Hakan Sundblad

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In this paper we propose an architecture for dialogue systems that incorporate information extraction, thereby providing natural and efficient access to unstructured information sources. A key feature of the architecture is the use of ontologies as shared domain knowledge sources. We discuss how ontologies can be used for various tasks. with focus on(More)
This paper presents a re-examiniation of previous work on machine learning techniques for questions classification, as well as results from new experiments. The results suggest that some of the work done in the field have yielded biased results. The results also suggest that Naı̈ve Bayes, Decision Trees and Support Vector Machines perform on par with each(More)
Question answering systems can be seen as the next step in information retrieval, allowing users to pose questions in natural language and receive succinct answers. In order for a question answering system as a whole to be successful, research has shown that the correct classification of questions with regards to the expected answer type is imperative.(More)
This paper reviews plan-based models of dialogue. The original model is thoroughly presented. Important developments of the original model are also presented. Finally, benefits and drawbacks of plan-based approaches to dialogue modelling are discussed. Introduction Plan-based dialogue models have since long earned their place in works intended to present(More)
As technology developed the use of internet has tremendously increased because of the availability of huge amount of data. Question answering is a specialized area in the field of information retrieval Text Processing. Question Answering system has many application based on source of answering like extracting information from document, language learning,(More)
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