Text Analytics for Android Project

Kaklauskas, Artūras; Seniut, Mark; Amaratunga, Rdg; Lill, Irene; Safonov, Andrej; Vatin, Nikolai Ivanovich; Cerkauskas, Justas; Jackute, Ieva; Kuzminske, Agne; Peciure, Lina

doi:10.1016/s2212-5671(14)00982-4

Cited by 9 publications

(7 citation statements)

References 10 publications

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“…Provisions of a personalized, friendly learning environment seem to constitute a key trend when it comes to developments relevant to Intelligent Tutoring Systems (ITSs) (Mao & Li, 2010). This research integrates Damasio's Somatic marker hypothesis (Damasio, 1994), Text Mining (Kaklauskas et al, 2014), DAM, CODEC, COPRAS and DUMA methods (Kaklauskas, 2015), biometric methods and systems (Kaklauskas et al, 2018a;Kaklauskas, 2015) and multiple criteria analysis methods and decision support systems (Kaklauskas, 2015;Kaklauskas, 2016, Kaklauskas, 1999.…”

Section: Research Backgroundmentioning

confidence: 99%

Affect-Based, Multimodal, Video Tutoring System for a Neuromarketing

Kaklauskas

Ubarte

Bučinskas

et al. 2020

mijst

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Considerable research has been conducted globally showing how study results are substantially conditional to the interest and productivity of a learner in the studies and the emotions and stress the learner experiences. Scholars emphasize that learning should be pleasing, enticing, and emotionally positive leading to increased effectiveness of the studying. Tests were conducted regarding the effectiveness of the MSc Property management studies process among students. Development of the ARTSY Model involved five iterative phases over the course of the research. ARTSY Model, intelligent

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Section: Research Backgroundmentioning

confidence: 99%

Affect-Based, Multimodal, Video Tutoring System for a Neuromarketing

Kaklauskas

Ubarte

Bučinskas

et al. 2020

mijst

Self Cite

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“…It is difficult to categorize the documents when collection of document is large and generated from diverse fields having the same domain. Abbreviations gives changed meaning in different situation is also a big issue [35]. Varying concepts of granularity change the context of text according to the condition and domain knowledge.…”

Section: Issues In Text Mining Fieldmentioning

confidence: 99%

Text Mining: Techniques, Applications and Issues

Talib¹,

Hanif²,

Ayesha³

et al. 2016

ijacsa

142

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Abstract-Rapid progress in digital data acquisition techniques have led to huge volume of data. More than 80 percent of today's data is composed of unstructured or semi-structured data. The discovery of appropriate patterns and trends to analyze the text documents from massive volume of data is a big issue. Text mining is a process of extracting interesting and nontrivial patterns from huge amount of text documents. There exist different techniques and tools to mine the text and discover valuable information for future prediction and decision making process. The selection of right and appropriate text mining technique helps to enhance the speed and decreases the time and effort required to extract valuable information. This paper briefly discuss and analyze the text mining techniques and their applications in diverse fields of life. Moreover, the issues in the field of text mining that affect the accuracy and relevance of results are identified.

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“…Can words used and attitudes expressed in reviews by housing market analysts correlate with changes the housing market is undergoing? We use text analytics (Kaklauskas, 2015;Kaklauskas et al, 2014) to identify and extract information on residential property prices from different online fi nancial reviews. Our goal is to defi ne the approach of an observer with respect to housing prices and discover patterns in fi nancial reviews that could explain increased housing market risk.…”

Section: Web Usage and Web Content Analyticsmentioning

confidence: 99%