Text Mining and Topic Modelling

  • Healthcare Data: Medical Transcriptions Analysis

    How to understand the symptoms and treatments better. Medical records analysis using text network visualization.

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  • Discover EU Grant Opportunities using Network Analysis

    In this case study, we will demonstrate how you can use text network analysis to analyze EU grant opportunities. We will demonstrate how you can use the graph to identify the most relevant topics in the existing grant proposals. We will also show how you can use network visualization to identify the structural gaps within.

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  • Tutorial: Text Mining Using LDA and Network Analysis

    In this tutorial we present a method for topic modeling using text network analysis (TNA) and visualization. The approach we propose is based on identifying topical clusters in text based on co-occurrence of words. We will demonstrate how this approach can be used for topic modeling, how it compares to Latent Dirichlet Allocation (LDA), and how they can be used together to provide more relevant results.

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  • Google SEO Strategies using Text Mining and Network Visualization

    Search engine optimization is a set of strategies used to promote certain content in search results. Using a combination of text mining and network visualization techniques, you can identify discrepancies between what the users search for and what they actually find. You can then create the content that bridges that gap, so that it’s shown at the top of the relevant search results.

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