KeyWorld:Extracting Keywords from Document s Small World

Matsuo, Yutaka; Ohsawa, Yukio; Ishizuka, Mitsuru

doi:10.1007/3-540-45650-3_24

Cited by 43 publications

(47 citation statements)

References 7 publications

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“…Lots of further work will be under exploration, such as expert group detection by considering the working location of TCM masters, consideration of more semantic meanings of keywords, such as origins or background of the thoughts, concerned patterns or syndromes, treating methods and principles or prescriptions in correspondence analysis, etc. It is also worth adopting or comparing with others' ideas [20] . Exploring a new linkage may be more difficult to be validated at TCM field.…”

Section: Discussionmentioning

confidence: 99%

Exploration of TCM Masters Knowledge Mining

Tang

Zhang

Wang

2008

J. Syst. Sci. Complex.

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Traditional Chinese medicine (TCM) has a rich knowledge about human health and disease by its special way evolved along a very long history. As modern medicine is achieving much progress, arguments and disputes toward TCM never end. To avoid losing precious knowledge of living TCM masters, endeavors have been engaged to systematic collection of those knowledge of TCM masters, such as their growth experiences, effective practical cases toward diseases and typical therapeutic principles and methods. Knowledge mining methods have been expected to explore some useful or hidden patterns to unveil some mysteries of the TCM system. In the paper, some computerized methods are applied toward those collected materials about some living TCM masters in China mainland to show a different way of exposing essential ideas of those TCM masters by correspondence visualization which aims to help people understand TCM holistic views toward disease and body, and facilitate tacit knowledge transfer and sense-making of the essence of TCM. The work is one kind of qualitative meta-synthesis of TCM masters' knowledge.

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Section: Discussionmentioning

confidence: 99%

Exploration of TCM Masters Knowledge Mining

Tang

Zhang

Wang

2008

J. Syst. Sci. Complex.

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“…Graph-based text summarization is another effective and popular field of research [11] [15][16][17]. In the graphbased model, various approaches and methodologies have been found to find the links between the sentences and the keyphrases.…”

Section: Related Workmentioning

confidence: 99%

An Efficient Approach for Keyphrase Extraction from English Document

Emu¹,

Ahmed²,

Islam³

et al. 2017

IJISA

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“…Based on the path lengths the significance of words is evaluated. Matsuo et al [13] have proposed Keyworld, as an extension of Small World concept by utilizing inverse document frequency.…”

Section: Related Workmentioning

confidence: 99%

A Keyword Extraction Approach for Single Document Extractive Summarization Based on Topic Centrality

Ravinuthala¹,

Chinnam²

2017

IJIES

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Graph based keyword extraction approaches represent the text document as a graph with the words as vertices. An edge between two vertices exists only if the corresponding words are related. The effectiveness of the graph representation is dependent on how the relationship is defined between two words. Early approaches used word order, word co-occurrence and syntactic relationships. Recent graph representation approaches are using lexical association measures for defining relationship between two words. The existing relationships can only help in identifying the words which form the

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KeyWorld:Extracting Keywords from Document s Small World

Cited by 43 publications

References 7 publications

Exploration of TCM Masters Knowledge Mining

Exploration of TCM Masters Knowledge Mining

An Efficient Approach for Keyphrase Extraction from English Document

A Keyword Extraction Approach for Single Document Extractive Summarization Based on Topic Centrality

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