Conversational IT Service Management
Conversational AI permeates our daily lives through chatbots such as Alexa, Siri, Google etc. We can ask questions about weather, music, shop for flowers or control various home electronics devices in a conversational manner. We believe that conversational interaction will dominate the next generation of interactions even in IT Service Management world. To that effect, in this chapter we describe an AI infused conversational self-service system that enables a user to get precise answers to various domain specific questions in a natural conversational manner. These questions span the gamut of 5 W + H (What, Where, Which, Who, Why, How) queries in an increasingly refined conversational context including some that may require performing transactions on behalf of the user – such as adding memory to a virtual machine or starting/stopping a database.
This work represents efforts of several contributors. We would like to acknowledge the significant contributions from Gargi Dasgupta, Yu Deng, Ruchi Mahindru, Jin Xiao, Anup Kalia and Sethu Subramaniam.
- 4.Hearst M (1992) Automatic acquisition of hyponyms from large text corpora. In: Proceedings of COLING-92. Nantes, France, pp 539–545Google Scholar
- 5.Snow R, Jurafsky D, Ng A (2005) Learning syntactic patterns for automatic hypernym discovery. In: Proceedings of NIPS 17, Bonn, GermanyGoogle Scholar
- 6.Bollegala D, Maehara T, Kawarabayashi K (2015) Embedding semantic relations into word representations. In: Proceedings of IJCAI, Buenos Aires, Argentina, pp. 1222–1228Google Scholar
- 7.Huang L, Sil A, Ji H, Florian R (2017) Improving slot filling performance with attentive neural networks on dependency structures. In: Empirical Methods in Natural Language Processing (EMNLP), Copenhagen, DenmarkGoogle Scholar