12,321 research outputs found

    Clustering the information space using top-ranking sentences : a study of user interaction

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    By considering sentences selected by a query-biased sentence extraction model from the top-retrieved documents, we create a personalised information space which is characterised by the presence of search terms. We cluster this information space, and enable searchers to interact with the resulting clusters. In order to examine whether users can recognise, and benefit from, the clustered organisation, we compare user interaction and performance between an actual clustering and a pseudo-clustering of the information space for completing information seeking tasks. The results provide evidence for the utility and meaningfulness of the clustered organisation

    Generating Aspect-oriented Multi-document Summarization with Event-Aspect Model

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    In this paper, we propose a novel approach to automatic generation of aspect-oriented summaries from multiple documents. We first develop an event-aspect LDA model to cluster sentences into aspects. We then use extended LexRank algorithm to rank the sentences in each cluster. We use Integer Linear Programming for sentence selection. Key features of our method include automatic grouping of semantically related sentences and sentence ranking based on extension of random walk model. Also, we implement a new sentence compression algorithm which use dependency tree instead of parser tree. We compare our method with four baseline methods. Quantitative evaluation based on Rouge metric demonstrates the effectiveness and advantages of our method.

    USFD at KBP 2011: Entity Linking, Slot Filling and Temporal Bounding

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    This paper describes the University of Sheffield's entry in the 2011 TAC KBP entity linking and slot filling tasks. We chose to participate in the monolingual entity linking task, the monolingual slot filling task and the temporal slot filling tasks. We set out to build a framework for experimentation with knowledge base population. This framework was created, and applied to multiple KBP tasks. We demonstrated that our proposed framework is effective and suitable for collaborative development efforts, as well as useful in a teaching environment. Finally we present results that, while very modest, provide improvements an order of magnitude greater than our 2010 attempt.Comment: Proc. Text Analysis Conference (2011
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