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

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...

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Published in:	Electronic library Vol. 35; no. 1; pp. 99 - 120
Main Authors:	Wang, Zhongyi, Zhang, Jin, Huang, Jing
Format:	Journal Article
Language:	English
Published:	Oxford Emerald Publishing Limited 01.01.2017 Emerald Group Publishing Limited
Subjects:	Access Algorithms Cohesion Computerized corpora Cues Digital libraries Digital systems Electronic Libraries Hierarchies Image segmentation Information overload Information retrieval Libraries Library resources Library users Linguistics Literature Reviews Methods Morphemes Parsing Relevance Repetition Resources Retrieval Retrieval performance measures Segmentation Segments Semantics Semiotics Sentences Sequences Spelling Structural hierarchy Studies Syntax Text editing Text processing (Computer science) Topic and comment New York United States > US China Access structures Digital library resources Hierarchical segmentation Lexical cohesion Structured segmentation AIC Optimum partitioning clustering
ISSN:	0264-0473, 1758-616X, 1758-616X
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Abstract	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 system (MHTSS) to decide section breaks. Design/methodology/approach MHTSS adopts up-down segmentation strategy to divide a structured, digital library document into a document segmentation tree. Specifically, it works in a three-stage process, such as document parsing, coarse segmentation based on document access structures and fine-grained segmentation based on lexical cohesion. Findings This paper analyzed limitations of document segmentation methods for the structured, digital library resources. Authors found that the combination of document access structures and lexical cohesion techniques should complement each other and allow for a better segmentation of structured, digital library resources. Based on this finding, this paper proposed the MHTSS for the structured, digital library resources. To evaluate it, MHTSS was compared to the TT and C99 algorithms on real-world digital library corpora. Through comparison, it was found that the MHTSS achieves top overall performance. Practical implications With MHTSS, digital library users can get their relevant information directly in segments instead of receiving the whole document. This will improve retrieval performance as well as dramatically reduce information overload. Originality/value This paper proposed MHTSS for the structured, digital library resources, which combines the document access structures and lexical cohesion techniques to decide section breaks. With this system, end-users can access a document by sections through a document structure tree.
AbstractList	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 system (MHTSS) to decide section breaks. Design/methodology/approach MHTSS adopts up-down segmentation strategy to divide a structured, digital library document into a document segmentation tree. Specifically, it works in a three-stage process, such as document parsing, coarse segmentation based on document access structures and fine-grained segmentation based on lexical cohesion. Findings This paper analyzed limitations of document segmentation methods for the structured, digital library resources. Authors found that the combination of document access structures and lexical cohesion techniques should complement each other and allow for a better segmentation of structured, digital library resources. Based on this finding, this paper proposed the MHTSS for the structured, digital library resources. To evaluate it, MHTSS was compared to the TT and C99 algorithms on real-world digital library corpora. Through comparison, it was found that the MHTSS achieves top overall performance. Practical implications With MHTSS, digital library users can get their relevant information directly in segments instead of receiving the whole document. This will improve retrieval performance as well as dramatically reduce information overload. Originality/value This paper proposed MHTSS for the structured, digital library resources, which combines the document access structures and lexical cohesion techniques to decide section breaks. With this system, end-users can access a document by sections through a document structure tree. 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 system (MHTSS) to decide section breaks. Design/methodology/approach MHTSS adopts up-down segmentation strategy to divide a structured, digital library document into a document segmentation tree. Specifically, it works in a three-stage process, such as document parsing, coarse segmentation based on document access structures and fine-grained segmentation based on lexical cohesion. Findings This paper analyzed limitations of document segmentation methods for the structured, digital library resources. Authors found that the combination of document access structures and lexical cohesion techniques should complement each other and allow for a better segmentation of structured, digital library resources. Based on this finding, this paper proposed the MHTSS for the structured, digital library resources. To evaluate it, MHTSS was compared to the TT and C99 algorithms on real-world digital library corpora. Through comparison, it was found that the MHTSS achieves top overall performance. Practical implications With MHTSS, digital library users can get their relevant information directly in segments instead of receiving the whole document. This will improve retrieval performance as well as dramatically reduce information overload. Originality/value This paper proposed MHTSS for the structured, digital library resources, which combines the document access structures and lexical cohesion techniques to decide section breaks. With this system, end-users can access a document by sections through a document structure tree. Proposes a new multi-granularity hierarchical topic-based segmentation system (MHTSS) to decide section breaks in coherent texts such as documents of a digital library which have hierarchical structures. Source: National Library of New Zealand Te Puna Matauranga o Aotearoa, licensed by the Department of Internal Affairs for re-use under the Creative Commons Attribution 3.0 New Zealand Licence.
Author	Zhang, Jin Huang, Jing Wang, Zhongyi
Author_xml	– sequence: 1 givenname: Zhongyi surname: Wang fullname: Wang, Zhongyi email: wzywzy13579@163.com – sequence: 2 givenname: Jin surname: Zhang fullname: Zhang, Jin email: jinzhanguwm@gmail.com – sequence: 3 givenname: Jing surname: Huang fullname: Huang, Jing email: huangjing8117@163.com
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Snippet	Purpose Current segmentation systems almost invariably focus on linear segmentation and can only divide text into linear sequences of segments. This suits... Proposes a new multi-granularity hierarchical topic-based segmentation system (MHTSS) to decide section breaks in coherent texts such as documents of a digital... Purpose Current segmentation systems almost invariably focus on linear segmentation and can only divide text into linear sequences of segments. This suits...
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SubjectTerms	Access Algorithms Cohesion Computerized corpora Cues Digital libraries Digital systems Electronic Libraries Hierarchies Image segmentation Information overload Information retrieval Libraries Library resources Library users Linguistics Literature Reviews Methods Morphemes Parsing Relevance Repetition Resources Retrieval Retrieval performance measures Segmentation Segments Semantics Semiotics Sentences Sequences Spelling Structural hierarchy Studies Syntax Text editing Text processing (Computer science) Topic and comment
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