{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T19:42:50Z","timestamp":1782243770650,"version":"3.54.5"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643685489","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,10,16]],"date-time":"2024-10-16T00:00:00Z","timestamp":1729036800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,10,16]]},"abstract":"<jats:p>Pre-trained language models are increasingly being used in multi-document summarization tasks. However, these models need large-scale corpora for pre-training and are domain-dependent. Other non-neural unsupervised summarization approaches mostly rely on key sentence extraction, which can lead to information loss. To address these challenges, we propose a lightweight yet effective unsupervised approach called GLIMMER: a Graph and LexIcal features based unsupervised Multi-docuMEnt summaRization approach. It first constructs a sentence graph from the source documents, then automatically identifies semantic clusters by mining low-level features from raw texts, thereby improving intra-cluster correlation and the fluency of generated sentences. Finally, it summarizes clusters into natural sentences. Experiments conducted on Multi-News, Multi-XScience and DUC-2004 demonstrate that our approach outperforms existing unsupervised approaches. Furthermore, it surpasses state-of-the-art pre-trained multi-document summarization models (e.g. PEGASUS and PRIMERA) under zero-shot settings in terms of ROUGE scores. Additionally, human evaluations indicate that summaries generated by GLIMMER achieve high readability and informativeness scores. Our code is available at https:\/\/github.com\/Oswald1997\/GLIMMER.<\/jats:p>","DOI":"10.3233\/faia240930","type":"book-chapter","created":{"date-parts":[[2024,10,17]],"date-time":"2024-10-17T13:43:10Z","timestamp":1729172590000},"source":"Crossref","is-referenced-by-count":3,"title":["GLIMMER: Incorporating Graph and Lexical Features in Unsupervised Multi-Document Summarization"],"prefix":"10.3233","author":[{"given":"Ran","family":"Liu","sequence":"first","affiliation":[{"name":"Institute of Information Engineering, Chinese Academy of Sciences"},{"name":"School of Cyber Security, University of Chinese Academy of Sciences"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ming","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Information Technology, Deakin University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Min","family":"Yu","sequence":"additional","affiliation":[{"name":"Institute of Information Engineering, Chinese Academy of Sciences"},{"name":"School of Cyber Security, University of Chinese Academy of Sciences"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianguo","family":"Jiang","sequence":"additional","affiliation":[{"name":"Institute of Information Engineering, Chinese Academy of Sciences"},{"name":"School of Cyber Security, University of Chinese Academy of Sciences"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gang","family":"Li","sequence":"additional","affiliation":[{"name":"School of Information Technology, Deakin University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dan","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Information Technology, Deakin University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingyuan","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Beijing Technology and Business University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiang","family":"Meng","sequence":"additional","affiliation":[{"name":"Institute of Information Engineering, Chinese Academy of Sciences"},{"name":"School of Cyber Security, University of Chinese Academy of Sciences"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weiqing","family":"Huang","sequence":"additional","affiliation":[{"name":"Institute of Information Engineering, Chinese Academy of Sciences"},{"name":"School of Cyber Security, University of Chinese Academy of Sciences"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","ECAI 2024"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA240930","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,17]],"date-time":"2024-10-17T13:43:10Z","timestamp":1729172590000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA240930"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,16]]},"ISBN":["9781643685489"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia240930","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,10,16]]}}}