Abstract
In Chap. 1, multi-document summarization is introduced as a potential solution to the information explosion problem. A major challenge in creating a summary from information extracted from multiple sources is to decide the order in which those information must be presented in the summary. Incorrect ordering of information selected from multiple sources would lead to misunderstandings. In this chapter, we discuss the challenges involved when ordering information selected from multiple sources and present several approaches to overcome those challenges. We also introduce several semi-automatic evaluation measures to empirically evaluate an ordering of sentences created by an algorithm.
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Notes
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Using the frequencies of words instead of the binary (0, 1) values as vector elements, did not have a positive impact in our experiments. We think this is because, compared to a document, a sentence typically has a lesser number of words, and a word does not appear many times in a single sentence.
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Bollegala, D., Okazaki, N., Ishizuka, M. (2013). A Bottom-Up Approach to Sentence Ordering for Multi-Document Summarization. In: Poibeau, T., Saggion, H., Piskorski, J., Yangarber, R. (eds) Multi-source, Multilingual Information Extraction and Summarization. Theory and Applications of Natural Language Processing. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28569-1_12
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