Warner ten Kate

Using Google distance to weight approximate ontology matches

Discovering mappings between concept hierarchies is widely regarded as one of the hardest and most urgent problems facing the Semantic Web. The problem is even harder in domains where concepts are inherently vague and ill-defined, and cannot be given a crisp definition. A notion of approximate concept mapping is required in such domains, but until now, no such notion is vailable. The first contribution of this paper is a definition for approximate mappings between concepts. Roughly, a mapping between two concepts is decomposed into a number of submappings, and a sloppiness value determines the fraction of these submappings that can be ignored when establishing the mapping. A potential problem of such a definition is that with an increasing sloppiness value, it will gradually allow mappings between any two arbitrary concepts. To improve on this trivial behaviour, we need to design a heuristic weighting which minimises the sloppiness required to conclude desirable matches, but at the same time maximises the sloppiness required to conclude undesirable matches. The second contribution of this paper is to show that a Google based similarity measure has exactly these desirable properties. We establish these results by experimental validation in the domain of musical genres. We show that this domain does suffer from ill-defined concepts. We take two real-life genre hierarchies from the Web, we compute approximate mappings between them at varying levels of sloppiness, and we validate our results against a handcrafted Gold Standard. Our method makes use of the huge amount of knowledge that is implicit in the current Web, and exploits this knowledge as a heuristic for establishing approximate mappings between ill-defined concepts.

Matching unstructured vocabularies using a background ontology

Existing ontology matching algorithms use a combination of lexical and structural correspondence between source and target ontologies. We present a realistic case-study where both types of overlap are low: matching two unstructured lists of vocabulary used to describe patients at Intensive Care Units in two different hospitals. We show that indeed existing matchers fail on our data. We then discuss the use of background knowledge in ontology matching problems. In particular, we discuss the case where the source and the target ontology are of poor semantics, such as flat lists, and where the background knowledge is of rich semantics, providing extensive descriptions of the properties of the concepts involved. We evaluate our results against a Gold Standard set of matches that we obtained from human experts.

trigg&link - A New Dimension in Television Program Making

The merge of internet and television broadcast is discussed at application level: how can internet contribute to television other than Web-surfing? Two main service types were identified. Both relate to television program making. The first refers to the hyperlinking nature of the internet. It led to the concept of trigg&link where a linear, non-interactive television program is enhanced into a linear (parallel), interactive program. The second refers to using internet services within the television program, where the internet services are on a higher level than plain Web-surfing. The enhancement they provide is found in the additional information, additional service, and enhanced programming available through the trigg&link principle. Basic services are combined into packaged services.

The link vs. the event: activating and deactivating elements in time-based hypermedia

Abstract Activation and deactivation of media items plays a fundamental role in the playing of multimedia and time-based hypermedia presentations. Activation and deactivation information thus has to be captured in an underlying document format. In this paper we show that a number of aspects of activation and deactivation information can be captured using both link structures and events in time-based hypermedia. In particular, we discuss how deactivation and activation can be specified, how the activations and deactivations can be initiated and potential (synchronization) relationships between the elements involved. We first introduce the notions of time-based scheduling and event-based scheduling and then present a short summary of linking. We discuss the similarities between event-based scheduling and linking. We describe a number of aspects of activation and deactivation that can be specified within a document. We then discuss how activation and deactivation information can be recorded in link structures and events.

Child-activity recognition from multi-sensor data

The automatic recognition of child activity using multi-sensor data enables various applications such as child-development monitoring, energy-expenditure estimation, child-obesity prevention, child safety in and around the home, etc. We formulate the activity recognition task as a classification problem based on multiple sensors embedded in a wearable device. The approach we propose in this paper isto apply spectral analysis techniques of multiple sensor data for activity recognition. Quadratic Discriminant Analysis (QDA) classifieris then trained using manually annotated data and applied for activity recognition. The obtained experimental results for the recognition of 7 activities based on a limited data set are promising and show the potential of the proposed method.

Presenting Multimedia on the Web and in TV Broadcast

This paper investigates the main issues related to the translation of SMIL into MHEG-5 documents. This is driven by the more general objective to achieve interoperability between the domains of Web and digital-TV, where MHEG-5 is used in the digital-TV environment and SMIL is the Web format to specify interactive synchronized multimedia presentations.

Bed exit prediction based on movement and posture data

Falls in nursing homes and hospitals take often place immediately after a bed exit of a patient. An alarm signaling the exit from the bed may already be too late for staff to react. In this paper we explore the possibilities of detecting the sequences of preparatory movements before the bed exit and in this way create an early warning of the preparation of bed exit. The method is described and tested using annotated accelerometer data collected from volunteers. A plausibility assessment is also done by comparing accelerometer data from hospital patients with the output of a bed alarm system. It is demonstrated that the proposed method is able to detect a bed exit already seconds before the patient actually leaves the bed.

Semantic Mapping by Approximation

We address the problem of semantic coordination, namely finding an agreement between the meanings of heterogeneous semantic models. We propose a new approximation method to discover and assess the “strength” (preciseness) of semantic mappings between different concept hierarchies. We apply this method in the music domain. We present the results of tests on mapping two music concept hierarchies from actual sites on the Internet.