# ShopTalk: A System for Conversational Faceted Search

arXiv: https://arxiv.org/abs/2109.00702 · HTML: https://mlsanity.com/paper/2109.00702/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 25 of its 44 references that are in the map.
- First posted on arXiv 2 Sep 2021.

## Builds on (most cited first, 25 of 25)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Self-Attention with Relative Position Representations](https://mlsanity.com/paper/1803.02155/) (2018)
- [MultiWOZ -- A Large-Scale Multi-Domain Wizard-of-Oz Dataset for Task-Oriented Dialogue Modelling](https://mlsanity.com/paper/1810.00278/) (2018)
- [Towards Scalable Multi-domain Conversational Agents: The Schema-Guided Dialogue Dataset](https://mlsanity.com/paper/1909.05855/) (2019)
- [A Network-based End-to-End Trainable Task-oriented Dialogue System](https://mlsanity.com/paper/1604.04562/) (2016)
- [Transferable Multi-Domain State Generator for Task-Oriented Dialogue Systems](https://mlsanity.com/paper/1905.08743/) (2019)
- [Language to Logical Form with Neural Attention](https://mlsanity.com/paper/1601.01280/) (2016)
- [Neural Belief Tracker: Data-Driven Dialogue State Tracking](https://mlsanity.com/paper/1606.03777/) (2016)
- [Data Recombination for Neural Semantic Parsing](https://mlsanity.com/paper/1606.03622/) (2016)
- [Coarse-to-Fine Decoding for Neural Semantic Parsing](https://mlsanity.com/paper/1805.04793/) (2018)
- [Learning a Neural Semantic Parser from User Feedback](https://mlsanity.com/paper/1704.08760/) (2017)
- [Frames: A Corpus for Adding Memory to Goal-Oriented Dialogue Systems](https://mlsanity.com/paper/1704.00057/) (2017)
- [Editing-Based SQL Query Generation for Cross-Domain Context-Dependent Questions](https://mlsanity.com/paper/1909.00786/) (2019)
- [Dialog State Tracking: A Neural Reading Comprehension Approach](https://mlsanity.com/paper/1908.01946/) (2019)
- [BERT-DST: Scalable End-to-End Dialogue State Tracking with Bidirectional Encoder Representations from Transformer](https://mlsanity.com/paper/1907.03040/) (2019)
- [Towards Universal Dialogue State Tracking](https://mlsanity.com/paper/1810.09587/) (2018)
- [Large-Scale Multi-Domain Belief Tracking with Knowledge Sharing](https://mlsanity.com/paper/1807.06517/) (2018)
- [An End-to-end Approach for Handling Unknown Slot Values in Dialogue State Tracking](https://mlsanity.com/paper/1805.01555/) (2018)
- [Grammar-based Neural Text-to-SQL Generation](https://mlsanity.com/paper/1905.13326/) (2019)
- [HyST: A Hybrid Approach for Flexible and Accurate Dialogue State Tracking](https://mlsanity.com/paper/1907.00883/) (2019)
- [Generating Logical Forms from Graph Representations of Text and Entities](https://mlsanity.com/paper/1905.08407/) (2019)
- [Deep Cascade Multi-task Learning for Slot Filling in Online Shopping Assistant](https://mlsanity.com/paper/1803.11326/) (2018)
- [Robust Handling of Polysemy via Sparse Representations](https://mlsanity.com/paper/1805.07398/) (2018)
- [Query Tracking for E-commerce Conversational Search: A Machine Comprehension Perspective](https://mlsanity.com/paper/1810.03274/) (2018)

## Built on by (most cited first, 1 of 1)

- [Task Conditioned BERT for Joint Intent Detection and Slot-filling](https://mlsanity.com/paper/2308.06165/) (2023)

## Abstract (arXiv)

We present ShopTalk, a multi-turn conversational faceted search system for shopping that is designed to handle large and complex schemas that are beyond the scope of state of the art slot-filling systems. ShopTalk decouples dialog management from fulfillment, thereby allowing the dialog understanding system to be domain-agnostic and not tied to the particular shopping application. The dialog understanding system consists of a deep-learned Contextual Language Understanding module, which interprets user utterances, and a primarily rules-based Dialog-State Tracker (DST), which updates the dialog state and formulates search requests intended for the fulfillment engine. The interface between the two modules consists of a minimal set of domain-agnostic "intent operators," which instruct the DST on how to update the dialog state. ShopTalk was deployed in 2020 on the Google Assistant for Shopping searches.