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...

Full description

Saved in:
Bibliographic Details
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
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
Bibliography:Includes illustrations, references, tables
Includes links to related electronic resources
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0264-0473
1758-616X
1758-616X
DOI:10.1108/EL-06-2015-0108