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Multi-granularity hierarchical topic-based segmentation of structured, digital library resources

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成果类型:
期刊论文
作者:
Wang, Zhongyi;Zhang, Jin;Huang, Jing*
通讯作者:
Huang, Jing
作者机构:
[Wang, Zhongyi] Cent China Normal Univ, Sch Informat Management, Wuhan, HuBei Province, Peoples R China.
[Zhang, Jin] Univ Wisconsin, Sch Informat Studies, Milwaukee, WI 53201 USA.
[Huang, Jing] Wuhan Polytech, Wuhan, HuBei Province, Peoples R China.
通讯机构:
[Huang, Jing] W
Wuhan Polytech, Wuhan, HuBei Province, Peoples R China.
语种:
英文
关键词:
Hierarchical segmentation;Access structures;AIC;Digital library resources;Lexical cohesion;Optimum partitioning clustering;Structured segmentation
期刊:
ELECTRONIC LIBRARY
ISSN:
0264-0473
年:
2017
卷:
35
期:
1
页码:
99-120
基金类别:
This study is supported by National Social Science Foundation of China: “Research on Multi-granularity Integration Knowledge Services of Digital Library Based on Linked Data” (14CTQ003).
机构署名:
本校为第一机构
院系归属:
信息管理学院
摘要:
Purpose - Current segmentation systems almost invariably focus on linear segmentation and can only divide text into linear sequences of segments. This suits cohesive text such as news feed but not coherent texts such as documents of a digital library which have hierarchical structures. To overcome the focus on linear segmentation in document segmentation and to realize the purpose of hierarchical segmentation for a digital library's structured resources, this paper aimed to propose a new multi-granularity hierarchical topic-based segmentation s...

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