43 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Emory UniversityUS4 papers
- Georgia Institute of TechnologyUS2 papers
- Information Technology UniversityPK2 papers
- Amazon (Germany)DE1 paper
- Amazon (United States)US1 paper
- George Mason UniversityUS1 paper
- Indra (Spain)ES1 paper
- Invitae (United States)US1 paper
- Kennesaw State UniversityUS1 paper
- Texas A&M UniversityUS1 paper
- University of MichiganUS1 paper
12 papers
Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap
Srivatsa Mallapragada, Ying Xie, Varsha Rani Chawan +2
E-commerce click-stream data and product catalogs offer critical user behavior insights and product knowledge. This paper propose a multi-modal transformer termed as PINCER, that l…
Joint Stream: Malignant Region Learning for Breast Cancer Diagnosis
Abdul Rehman, Sarfaraz Hussein, Waqas Sultani
Early diagnosis of breast cancer (BC) significantly contributes to reducing the mortality rate worldwide. The detection of different factors and biomarkers such as Estrogen recepto…
3DPFIX: Improving Remote Novices' 3D Printing Troubleshooting through Human-AI Collaboration
Nahyun Kwon, Tong Sun, Yuyang Gao +4
The widespread consumer-grade 3D printers and learning resources online enable novices to self-train in remote settings. While troubleshooting plays an essential part of 3D printin…
A Comprehensive Review of Modern Object Segmentation Approaches
Yuanbo Wang, Unaiza Ahsan, Hanyan Li +1
Image segmentation is the task of associating pixels in an image with their respective object class labels. It has a wide range of applications in many industries including healthc…
M2TRec: Metadata-aware Multi-task Transformer for Large-scale and Cold-start free Session-based Recommendations
Walid Shalaby, Sejoon Oh, Amir Afsharinejad +2
Session-based recommender systems (SBRSs) have shown superior performance over conventional methods. However, they show limited scalability on large-scale industrial datasets since…
Adaptive Multi-view Rule Discovery for Weakly-Supervised Compatible Products Prediction
Rongzhi Zhang, Rebecca West, Xiquan Cui +1
On e-commerce platforms, predicting if two products are compatible with each other is an important functionality to achieve trustworthy product recommendation and search experience…
Diversifying Multi-aspect Search Results Using Simpson's Diversity Index
Jianghong Zhou, Eugene Agichtein, Surya Kallumadi
In search and recommendation, diversifying the multi-aspect search results could help with reducing redundancy, and promoting results that might not be shown otherwise. Many previo…
De-Biased Modelling of Search Click Behavior with Reinforcement Learning
Jianghong Zhou, Sayyed M. Zahiri, Simon Hughes +3
Users' clicks on Web search results are one of the key signals for evaluating and improving web search quality and have been widely used as part of current state-of-the-art Learnin…
APRF-Net: Attentive Pseudo-Relevance Feedback Network for Query Categorization
Ali Ahmadvand, Sayyed M. Zahiri, Simon Hughes +3
Query categorization is an essential part of query intent understanding in e-commerce search. A common query categorization task is to select the relevant fine-grained product cate…
Interpretable Methods for Identifying Product Variants
Rebecca West, Khalifeh Al Jadda, Unaiza Ahsan +2
For e-commerce companies with large product selections, the organization and grouping of products in meaningful ways is important for creating great customer shopping experiences a…
Estimation of BMI from Facial Images using Semantic Segmentation based Region-Aware Pooling
Nadeem Yousaf, Sarfaraz Hussein, Waqas Sultani
Body-Mass-Index (BMI) conveys important information about one's life such as health and socio-economic conditions. Large-scale automatic estimation of BMIs can help predict several…
JointMap: Joint Query Intent Understanding For Modeling Intent Hierarchies in E-commerce Search
Ali Ahmadvand, Surya Kallumadi, Faizan Javed +1
An accurate understanding of a user's query intent can help improve the performance of downstream tasks such as query scoping and ranking. In the e-commerce domain, recent work in…