no code implementations • 17 Apr 2024 • Zezhong Fan, Xiaohan Li, Chenhao Fang, Topojoy Biswas, Kaushiki Nag, Jianpeng Xu, Kannan Achan
The dataset is created with GPT-4 to extend the abstract concept to a scene and concrete objects.
no code implementations • 29 Feb 2024 • Chenhao Fang, Xiaohan Li, Zezhong Fan, Jianpeng Xu, Kaushiki Nag, Evren Korpeoglu, Sushant Kumar, Kannan Achan
Product attribute value extraction is a pivotal component in Natural Language Processing (NLP) and the contemporary e-commerce industry.
no code implementations • 2 Feb 2024 • Najmeh Forouzandehmehr, Yijie Cao, Nikhil Thakurdesai, Ramin Giahi, Luyi Ma, Nima Farrokhsiar, Jianpeng Xu, Evren Korpeoglu, Kannan Achan
The outfit generation problem involves recommending a complete outfit to a user based on their interests.
no code implementations • 26 Dec 2023 • Luyi Ma, Nikhil Thakurdesai, Jiao Chen, Jianpeng Xu, Evren Korpeoglu, Sushant Kumar, Kannan Achan
Although the UDF design pattern introduces flexibility, reusability and scalability, the increasing demand on machine learning pipelines brings three new challenges to this design pattern -- not low-code, not dependency-free and not knowledge-aware.
no code implementations • 1 Dec 2023 • Reza Yousefi Maragheh, Chenhao Fang, Charan Chand Irugu, Parth Parikh, Jason Cho, Jianpeng Xu, Saranyan Sukumar, Malay Patel, Evren Korpeoglu, Sushant Kumar, Kannan Achan
We call our LLM-based framework Theme-Aware Keyword Extraction (LLM TAKE).
no code implementations • 26 Oct 2023 • Ramin Giahi, Reza Yousefi Maragheh, Nima Farrokhsiar, Jianpeng Xu, Jason Cho, Evren Korpeoglu, Sushant Kumar, Kannan Achan
Similar item recommendation is a critical task in the e-Commerce industry, which helps customers explore similar and relevant alternatives based on their interested products.
no code implementations • 17 May 2023 • Jiao Chen, Luyi Ma, Xiaohan Li, Nikhil Thakurdesai, Jianpeng Xu, Jason H. D. Cho, Kaushiki Nag, Evren Korpeoglu, Sushant Kumar, Kannan Achan
Knowledge Graphs (KGs) play a crucial role in enhancing e-commerce system performance by providing structured information about entities and their relationships, such as complementary or substitutable relations between products or product types, which can be utilized in recommender systems.
no code implementations • 11 Feb 2022 • Luyi Ma, Jianpeng Xu, Jason H. D. Cho, Evren Korpeoglu, Sushant Kumar, Kannan Achan
On the other hand, the model evaluation will not be trustworthy if the labels for evaluation are not reflecting the true complementary relatedness.
no code implementations • 12 Dec 2020 • Yao Zhou, Jianpeng Xu, Jun Wu, Zeinab Taghavi Nasrabadi, Evren Korpeoglu, Kannan Achan, Jingrui He
Recommender systems are popular tools for information retrieval tasks on a large variety of web applications and personalized products.