Text Document Clustering Approach by Improved Sine Cosine Algorithm
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18470%2F23%3A50022533" target="_blank" >RIV/62690094:18470/23:50022533 - isvavai.cz</a>
Result on the web
<a href="https://itc.ktu.lt/index.php/ITC/article/view/33536" target="_blank" >https://itc.ktu.lt/index.php/ITC/article/view/33536</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.5755/j01.itc.52.2.33536" target="_blank" >10.5755/j01.itc.52.2.33536</a>
Alternative languages
Result language
angličtina
Original language name
Text Document Clustering Approach by Improved Sine Cosine Algorithm
Original language description
Due to the vast amounts of textual data available in various forms such as online content, social media comments, corporate data, public e-services and media data, text clustering has been experiencing rapid development. Text clustering involves categorizing and grouping similar content. It is a process of identifying significant patterns from unstructured textual data. Algorithms are being developed globally to extract useful and relevant information from large amounts of text data. Measuring the significance of content in documents to partition the collection of text data is one of the most important obstacles in text clustering. This study suggests utilizing an improved metaheuristics algorithm to fine-tune the K-means approach for text clustering task. The suggested technique is evaluated using the first 30 unconstrained test functions from the CEC2017 test-suite and six standard criterion text datasets. The simulation results and comparison with existing techniques demonstrate the robustness and supremacy of the suggested method.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
INFORMATION TECHNOLOGY AND CONTROL
ISSN
1392-124X
e-ISSN
1392-124X
Volume of the periodical
52
Issue of the periodical within the volume
2
Country of publishing house
LT - LITHUANIA
Number of pages
21
Pages from-to
541-561
UT code for WoS article
001091788500021
EID of the result in the Scopus database
2-s2.0-85168718410