# Discovering Conversational Dependencies between Messages in Dialogs

arXiv: https://arxiv.org/abs/1612.02801 · HTML: https://mlsanity.com/paper/1612.02801/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Dec 2016.

## Built on by (most cited first, 2 of 2)

- [Dependency Dialogue Acts -- Annotation Scheme and Case Study](https://mlsanity.com/paper/2302.12944/) (2023)
- [Who Responded to Whom: The Joint Effects of Latent Topics and Discourse in Conversation Structure](https://mlsanity.com/paper/2104.08601/) (2021)

## Abstract (arXiv)

We investigate the task of inferring conversational dependencies between messages in one-on-one online chat, which has become one of the most popular forms of customer service. We propose a novel probabilistic classifier that leverages conversational, lexical and semantic information. The approach is evaluated empirically on a set of customer service chat logs from a Chinese e-commerce website. It outperforms heuristic baselines.