Paul Buitelaar

RelExt : a tool for relation extraction from text in ontology extension

Domain ontologies very rarely model verbs as relations holding between concepts. However, the role of the verb as a central connecting element between concepts is undeniable. Verbs specify the interaction between the participants of some action or event by expressing relations between them. In parallel, it can be argued from an ontology engineering point of view that verbs express a relation between two classes that specify domain and range. The work described here is concerned with relation extraction for ontology extension along these lines. We describe a system (RelExt) that is capable of automatically identifying highly relevant triples (pairs of concepts connected by a relation) over concepts from an existing ontology. RelExt works by extracting relevant verbs and their grammatical arguments (i.e. terms) from a domain-specific text collection and computing corresponding relations through a combination of linguistic and statistical processing. The paper includes a detailed description of the system architecture and evaluation results on a constructed benchmark. RelExt has been developed in the context of the SmartWeb project, which aims at providing intelligent information services via mobile broadband devices on the FIFA World Cup that will be hosted in Germany in 2006. Such services include location based navigational information as well as question answering in the football domain.

Semantic annotation for concept-based cross-language medical information retrieval

We present a framework for concept-based cross-language information retrieval in the medical domain, which is under development in the MUCHMORE project. Our approach is based on using the Unified Medical Language System (UMLS) as the primary source of semantic data. Documents and queries are annotated with multiple layers of linguistic information. Linguistic processing includes part-of-speech tagging, morphological analysis, phrase recognition and the identification of medical terms and semantic relations between them. The paper describes experiments in monolingual and cross-language document retrieval, performed on a corpus of medical abstracts. Results show that linguistic processing, especially lemmatization and compound analysis for German, is a crucial step in achieving a good baseline performance. On the other hand, they show that semantic information, specifically the combined use of concepts and relations, increases the performance in monolingual and cross-language retrieval.

The Multilingual Semantic Web (Dagstuhl Seminar 12362)

This document constitutes a brief report from the Dagstuhl Seminar on the Multilingual Semantic Web which took place at Schloss Dagstuhl between September 3rd and 7th, 2012. The document states the motivation for the workshop as well as the main thematic focus. It describes the organization and structure of the seminar and briefly reports on the main topics of discussion and the main outcomes of the workshop.

A cross-language document retrieval system based on semantic annotation

The paper describes a cross-lingual document retrieval system in the medical domain that employs a controlled vocabulary (UMLS1) in constructing an XML-based intermediary representation into which queries as well as documents are mapped. The system assists in the retrieval of English and German medical scientific abstracts relevant to a German query document (electronic patient record). The modularity of the system allows for deployment in other domains, given appropriate linguistic and semantic resources.