Pedro Mota

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In this paper we target Natural Language Understanding in the context of Conversational Agents that answer questions about their topics of expertise, and have in their knowledge base question/answer pairs, limiting the understanding problem to the task of finding the question in the knowledge base that will trigger the most appropriate answer to a given(More)
In this paper we propose a graph-community detection approach to identify cross-document relationships at the topic segment level. Given a set of related documents, we automatically find these relationships by clustering segments with similar content (topics). In this context, we study how different weighting mechanisms influence the discovery of word(More)
Acknowledgements I would like to thank my supervisor Luís Veiga for all the effort he has put on helping me complete this work, which proved to be a worthy and ever too interesting challenge, but not impossible. I would also like to thank all the Distributed Systems Group students and professors from INESC-ID which helped me along the way, providing useful(More)
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