activity
20192021
most citedPersonalized Query Auto-Completion Through a Lightweight Representation of the User Context

3 citations · 4 across the 3 of their papers we have counts for

collaborators

5 papers

cs.IR2021

Conditional Sequential Slate Optimization

Yipeng Zhang, Mingjian Lu, Saratchandra Indrakanti +2

The top search results matching a user query that are displayed on the first page are critical to the effectiveness and perception of a search system. A search ranking system typic…

cs.IR20201 cited

Addressing Purchase-Impression Gap through a Sequential Re-ranker

Shubhangi Tandon, Saratchandra Indrakanti, Amit Jaiswal +2

Large scale eCommerce platforms such as eBay carry a wide variety of inventory and provide several buying choices to online shoppers. It is critical for eCommerce search engines to…

cs.IR2019

Influence of Neighborhood on the Preference of an Item in eCommerce Search

Saratchandra Indrakanti, Svetlana Strunjas, Shubhangi Tandon +1

Surfacing a ranked list of items for a search query to help buyers discover inventory and make purchase decisions is a critical problem in eCommerce search. Typically, items are in…

cs.IR20193 cited

Personalized Query Auto-Completion Through a Lightweight Representation of the User Context

Manojkumar Rangasamy Kannadasan, Grigor Aslanyan

Query Auto-Completion (QAC) is a widely used feature in many domains, including web and eCommerce search, suggesting full queries based on a prefix typed by the user. QAC has been…

cs.IR2019

Personalized Ranking in eCommerce Search

Grigor Aslanyan, Aritra Mandal, Prathyusha Senthil Kumar +2

We address the problem of personalization in the context of eCommerce search. Specifically, we develop personalization ranking features that use in-session context to augment a gen…