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Messaging System Problem Management Record diagnostics using cognitive approach

IP.com Disclosure Number: IPCOM000248500D
Publication Date: 2016-Dec-09
Document File: 2 page(s) / 42K

Publishing Venue

The IP.com Prior Art Database

Abstract

Customer problems in Messaging Systems can take a significant amount of time for technical support to address. Using a cognitive approach to address these customer issues will result in a reduction in response and solution time.

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Messaging System Problem Management Record diagnostics using cognitive approach

Current Method: Currently Problem Management Record (PMR) solving systems are

dependent upon a customer raising a ticket and the technical support attends to it and the efficiency and time taken is purely dependent upon the expertise of the technical support personnel. Invention:

This innovation provides a more efficient and cognitive way of approaching and solving customer PMRs related to Messaging Systems.

The general idea behind this system is to reduce the time spent attending and solving problems that are similar but from different customers at different time.

Also, as the knowledge base is based on NoSQL database, different clusters will be created for similar problems hence displaying hotspots or product areas which can then be focused on and improved.

The invented system runs complete diagnostics of Messaging Systems on the clients system and collects all the possible data, analyses it and then provides detailed diagnostics and a relevant possible solution to technical support. This is accomplished by comparing the PMR with previous similar PMR in the database. Whilst processing this information, the system learns about the parameters which caused this problem, the appropriate solution, and what other scenarios can cause similar problems and what diagnostics programs were used. As a result, the next time such a problem occurs at the customer end the system can give its expert opinion quickly by running fewer diagnostic tools, hence evolving its knowledge base in the process

We start by using a graph database (i.e. NoSQL) that stores all the PMRs with additional details such as the keywords of the complaint in that record, the flag and the distance to the next connected node i.e. the similarity of the keywords between two connected nodes. The flags are based on different combinations of keywords and are stored separately. The search algorithm provides the cognitive piece of the algorithm. It searches for the node with maximum number of similar keywords, and whilst doing this it flags different nodes that it traverses. To find its way it only traverses through nodes that have some similarity of keywords. On different attempts it flags new nodes creating zones of flags. With zones created when a similar search comes it directly jumps into the correct zone and gets the results. In the initial steps, the algorithm will take some time to find the right...