Presentation at GigaTIC2017 on artificial intelligence techniques for the automatic interpretation of service management indicators
Presentation at GigaTIC2017, event organized by iTSMF and ISACA, of the research on the automatic interpretation of service management indicators implemented in Obsidian. A presentation given by the professor of artificial intelligence Alberto Bugarín and the director of Obsidian, Diego Berea.
The video currently has 37148 visits on YouTube and 358 likes.
If you would like to receive notifications of new videos posted by Obsidian, subscribe to the channel, and YouTube will periodically send you notifications when new videos are posted. The Obsidian YouTube channel currently has 1810 subscribers.
Data2text implementation on Obsidian
Several disciplines of artificial intelligence are related to natural language processing (NLP). Of these, one particular subset concerns techniques of automatic generation of natural language (NLG).
Over the course of recent years, intensive research has been carried out in these areas. As a result, researchers have developed and deployed different software, which has been tested in real environments and with satisfactory results.
For 2018, it is predicted that NLG will be present in a large percentage of BI market tools.
In this scenario, the management of ITSM services offers an extremely rich context for the application of NLG techniques. There are multiple actors (technicians, managers or directors), each with different information needs. These may be technical specifications, service performance values or simply knowing whether the service level agreed with the customer have been accomplished or not. This information can be extracted from the corporate tools of service desk and monitoring. NLG techniques attempt to help the user, by processing data and displaying a written interpretation of these data according to each user’s role.
Initially, this presentation shows the most common methodologies for the implementation of an NLG system of data2text type. At the end, multiple examples of the practical application of the automatic interpretation of service management indicators are shown. The examples are based on the data2text implementation performed in Obsidian. This implementation includes service desk metrics and availability, capacity and service level indicators, which are already working in real environments. With data2text implementation it is now possible to generate written automatic reports using data obtained from these tools. This is one of the main advantages of these types of systems: reducing the analytical effort required from the user.
More information on the data2text functionalities of Obsidian.