Abstract
Through the widely-spread of digital devices such as smartphone, the digital books have become more popular. This research investigated the abstract required before resuming the reading. Through the survey, it seemed that the words that have a climax just before the bookmark is important for the abstract. We propose an elemental method to generate dynamic abstracts for each reading progress based on the results of the survey. The proposed method focuses on the local variation of word importance, though some existing criterions for summarization focus on the overall word importance. We prepared four types of local variation and compared the effectiveness of those with each other. The experiment to detect words accepted to manually-generated dynamic abstracts was conducted with each types of the proposed method while the general word importance criterion (tf-idf) is used as the comparative method. Through the discussions of the results, it was confirmed that some types of the proposed method were more effective to detect the words accepted to dynamic abstracts than the comparative method.
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Notes
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The ranking of XHTML ver. in the whole year of 2016. There are all 13,969 novels, as of 2016.12.31.
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The ranking of XHTML ver. in the whole year of 2016. There are all 13,969 novels, as of 2016.12.31.
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Acknowledgements
This work was supported in part by JSPS Grant-in-Aid for Young Scientists B #16K21482.
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Mori, H., Yamanishi, R., Nishihara, Y. (2020). Important Index of Words for Dynamic Abstracts Based on Surveying Reading Behavior. In: Ao, SI., Kim, H., Castillo, O., Chan, As., Katagiri, H. (eds) Transactions on Engineering Technologies. IMECS 2018. Springer, Singapore. https://doi.org/10.1007/978-981-32-9808-8_18
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DOI: https://doi.org/10.1007/978-981-32-9808-8_18
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