Natthakit Srikanjanapert's research while affiliated with Mahasarakham University and other places
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Publications (3)
Nowadays, various bug tracking systems (BTS) such as Jira, Trace, and Bugzilla have been developed and proposed to gather the issues from users worldwide. This is because those issues, called bug reports, contain a significant information for software quality maintenance and improvement. However, many bug reports with poor quality might have been s...
In general, the existing works in sentiment classification concentrate only the syntactic context of words. It always disregards the sentiment of text. This work addresses this issue by applying Word2Vec to learn sentiment specific words embedded in texts, and then the similar words will be grouped as a same concept (or class) with sentiment inform...
Today, millions of message posted daily contain opinions of users in a variety of languages, including emoticon. Sentiment analysis becomes a very difficult task, and the understanding and knowledge of the problem and its solution are still preliminary. Therefore, this work presents a new methodology, called Concept-based Sentiment Analysis (C-SA)....
Citations
... Some standardization attempts have been made to address this problem [5], which attempted to find the best device settings that lead to more accurate segmentation results. In addition, segmentation methods can be modified to segment and transmit medical images securely [6]. Alternatively, the use of neural networks in medical image classification is becoming increasingly popular to achieve highly accurate classification results. ...
... Other studies aimed to identify product weaknesses by comparing analysis results with those of competing products [72]. Some studies suggested a method to automatically identify positive and negative sentiments by finding similar words using word2vec and conducting sentiment analysis [73]. Each study shares a common goal of quantifying customers' positive and negative emotions toward products and determining their relative importance. ...
... Millions of people have expressed their feelings and attitudes on social and e-commerce platforms, with text being the most frequent way. Aiming at the text generated in the networks, it is very important for users, merchants, and researchers to extract this information and implied sentiments automatically and accurately [18]. For example, users can know the praise rate of the product through the Multimedia Tools and Applications https://doi.org/10.1007/s11042-020-09846-x ...
