We describe WHIRL, an \information representation language" that synergistically combines properties of logic-based and text-based representation systems. WHIRL is a subset of non-recursive Datalog that has been extended by introducing an atomic type for textual entities, an atomic operation for computing textual similarity, and a \soft" semantics; that is, inferences in WHIRL are associated wi...

This paper presents an approach to automatically mine rules in time series data representing physiological parameters in clinical conditions. The approach is fully data driven, where prototypical patterns are mined for each physiological time series data. The generated rules based on the prototypical patterns are then described in a textual representation which captures trends in each physiolog...

This paper describes the development of an information retrieval (IR) model for the indexing, storage and retrieval of documents created in extensible mark-up language (XML). The application area is the software reuse environment, which involves a broader class of documents than can be processed by conventional IR systems. This includes design and analysis documents in unified modelling languag...

We report on an approach to representation and retrieval of information from large textual databases. Our approach is based on dynamic ontologies that are automatically constructed from textual data by a new method combining techniques from knowledge representation, natural language processing, and machine learning. The method learns concepts automatically from documents, and uses them to build...

Ontology development is mostly directed at the representation of domain knowledge and much less at the representation of textual or image-based symbols for this knowledge, i.e., the multilingual and multimedia lexicon. To allow for automatic multilingual and multimedia knowledge markup, a richer representation of text and image features is needed. At present, such information is mostly missing ...

When representing textual documents by feature vectors for the purposes of further processing (e.g. for categorization, clustering, or visualization), one possible representation is based on “loose phrases” (also known as “proximity features”). This is a generalization of n-grams: a loose phrase is considered to appear in a document if all the words from the phrase occur sufficiently close to e...

Information Realisation is the process of presenting data as Textual, Graphical or Audial information to a human user. In this paper, we discuss the importance of this concept with respect to the accessibility of Semantic Web data to a diverse target audience. We provide an ontological point of view, defining the expressive characteristics and application domain of representation formats, thus ...

Continuous speech production is a highly complex process involving many parts of the human brain. To date, no fundamental representation that allows for decoding of continuous speech from neural signals has been presented. Here we show that techniques from automatic speech recognition can be applied to decode a textual representation of spoken words from neural signals. We model phones as the f...

The approaches for extraction and representation of knowledge from textual user requirements could be summarized in two groups: i) when we have in mind an end model and seek, mine and represent knowledge for it. In short, this approach can be defined as “knowledge driven from a target model”; ii) when we have in mind knowledge in a text, and seek an appropriate model to represent it. The interm...

Browsing multimedia collection on mobile devices raises the needs for new multimedia indexing solutions. In this paper, we focus on the management of personal image collections. We propose a method to simplify the browsing task on such a collection. The contributions reside in an incremental hierarchical algorithm, a method to provide a textual representation of the groups obtained and an algor...