| 書目名稱 | Cohesive Subgraph Search Over Large Heterogeneous Information Networks | | 編輯 | Yixiang Fang,Kai Wang,Wenjie Zhang | | 視頻video | http://file.papertrans.cn/230/229242/229242.mp4 | | 叢書名稱 | SpringerBriefs in Computer Science | | 圖書封面 |  | | 描述 | .This SpringerBrief provides the first systematic review of the existing works of cohesive subgraph search (CSS) over large heterogeneous information networks (HINs). It also covers the research breakthroughs of this area, including models, algorithms and comparison studies in recent years. This SpringerBrief offers a list of promising future research directions of performing CSS over large HINs..The authors first classify the existing works of CSS over HINs according to the classic cohesiveness metrics such as core, truss, clique, connectivity, density, etc., and then extensively review the specific models and their corresponding search solutions in each group. Note that since the bipartite network is a special case of HINs, all the models developed for general HINs can be directly applied to bipartite networks, but the models customized for bipartite networks may not be easily extended for other general HINs due to their restricted settings. The authors also analyze and compare these cohesive subgraph models (CSMs) and solutions systematically. Specifically, the authors compare different groups of CSMs and analyze both their similarities and differences, from multiple perspective | | 出版日期 | Book 2022 | | 關鍵詞 | cohesive subgraph search; heterogeneous information networks; heterogeneous graphs; dense subgraphs; gra | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-030-97568-5 | | isbn_softcover | 978-3-030-97567-8 | | isbn_ebook | 978-3-030-97568-5Series ISSN 2191-5768 Series E-ISSN 2191-5776 | | issn_series | 2191-5768 | | copyright | The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 |
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