Information Retrieval
We handle a lot of text: from mail and news, to travel reviews, user comments, and the whole web. Finding information and answers in them requires machine learning, natural language understanding and large-scale data processing.
Publications
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March 6, 2024
ICDE 2024
An Effective, Efficient, and Stable Framework for Query Clustering
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July 5, 2023
Ad KDD 2023
Staging E-Commerce Products for Online Advertising Using Retrieval Assisted Image Generation
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May 17, 2021
KDD 2021
VisualTextRank: Unsupervised Graph-Based Content Extraction for Automating Ad Text to Image Search
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November 13, 2020
AAAI 2021
Empirical Best Practices on Using Product-Specific Schema.org
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September 15, 2020
EMNLP 2020
TNT: Text Normalization Based Pre-Training of Transformers for Content Moderation
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July 24, 2020
CIKM 2020
Learning to Create Better Ads: Generation and Ranking Approaches for Ad Creative Refinement
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May 25, 2020
EDGE 2020
Edge Architecture for Dynamic Data Stream Analysis and Manipulation
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May 1, 2020
SIGIR 2020 industrial track
Identifying Tasks from Mobile App Usage Patterns
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February 14, 2020
EuroSys 2020
EvenDB: Optimizing Key-Value Storage for Spatial Locality
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February 4, 2020
Wiki Workshop 2020/ WWW2020
Layered Graph Embedding for Entity Recommendation Using Wikipedia in the Yahoo! Knowledge Graph
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November 3, 2019
Principles and Practice of Parallel Programming (PPoPP) 2020
Scalable Top-K Retrieval with Sparta
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January 1, 2019
CIKM
Estimating the Number of Distinct Items in a Database by Sampling
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January 1, 2019
Data Mining and Knowledge Discovery
Deeply Supervised Model for Click-Through Rate Prediction in Sponsored Search
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January 1, 2019
DLP-KDD 2019
Automatic Feature Engineering from Very High Dimensional Event Logs Using Deep Neural Networks
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January 1, 2019
SIGIR 2019 workshop on eCommerce
PSAC: Context-Based Purchase Prediction Framework via User's Sequential Actions
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January 1, 2019
SIGIR
