Content analysis using the latest NLP tools can help optimize a customer support portal or a knowledge base — making it more relevant, better structured, and optimizing it for search engines as well.
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.
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.
