MACHINE LEARNING BASED TENANT-SPECIFIC CHATBOTS FOR PERFORMING ACTIONS IN A MULTI-TENANT SYSTEM

• Main Authors: Thakar, Rohiniben, Kollu, Srikanth, Xiong, Caiming, Abrahamyan, Armen, Yang, Xinyi, Vijayakumar, Manju, McCann, Bryan, Xie, Tian, Zhang, Kevin, Keskar, Nitish Shirish, Zou, Zhihao, Liu, Qiong, Gulabrani, Chitra, Liu, Johnson, Machado, Michael, Harrison, James Douglas, Soumet, Jean-Marc, Schoen, Kevin, Brouk, Victor, Khodani, Minal, Lalani, Roojuta, Motwani, Vishal, Rodriguez, Juan Manuel, Skucha, Karl Ryszard, Badarinath, Adarsha, Hetawal, Amit, Cook, Thomas Archie, Amsili, Rafael
• Format: Patent
• Language: English
• Published: 13.05.2021
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; ELECTRIC COMMUNICATION TECHNIQUE; ELECTRICITY; PHYSICS; TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHICCOMMUNICATION

A multi-tenant system performs custom configuration of a tenant-specific chatbot to process and act upon natural language requests. The multi-tenant system configures the tenant-specific chatbots without requiring tenant-specific training. The multi-tenant system providing a user interface for configuring a tenant-specific set of permitted actions. The multi-tenant system determines a set of example phrases for each of the selected permitted actions. The multi-tenant system receives a natural language request from a user and identifies the action that the user wants to perform. The multi-tenant system uses a neural network to compare the natural language request with example phrases to identify an example phrase that matches the natural language request. The multi-tenant system performs the action corresponding to the matching example phrase.