30 citations · 39 across the 7 of their papers we have counts for
5 papers · 1 filter
GRIT: Graph-based Recall Improvement for Task-oriented E-commerce Queries
Hrishikesh Kulkarni, Surya Kallumadi, Sean MacAvaney +2
Many e-commerce search pipelines have four stages, namely: retrieval, filtering, ranking, and personalized-reranking. The retrieval stage must be efficient and yield high recall be…
LexBoost: Improving Lexical Document Retrieval with Nearest Neighbors
Hrishikesh Kulkarni, Nazli Goharian, Ophir Frieder +1
Sparse retrieval methods like BM25 are based on lexical overlap, focusing on the surface form of the terms that appear in the query and the document. The use of inverted indices in…
Lexically-Accelerated Dense Retrieval
Hrishikesh Kulkarni, Sean MacAvaney, Nazli Goharian +1
Retrieval approaches that score documents based on learned dense vectors (i.e., dense retrieval) rather than lexical signals (i.e., conventional retrieval) are increasingly popular…
Sentiment Progression based Searching and Indexing of Literary Textual Artefacts
Hrishikesh Kulkarni, Bradly Alicea
Literary artefacts are generally indexed and searched based on titles, meta data and keywords over the years. This searching and indexing works well when user/reader already knows…
Computational Psychology to Embed Emotions into News or Advertisements to Increase Reader Affinity
Hrishikesh Kulkarni, P Joshi, P Chande
Readers take decisions about going through the complete news based on many factors. The emotional impact of the news title on reader is one of the most important factors. Cognitive…