Dublin City University at QA@CLEF 2008

We describe our participation in Multilingual Question Answering at CLEF 2008 using German and English as our source and target languages respectively. The system was built using UIMA (Unstructured Information Management Architecture) as underlying framework

A literature survey of methods for analysis of subjective language

Subjective language is used to express attitudes and opinions towards things, ideas and people. While content and topic centred natural language processing is now part of everyday life, analysis of subjective aspects of natural language have until recently been largely neglected by the research community. The explosive growth of personal blogs, consumer opinion sites and social network applications in the last years, have however created increased interest in subjective language analysis. This paper provides an overview of recent research conducted in the area

Stance Classification on PTT Comments

With the development of social media and online forums, users have grown accustomed to expressing their agreement and disagreement via short texts. Elements that reveal the user’s stance or subjectivity thus becomes an important resource in identifying the user’s position on a given topic. In the current study, we observe comments of an online bulletin board in Taiwan for how people express their stance when responding to other people’s post in Chinese. A lexicon is built based on linguistic analysis and annotation of the data. We performed binary classification task using these linguistic features and was able to reach an average of 71 percent accuracy. A linguistic analysis on the confusion caused in the classification task is done for future work on better accuracy for such task.

Ontology-based information extraction from learning management systems

In this work we present a system for information extraction from Learning Management Systems. This system is ontology-based. It retrieves information according to the structure of the ontology to populate the ontology. We graphically present statistics about the ontology data. These statistics present latent knowledge which is difficult to see in the traditional Learning Management System. To answer questions about the ontology, a question answering system was developed using Natural Language Processing in the conversion of the natural language question into an ontology query language; Sumário: Extração de Informação de Sistemas de Gestão para Educação Usando Ontologias Neste dissertação apresentamos um sistema de extracção de informação de sistemas de gestão para educação (Learning Management Systems). Este sistema é baseado em ontologias e extrai informação de acordo com a estrutura da ontologia para a popular. Também permite apresentar graficamente algumas estatísticas sobre os dados da ontologia. Estas estatísticas revelam o conhecimento latente que é difícil de ver num sistema tradicional de gestão para a educação. Para poder responder a perguntas sobre os dados da ontologia, um sistema de resposta automática a perguntas em língua natural foi desenvolvido usando Processamento de Língua Natural para converter as perguntas para linguagem de interrogação de ontologias