Structuring and Controlling the Knowledge for the Software User Support

The research aims to create a smart user Support Assistant LAVA - a solution providing context sensitive and user experience aware support to a user of a software product. The solution is based on machine learning and search in a two-level distributed knowledge store. LAVA model focuses on providing user on a mouse click with a content relevant to a current context. LAVA uses context transferred from the supported product to instantly show a FAQ list of items used and/or positively rated by other users in the same context. Full-text search and a topic hierarchy are provided as well to cover as many of cases as possible given the content available currently in the Knowledge base. Main design ideas of the LAVA model are presented in the article including the calculation of ranges and creation of ranged context-sensitive FAQs, customizing the full-text search, organizing the topic hierarchy and integrating with the Service desk. The article covers as well the main considerations on how the LAVA model should be implemented in a successful solution, and a description of method to evaluate the model performance.