The Library
Reflective writing analysis approach based on semantic concepts : an evaluation of WordNet affect efficiency
Tools
Tools
Tools
Alrashidi, Huda and Joy, Mike (2019) Reflective writing analysis approach based on semantic concepts : an evaluation of WordNet affect efficiency. In: Bi, Y. and Bhatia, R. and Kapoor, S., (eds.) Intelligent Systems and Applications. Cham: Springer, pp. 321-333. ISBN 9783030295127
|
PDF
WRAP-Reflective-writing-analysis-semantic-evaluation-WordNet-Joy-2019.pdf - Accepted Version - Requires a PDF viewer. Download (593Kb) | Preview |
Official URL: http://dx.doi.org/10.1007/978-3-030-29513-4_23
Abstract
Automatic analysis of reflective writing involves identifying indicator strings and using string matching or rule matching processes, which flag sections of a text containing reflective material. The problem with the string-based approach is its inability to deal with knowledge inference from the text, such as the content, context, relevance, clarity, and interconnection, which can be identified by semantic analysis. The semantic analysis depends mainly on mapping the text into stored knowledge sources, such as WordNet, and analyzing the associations in the underlying knowledge source. In this paper, a semantic-based approach for reflective writing analysis is proposed, in which the input text, which is being analyzed, is mapped into semantic concepts. Moreover, a machine learning (ML) approach for reflective writing identification and analysis has been implemented to overcome the limitations of rule execution and keyword matching. The proposed approach addresses the efficiency of using several effective concepts, correlated with effective words that are identified in WordNet-Affect. The input text is classified into reflective or non-reflective categories, after which the input text is classified into various reflective classes, based on the type of the document. Moreover, the concepts in WordNet-Affect are evaluated and analyzed to demonstrate their effects on classification and labeling tasks.
| Item Type: | Book Item | ||||||
|---|---|---|---|---|---|---|---|
| Subjects: | P Language and Literature > P Philology. Linguistics | ||||||
| Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | ||||||
| Library of Congress Subject Headings (LCSH): | Semantics -- Data processing, English language -- Data processing, English language -- Rhetoric -- Study and teaching -- Computer-assisted instruction, WordNet | ||||||
| Publisher: | Springer | ||||||
| Place of Publication: | Cham | ||||||
| ISBN: | 9783030295127 | ||||||
| ISSN: | 2194-5357 | ||||||
| Book Title: | Intelligent Systems and Applications | ||||||
| Editor: | Bi, Y. and Bhatia, R. and Kapoor, S. | ||||||
| Official Date: | 24 August 2019 | ||||||
| Dates: |
|
||||||
| Volume: | 1038 | ||||||
| Page Range: | pp. 321-333 | ||||||
| DOI: | 10.1007/978-3-030-29513-4_23 | ||||||
| Status: | Peer Reviewed | ||||||
| Publication Status: | Published | ||||||
| Reuse Statement (publisher, data, author rights): | This is a post-peer-review, pre-copyedit version of a chapter published in Intelligent Systems and Applications. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-3-030-29513-4_23 | ||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||
| Copyright Holders: | © Springer Nature Switzerland AG 2020 | ||||||
| RIOXX Funder/Project Grant: |
|
Request changes or add full text files to a record
Repository staff actions (login required)
 |
View Item |
Downloads
Downloads per month over past year
