Abstract
Automatic text summarization is a very complex problem. Despite being intensively researched, automatic summaries are still considered to be of lower quality than manual summaries. This paper introduces a novel HCI approach to web page summarization. The proposed Crowd-Copy Summarizer follows the extractive text summarization approach of summarizing by selecting sentences within the text. The selection is performed by examining how frequently users copy certain sentences to their clipboards, for their own purposes. The most frequently copied sentences are included in the summary. Results from an early experiment are promising, as key sentences, such as introductory sentences, definitions, and important highlights, are copied frequently. Consequently, the generated summaries can provide good coverage of the main topics. This novel text summarization approach combines the best of both worlds: summarization based on collective human wisdom, without the expensive burden of manual summarization work.
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Kirsh, I., Joy, M. (2020). An HCI Approach to Extractive Text Summarization: Selecting Key Sentences Based on User Copy Operations. In: Stephanidis, C., Antona, M., Ntoa, S. (eds) HCI International 2020 – Late Breaking Posters. HCII 2020. Communications in Computer and Information Science, vol 1293. Springer, Cham. https://doi.org/10.1007/978-3-030-60700-5_43
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