abstract
Authors: Sudeep Das, Raghav Saboo, Chaitanya S. K. Vadrevu, Bruce Wang, and Steven Xu
WSDM '24: Proceedings of the 17th ACM International Conference on Web Search and Data Mining
March 2024
Pages 1163 - 1164
Published: 04 March 2024 Publication History
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Abstract
Extracting knowledge from unstructured or semi-structured textual information is essential for the machine learning applications that power DoorDash's search experience, and the development and maintenance of its product knowledge graph. Large language models (LLMs) have opened up new possibilities for utilizing their power in these areas, replacing or complementing traditional natural language processing methods. LLMs are also proving to be useful in the label and annotation generation process, which is critical for these use cases. In this talk, we will provide a high-level overview of how we incorporated LLMs for search relevance and product understanding use cases, as well as the key lessons learned and challenges faced during their practical implementation.
References
[1]
Alexander Brinkmann, Roee Shraga, Reng Chiz Der, and Christian Bizer. 2023. Product Information Extraction using ChatGPT. arXiv preprint arXiv:2304.10428 (2023).
[2]
Fabrizio Gilardi, Meysam Alizadeh, and Maël Kubli. 2023. ChatGPT outperforms crowd workers for text-annotation tasks Proceedings of the National Academy of Sciences 120, 30 (jul 2023). https://doi.org/10.1073/pnas.2305016120
[3]
Philipp Moritz, Robert Nishihara, Stephanie Wang, Alexey Tumanov, Richard Liaw, Eric Liang, Melih Elibol, Zongheng Yang, William Paul, Michael I. Jordan, and Ion Stoica. 2018. Ray: A Distributed Framework for Emerging AI Applications. arXiv preprint arXiv:1712.05889 (2018).
[4]
Tao Shen, Guodong Long, Xiubo Geng, Chongyang Tao, Tianyi Zhou, and Daxin Jiang. 2023. Large Language Models are Strong Zero-Shot Retriever. arXiv preprint arXiv:2304.14233 (2023).
[5]
Senbao Shi, Zhenran Xu, Baotian Hu, and Min zhang. 2023. Generative Multimodal Entity Linking. arXiv preprint arXiv:2306.12725 (2023).
[6]
Khanin Sisaengsuwanchai, Navapat Nananukul, and Mayank Kejriwal. 2023. How does prompt engineering affect ChatGPT performance on unsupervised entity resolution? arXiv preprint arXiv:2310.06174 (2023).
[7]
Krishna Srinivasan, Karthik Raman, Anupam Samanta, Lingrui Liao, Luca Bertelli, and Mike Bendersky. 2022. QUILL: Query Intent with Large Language Models using Retrieval Augmentation and Multi-stage Distillation. arXiv preprint arXiv:2210.15718 (2022).
[8]
Shuhe Wang, Xiaofei Sun, Xiaoya Li, Rongbin Ouyang, Fei Wu, Tianwei Zhang, Jiwei Li, and Guoyin Wang. 2023. GPT-NER: Named Entity Recognition via Large Language Models. arXiv preprint arXiv:2304.10428 (2023).
Index Terms
Applications of LLMs in E-Commerce Search and Product Knowledge Graph: The DoorDash Case Study
Computing methodologies
Artificial intelligence
Knowledge representation and reasoning
Natural language processing
Information extraction
Machine learning
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Information & Contributors
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Published In
WSDM '24: Proceedings of the 17th ACM International Conference on Web Search and Data Mining
March 2024
1246 pages
ISBN:9798400703713
DOI:10.1145/3616855
- General Chairs:
- Luz Angélica
Caudillo Mata (MDA Geointelligence)
, - Silvio Lattanzi
Google Research
, - Andrés Muñoz Medina
Google Research
, - Program Chairs:
- Leman Akoglu
CMU
, - Aristides Gionis
KTH
, - Sergei Vassilvitskii
Google Research
Copyright © 2024 Owner/Author.
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.
Sponsors
- SIGMOD: ACM Special Interest Group on Management of Data
- SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web
- SIGKDD: ACM Special Interest Group on Knowledge Discovery in Data
- SIGIR: ACM Special Interest Group on Information Retrieval
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 04 March 2024
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Author Tags
- large language model
- natural language processing
- product knowledge graph
- search
Qualifiers
- Abstract
Conference
WSDM '24
Sponsor:
- SIGMOD
- SIGWEB
- SIGKDD
- SIGIR
WSDM '24: The 17th ACM International Conference on Web Search and Data Mining
March 4 - 8, 2024
Merida, Mexico
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