MATEC Web Conf.
Volume 189, 20182018 2nd International Conference on Material Engineering and Advanced Manufacturing Technology (MEAMT 2018)
|Number of page(s)||6|
|Section||Cloud & Network|
|Published online||10 August 2018|
The use of additional evidence in mining usercreated descriptions for content structural design
Department of Library and Information Studies, The University of the West Indies, Mona, Kingston, Jamaica
* Corresponding author: Yan.firstname.lastname@example.org
The use of a text mining approach for full automatic taxonomy creation for content management has proven with serious limitations. The high level semantics indicating relevant association of entities among the documents are often not explored. This study introduces a feasible method that allows identifying high level semantics into text mining procedures while providing for appropriate levels of document descriptions to support access and discoverability. Due to the effectiveness of categorization and adequacy of the structure created can be better determined by humans who are familiar to the documents, qualitative inquiry rather than a purely experimental design was applied. The study collected the data and run the text mining analysis with text analysis, clustering and topic extraction. Two examples show how to develop a faceted classification structure to support digital collection access and navigation using the method. The study indicates that the text-mining method supports taxonomy creation with more efficiency and accuracy when human domain and application knowledge are captured during data collection and text mining processing. The proposed method of taxonomy creation would support the creation of new knowledge.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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