mlsanityData to 7 Oct 2026

Analyzing and Characterizing User Intent in Information-seeking Conversations

arXiv 1804.08759 ↗First posted 23 Apr 2018cs.IR cs.CLcited by 36

Not on the map. Why?

Abstract (arXiv)

Understanding and characterizing how people interact in information-seeking conversations is crucial in developing conversational search systems. In this paper, we introduce a new dataset designed for this purpose and use it to analyze information-seeking conversations by user intent distribution, co-occurrence, and flow patterns. The MSDialog dataset is a labeled dialog dataset of question answering (QA) interactions between information seekers and providers from an online forum on Microsoft products. The dataset contains more than 2,000 multi-turn QA dialogs with 10,000 utterances that are annotated with user intent on the utterance level. Annotations were done using crowdsourcing. With MSDialog, we find some highly recurring patterns in user intent during an information-seeking process. They could be useful for designing conversational search systems. We will make our dataset freely available to encourage exploration of information-seeking conversation models.

Key facts. Cited by 36 papers in the map (data through 7 Oct 2026). First posted on arXiv 23 Apr 2018.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 6; 2022: 4; 2023: 6; 2024: 10; 2025: 6; 2026: 4.

36 papers.

Sort:

By area:

  1. 2021QA Dataset Explosion: A Taxonomy of NLP Resources for Question Answering and Reading Comprehensioncited by 91
  2. 2024Tell Me More! Towards Implicit User Intention Understanding of Language Model Driven Agentscited by 71
  3. 2023User Simulation for Evaluating Information Access Systemscited by 30
  4. 2021On the Calibration and Uncertainty of Neural Learning to Rank Modelscited by 24
  5. 2025Prototypical Human-AI Collaboration Behaviors from LLM-Assisted Writing in the Wildcited by 24
  6. 2024A Survey on Recent Advances in Conversational Data Generationcited by 23
  7. 2024A Survey of Conversational Searchcited by 22
  8. 2022User Satisfaction Estimation with Sequential Dialogue Act Modeling in Goal-oriented Conversational Systemscited by 20
  9. 2024Self-seeding and Multi-intent Self-instructing LLMs for Generating Intent-aware Information-Seeking dialogscited by 18
  10. 2024STYLE: Improving Domain Transferability of Asking Clarification Questions in Large Language Model Powered Conversational Agentscited by 17
  11. 2024Dial-In LLM: Human-Aligned LLM-in-the-loop Intent Clustering for Customer Service Dialoguescited by 11
  12. 2023Investigating Conversational Search Behavior For Domain Explorationcited by 9
24 more
  1. 2025Impatient Users Confuse AI Agents: High-fidelity Simulations of Human Traits for Testing Agentscited by 8
  2. 2021We've had this conversation before: A Novel Approach to Measuring Dialog Similaritycited by 7
  3. 2022Mediators: Conversational Agents Explaining NLP Model Behaviorcited by 7
  4. 2024Learning to Ask: Conversational Product Search via Representation Learningcited by 7
  5. 2021Meta-evaluation of Conversational Search Evaluation Metricscited by 6
  6. 2024Engineering Conversational Search Systems: A Review of Applications, Architectures, and Functional Componentscited by 3
  7. 2025Trapped by Expectations: Functional Fixedness in LLM-Enabled Chat Searchcited by 3
  8. 2021POSSCORE: A Simple Yet Effective Evaluation of Conversational Search with Part of Speech Labellingcited by 2
  9. 2022Intent Recognition in Conversational Recommender Systemscited by 2
  10. 2023Efficient Uncertainty Estimation with Gaussian Process for Reliable Dialog Response Retrievalcited by 2
  11. 2024Corpus-informed Retrieval Augmented Generation of Clarifying Questionscited by 2
  12. 2024From Intents to Conversations: Generating Intent-Driven Dialogues with Contrastive Learning for Multi-Turn Classificationcited by 2
  13. 2023FCC: Fusing Conversation History and Candidate Provenance for Contextual Response Ranking in Dialogue Systemscited by 1
  14. 2023Intent-calibrated Self-training for Answer Selection in Open-domain Dialoguescited by 1
  15. 2025PSCon: Product Search Through Conversationscited by 1
  16. 2025IP-Dialog: Evaluating Implicit Personalization in Dialogue Systems with Synthetic Datacited by 1
  17. 2021Evaluating Predictive Uncertainty under Distributional Shift on Dialogue Datasetcited by 0
  18. 2022Sparse and Dense Approaches for the Full-rank Retrieval of Responses for Dialoguescited by 0
  19. 2023On the Calibration and Uncertainty with P'olya-Gamma Augmentation for Dialog Retrieval Modelscited by 0
  20. 2025Finding Diamonds in Conversation Haystacks: A Benchmark for Conversational Data Retrievalcited by 0
  21. 2026Do Images Clarify? A Study on the Effect of Images on Clarifying Questions in Conversational Searchcited by 0
  22. 2026Structure-Aware RAG: Structured Retrieval Augmented Generation from Noisy Data for Conversational Agentscited by 0
  23. 2026CIR at iKAT SCAI 2026: Exploring Clarification Need Prediction in Agentic Conversational Searchcited by 0
  24. 2026RAFT: A Stateful Retrieval-Augmented Framework for Troubleshooting Agentscited by 0