4 research outputs found
Natural Language Sentence Generation from API Specifications
APIs are everywhere; they provide access to automation solutions that could
help businesses automate some of their tasks. Unfortunately, they may not be
accessible to the business users who need them but are not equipped with the
necessary technical skills to leverage them. Wrapping these APIs with chatbot
capabilities is one solution to make these automation solutions interactive. In
this work, we propose a system to generate sentences to train intent
recognition models, a crucial component within chatbots to understand natural
language utterances from users. Evaluation of our approach based on deep
learning models showed promising and inspiring results, and the
human-in-the-loop interaction will provide further improvement on the system
Towards Hybrid Automation by Bootstrapping Conversational Interfaces for IT Operation Tasks
Process automation has evolved from end-to-end automation of repetitive process branches to hybrid automation where bots perform some activities and humans serve other activities. In the context of knowledge-intensive processes such as IT operations, implementing hybrid automation is a natural choice where robots can perform certain mundane functions, with humans taking over the decision of when and which IT systems need to act. Recently, ChatOps, which refers to conversation-driven collaboration for IT operations, has rapidly accelerated efficiency by providing a cross-organization and cross-domain platform to resolve and manage issues as soon as possible. Hence, providing a natural language interface to bots is a logical progression to enable collaboration between humans and bots. This work presents a no-code approach to provide a conversational interface that enables human workers to collaborate with bots executing automation scripts. The bots identify the intent of users' requests and automatically orchestrate one or more relevant automation tasks to serve the request. We further detail our process of mining the conversations between humans and bots to monitor performance and identify the scope for improvement in service quality