Alexander Troussov

Navigating and Annotating Semantically-Enabled Networks of People and Associated Objects

Social spaces such as blogs, wikis and online social networking sites are enabling the formation of online communities where people are linked to each other through direct profile connections and also through the content items that they are creating, sharing and tagging. As these spaces become bigger and more distributed, more intuitive ways of navigating the associated information become necessary. The Semantic Web aims to link identifiable objects to each other and to textual strings via relationships and attributes respectively, and provides a platform for gathering diverse information from heterogeneous sources and performing operations on such linked data. In this paper, we will demonstrate how this linked semantic data can provide an enhanced view of the activity in a social network, and how the Galaxy tool described in this work can augment objects from social spaces, by highlighting related people and objects, and suggesting relevant sources of knowledge.

A linguistic light approach to multilingualism in lexical layers for ontologies

Semantic Web ontologies are being increasingly used in modern text analytics applications and ontology-based information extraction (OBIE) as a means to provide a semantic backbone either for modelling the internal conceptual data structures of the text analytics (TA) engine or to model the knowledge base to drive the analysis of unstructured information in raw text and subsequent Knowledge acquisition and population. creating and targeting language resources (LR)s from a TA to an ontology can be time consuming and costly.The authors describe a user-friendly method for ontology engineers to augment an ontologies with a lexical layer which provides a flexible framework to identify term mentions of ontology concepts in raw text. In this paper we explore multilinguality in these lexical layers using the same framework. We discuss a number of potential issues for the ldquolinguistic lightrdquo lexical extensions for ontologies (LEON) approach when looking at languages more morphologically rich and which have more complex linguistic constraints than English. We show how the LEON approach can cope with these phenomena once the morphological normaliser used in the lexical analysis process is able to generalise sufficiently well for the language concerned.