中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Extracting Variable-Depth Logical Document Hierarchy from Long Documents: Method, Evaluation, and Application

文献类型:期刊论文

作者Cao, Rong-Yu1,2; Cao, Yi-Xuan1,2; Zhou, Gan-Bin3; Luo, Ping1,2,4
刊名JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY
出版日期2022-06-01
卷号37期号:3页码:699-718
关键词logical document hierarchy long document passage retrieval
ISSN号1000-9000
DOI10.1007/s11390-021-1076-7
英文摘要In this paper, we study the problem of extracting variable-depth "logical document hierarchy" from long documents, namely organizing the recognized "physical document objects" into hierarchical structures. The discovery of logical document hierarchy is the vital step to support many downstream applications (e.g., passage-based retrieval and high-quality information extraction). However, long documents, containing hundreds or even thousands of pages and a variable-depth hierarchy, challenge the existing methods. To address these challenges, we develop a framework, namely Hierarchy Extraction from Long Document (HELD), where we "sequentially" insert each physical object at the proper position on the current tree. Determining whether each possible position is proper or not can be formulated as a binary classification problem. To further improve its effectiveness and efficiency, we study the design variants in HELD, including traversal orders of the insertion positions, heading extraction explicitly or implicitly, tolerance to insertion errors in predecessor steps, and so on. As for evaluations, we find that previous studies ignore the error that the depth of a node is correct while its path to the root is wrong. Since such mistakes may worsen the downstream applications seriously, a new measure is developed for a more careful evaluation. The empirical experiments based on thousands of long documents from Chinese financial market, English financial market and English scientific publication show that the HELD model with the "root-to-leaf" traversal order and explicit heading extraction is the best choice to achieve the tradeoff between effectiveness and efficiency with the accuracy of 0.972 6, 0.729 1 and 0.957 8 in the Chinese financial, English financial and arXiv datasets, respectively. Finally, we show that the logical document hierarchy can be employed to significantly improve the performance of the downstream passage retrieval task. In summary, we conduct a systematic study on this task in terms of methods, evaluations, and applications.
资助项目National Key Research and Development Program of China[2017YFB1002104] ; National Natural Science Foundation of China[62076231] ; National Natural Science Foundation of China[U1811461]
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000812520400015
出版者SCIENCE PRESS
源URL[http://119.78.100.204/handle/2XEOYT63/19530]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Cao, Rong-Yu
作者单位1.Chinese Acad Sci, Key Lab Intelligent Informat Proc, Inst Comp Technol, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Tencent Holdings Ltd, WeChat Search Applicat Dept, Beijing 100080, Peoples R China
4.Peng Cheng Lab, Shenzhen 518066, Peoples R China
推荐引用方式
GB/T 7714
Cao, Rong-Yu,Cao, Yi-Xuan,Zhou, Gan-Bin,et al. Extracting Variable-Depth Logical Document Hierarchy from Long Documents: Method, Evaluation, and Application[J]. JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY,2022,37(3):699-718.
APA Cao, Rong-Yu,Cao, Yi-Xuan,Zhou, Gan-Bin,&Luo, Ping.(2022).Extracting Variable-Depth Logical Document Hierarchy from Long Documents: Method, Evaluation, and Application.JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY,37(3),699-718.
MLA Cao, Rong-Yu,et al."Extracting Variable-Depth Logical Document Hierarchy from Long Documents: Method, Evaluation, and Application".JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY 37.3(2022):699-718.

入库方式: OAI收割

来源:计算技术研究所

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