ICM : Intent and Conversational Mining from Conversation Logs
Sayantan Mitra, Roshni Ramnani, Sumit Ranjan, Shubhashis Sengupta
Abstract
Building conversation agents requires a large amount of manual effort in creating training data for intents / entities as well as mapping out extensive conversation flows. In this demonstration, we present ICM (Intent and conversation Mining), a tool which can be used to analyze existing conversation logs and help a bot designer analyze customer intents, train a custom intent model as well as map and optimize conversation flows. The tool can be used for first time deployment or subsequent deployments of chatbots.- Anthology ID:
- 2022.sigdial-1.39
- Volume:
- Proceedings of the 23rd Annual Meeting of the Special Interest Group on Discourse and Dialogue
- Month:
- September
- Year:
- 2022
- Address:
- Edinburgh, UK
- Venue:
- SIGDIAL
- SIG:
- SIGDIAL
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 403–406
- Language:
- URL:
- https://aclanthology.org/2022.sigdial-1.39
- DOI:
- Cite (ACL):
- Sayantan Mitra, Roshni Ramnani, Sumit Ranjan, and Shubhashis Sengupta. 2022. ICM : Intent and Conversational Mining from Conversation Logs. In Proceedings of the 23rd Annual Meeting of the Special Interest Group on Discourse and Dialogue, pages 403–406, Edinburgh, UK. Association for Computational Linguistics.
- Cite (Informal):
- ICM : Intent and Conversational Mining from Conversation Logs (Mitra et al., SIGDIAL 2022)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/2022.sigdial-1.39.pdf