Abstract: A computer joining an online chat service, based on unstructured text input, can be matched automatically under computer control to one of multiple different online chat conversations using a trained transformer-based machine learning model, training techniques, and similarity assessment techniques. Computer analysis in this manner improves the likelihood that the unstructured text input results in assigning the computer to a relevant chat conversation. Additionally, or alternatively, a dense passage retrieval machine learning model having a first encoder for resources and a second encoder for messages can automatically match relevant resources to computers or sessions based on analysis of a series of messages of an online chat conversation. In either approach, continuous re-training is supported based on feedback from a moderator computer and/or user computers.

Abstract: A dense passage retrieval machine learning model having a first encoder for resources and a second encoder for messages can automatically match relevant resources to computers or sessions based on analysis of a series of messages of an online chat conversation. Continuous re-training is supported based on feedback from a moderator computer and/or user computers.