{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,17]],"date-time":"2025-09-17T15:52:43Z","timestamp":1758124363786},"reference-count":0,"publisher":"National Library of Serbia","issue":"3","license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["ComSIS","COMPUT SCI INF SYST","COMPUT SCI INFORM SY","COMPUTER SCI INFORM","COMSIS J"],"published-print":{"date-parts":[[2018]]},"abstract":"<jats:p>Automatic question generation from text or paragraph is a great challenging task which attracts broad attention in natural language processing. Because of the verbose texts and fragile ranking methods, the quality of top generated questions is poor. In this paper, we present a novel framework Automatic Chinese Question Generation (ACQG) to generate questions from text or paragraph. In ACQG, we use an adopted TextRank to extract key sentences and a template-based method to construct questions from key sentences. Then a multi-feature neural network model is built for ranking to obtain the top questions. The automatic evaluation result reveals that the proposed framework outperforms the state-of-the-art systems in terms of perplexity. In human evaluation, questions generated by ACQG rate a higher score.<\/jats:p>","DOI":"10.2298\/csis171121018z","type":"journal-article","created":{"date-parts":[[2018,9,21]],"date-time":"2018-09-21T10:22:52Z","timestamp":1537525372000},"page":"487-499","source":"Crossref","is-referenced-by-count":11,"title":["A novel framework for Automatic Chinese Question Generation based on multi-feature neural network model"],"prefix":"10.2298","volume":"15","author":[{"given":"Hai-Tao","family":"Zheng","sequence":"first","affiliation":[{"name":"Graduate School at Shenzhen Tsinghua University China, Shenzhen"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinxin","family":"Han","sequence":"additional","affiliation":[{"name":"Graduate School at Shenzhen Tsinghua University China, Shenzhen"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinyuan","family":"Chen","sequence":"additional","affiliation":[{"name":"Graduate School at Shenzhen Tsinghua University China, Shenzhen"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"suffix":"Kumar","given":"Arun","family":"Sangaiah","sequence":"additional","affiliation":[{"name":"School of Computing Science and Engineering VIT University India, Tamil Nadu Vellore"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1078","container-title":["Computer Science and Information Systems"],"original-title":[],"language":"en","deposited":{"date-parts":[[2023,5,29]],"date-time":"2023-05-29T08:33:31Z","timestamp":1685349211000},"score":1,"resource":{"primary":{"URL":"https:\/\/doiserbia.nb.rs\/Article.aspx?ID=1820-02141800018Z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"references-count":0,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2018]]}},"URL":"https:\/\/doi.org\/10.2298\/csis171121018z","relation":{},"ISSN":["1820-0214","2406-1018"],"issn-type":[{"value":"1820-0214","type":"print"},{"value":"2406-1018","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018]]}}}