most citedFeature-based factorized Bilinear Similarity Model for Cold-Start Top-n Item Recommendation

23 citations · 32 across the 2 of their papers we have counts for

collaborators

5 papers

cs.IR2020

Distant-Supervised Slot-Filling for E-Commerce Queries

Saurav Manchanda, Mohit Sharma, George Karypis

Slot-filling refers to the task of annotating individual terms in a query with the corresponding intended product characteristics (product type, brand, gender, size, color, etc.).…

cs.IR2019

Intent term selection and refinement in e-commerce queries

Saurav Manchanda, Mohit Sharma, George Karypis

In e-commerce, a user tends to search for the desired product by issuing a query to the search engine and examining the retrieved results. If the search engine was successful in co…

cs.IR20199 cited

Learning from Sets of Items in Recommender Systems

Mohit Sharma, F. Maxwell Harper, George Karypis

Most of the existing recommender systems use the ratings provided by users on individual items. An additional source of preference information is to use the ratings that users prov…

cs.IR201923 cited

Feature-based factorized Bilinear Similarity Model for Cold-Start Top-n Item Recommendation

Mohit Sharma, Jiayu Zhou, Junling Hu +1

Recommending new items to existing users has remained a challenging problem due to absence of user's past preferences for these items. The user personalized non-collaborative metho…

cs.IR2019

Adaptive Matrix Completion for the Users and the Items in Tail

Mohit Sharma, George Karypis

Recommender systems are widely used to recommend the most appealing items to users. These recommendations can be generated by applying collaborative filtering methods. The low-rank…