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LDA-based topic analysis is widely used in text mining field. Considering the large scale of web documents, document clusters are usually analyzed instead of single ones. However, the existing visualizations of LDA-based clustering do not intuitively present contents of hot topics while maintaining the relationships between the topics and the document clusters. In this paper, we propose an integrated...
Sentiment analysis found various applications in banking, financial, service, and insurance sector. In this regard, we proposed to analyze customer reviews on the basis of sentiment score. We analyzed a set of credible text reviews collected on 270 training programmes posted by 2688 participants in an organization. In order to evaluate the efficacy of the proposed approach, we computed correlation...
There is growing interest in mining software repository data to understand, and predict, various aspects of team processes. In particular, text mining and natural-language processing (NLP) techniques have supported such efforts. Visualization may also supplement text mining to reveal unique multi-dimensional insights into software teams' behavioral processes. We demonstrate the utility of combining...
This paper presents a mining tool that is able to extract graphs from texts, and proposes their use in helping students to write summaries. The text summarization method is based on the use of the graphs as graphic organizers, leading students to further reflect about the main ideas of the text before getting to the actual task of writing. An experiment carried out demonstrated that the tool helped...
Since the beginning of mankind, there has been a need to display knowledge in such a way that it could be easily understood. In today's highly technological world we face an overwhelming amount of information from a variety of sources, namely: business applications such as customer comments and communications, trade publications, internal research reports and competitor web sites. Most of this knowledge...
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