Presentation at GigaTIC2017 on artificial intelligence techniques for the automatic interpretation of service management indicators
Alberto Bugarín, professor of artificial intelligence, and Diego Berea, Director of Obsidian, gave a presentation about the use of data2text NGL for the automatic interpretation of service management indicators implemented in Obsidian. This session was part of GigaTIC2017, an event organized by iTSMF and ISACA.
Below is the video of the presentation, which currently has 37220 visits on YouTube and 358 likes.
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Artificial intelligence techniques for the automatic interpretation of service management indicators
First, this presentation sets out the most common methodologies to implement a data2text NLG system. Then, it shows multiple examples of its practical application for the automatic interpretation of service management indicators. These examples are based on data2text implementation in Obsidian, which includes service desk metrics as well as availability, capacity, or service level indicators. Now it is possible to obtain explanatory reports in real time based on data from tools. This is one of the main advantages of this type of system: Less analytical effort is required of the user.
Automatic data2text natural language generation systems in Obsidian
There are several disciplines of artificial intelligence that relate to natural language processing (NLP). Out of these, one particular subset concerns techniques of automatic generation of natural language (NLG).
In recent years, intensive research has been carried out in these areas. As a result, researchers have developed and deployed different software programs, which have even been tested in real environments with satisfactory results.
Gartner predicts that, by 2018, NLG will be present in about 90% of BI market tools.
In this sense, 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 information about whether the service level agreed with the customer has been accomplished. But all this information can be extracted from corporate service desk and monitoring tools. So, NLG techniques attempt to help the user by processing these data and displaying a written interpretation according to each user’s role.
More information on the data2text functionalities of Obsidian.
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