Semantic Computing

Connecting Wikis and Natural Language Processing Systems

Palais de Congres, Montreal, Canada


We investigate the integration of Wiki systems with automated natural language processing (NLP) techniques. The vision is that of a "self-aware" Wiki system reading, understanding, transforming, and writing its own content, as well as supporting its users in information analysis and content development. We provide a number of practical application examples, including index generation, question answering, and automatic summarization, which demonstrate the practicability and usefulness of this idea. A system architecture providing the integration is presented, as well as first results from an initial implementation based on the GATE framework for NLP and the MediaWiki system.

General Terms: Design, Human Factors, Languages
Keywords: Self-aware Wiki System, Wiki/NLP Integration

An Integration Architecture for User-Centric Document Creation, Retrieval, and Analysis



The different stages in the life-cycle of content—creation, storage, retrieval, and analysis—are usually regarded as distinct and isolated steps. In this paper we examine the synergies resulting from their integration within a single architecture.

Our goal is to employ such an architecture to improve user support for knowledge-intensive tasks. We present a case study from the area of building architecture, which is currently ongoing.

Engineering a Semantic Desktop for Building Historians and Architects

Page scan from 'Handbuch der Architektur'


We analyse the requirements for an advanced semantic support of users—building historians and architects—of a multi-volume encyclopedia of architecture from the late 19th century. Novel requirements include the integration of content retrieval, content development, and automated content analysis based on natural language processing.

We present a system architecture for the detected requirements and its current implementation. A complex scenario demonstrates how a desktop supporting semantic analysis can contribute to specific, relevant user tasks.

The FungalWeb Ontology: Application Scenarios


The FungalWeb Ontology aims to support the data integration needs of enzyme biotechnology from inception to product roll out. Serving as a knowledge base for decision support, the conceptualization seeks to link fungal species with enzymes, enzyme substrates, enzyme classifications, enzyme modifications, enzyme retail and applications. We demonstrate how the FungalWeb Ontology supports this remit by presenting application scenarios, conceptualizations of the ontological frame able to support these scenarios and semantic queries typical of a Biotech Manager. Queries to the knowledge base are answered with description logic (DL) and automated reasoning tools.

A Context-Driven Software Comprehension Process Model


Comprehension is an essential part of software evolution. Only software that is well understood can evolve in a controlled manner. In this paper, we present a formal process model to support the comprehension of software systems by using Ontology and Description Logic. This formal representation supports the use of reasoning services across different knowl- edge resources and therefore, enables us to provide users with guidance during the comprehension process that is context sensitive to their particular comprehension task. As part of the process model, we also adopt a new interactive story metaphor, to represent the interactions between users and the comprehension process.

Keywords: Software evolution, program comprehension, process modeling, story metaphor, ontological reasoning

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