents and a minimum of non-relevant ones. The paper first discusses the challenges of information retrieval in medicine and various existing approaches. To address the challenges two completely opposite approaches are presented. The first supports the user by means of metabrowsing: a visual way of depicting the relations between domain concepts and documents. Metabrowsing relieves the user from the formulation of queries, while leaving him in full control. The second approach aims to minimize the interaction with the user. Information needs and queries are autonomously and proactively formulated by a software-agent who remains invisible to the user. The agent uses the electronic patient record of a particular patient and domain knowledge. As a result, the agent provides the doctor with literature that is relevant with respect to the patient at hand.

A mobile multi-agent system for distributed computing

The paper describes a peer-to-peer distributed-computing platform, called YACA, based on mobile agents. Next to the client agents, which seek computational resources in a cluster, YACA consists of four agents, who manage the computers within a cluster. (1) The Directory Agent keeps track of the computers belonging to the cluster. These computers are called nodes. (2) The Weather Agent monitors the resources of a node and (3) the Account Agent keeps track of the resources used by each client agent. (4) The Controller Agent controls the access to a node and migrates client agents to other nodes in the cluster if the node becomes overloaded. Experiments showed that yaca brings little overhead. However, its load balancing algorithm has room for improvements.

The ARCHIMEDES Network System: a system for searching and accessing information in multiplemultimedia sources

The amount of information available to information workers recently has becomeoverwhelming. This confronts information workers with two majorproblems: finding the information needed, and accessing it; they arecalled the search problem and the access problem, respectively. Asthe main result of our research an architecture is specified of anautomated tool that provides integrated support for searching andaccessing multimedia documents that may be located at arbitraryplaces. The architecture contains a database with information aboutthe documents and with thesaurus-like information. The architecturealso contains a browse mechanism and a query mechanism for inspectingthe database. In the design process of the architecture, severalfundamental questions arose, like “What is a document?”and “ What is a medium kind?”. The developed answers tosome of these questions are considered to have a general characterand thus to be useful also outside the scope of the research at hand.The paper concludes with an overview of the current status of theproject and a discussion of future work.