activity
20152023
most citedPosthoc Interpretability of Learning to Rank Models using Secondary Training Data

35 citations · 125 across the 10 of their papers we have counts for

collaborators
Showing 2018 · cs.IRShow all

6 papers · 2 filters

cs.IR2018★ 16 cited

Expedition: A Time-Aware Exploratory Search System Designed for Scholars

Jaspreet Singh, Wolfgang Nejdl, Avishek Anand

Archives are an important source of study for various scholars. Digitization and the web have made archives more accessible and led to the development of several time-aware explora…

cs.IR2018★ 2 cited

Designing Search Tasks for Archive Search

Jaspreet Singh, Avishek Anand

Longitudinal corpora like legal, corporate and newspaper archives are of immense value to a variety of users, and time as an important factor strongly influences their search behav…

cs.IR2018★ 9 cited

Discovering Entities with Just a Little Help from You

Jaspreet Singh, Johannes Hoffart, Avishek Anand

Linking entities like people, organizations, books, music groups and their songs in text to knowledge bases (KBs) is a fundamental task for many downstream search and mining applic…

cs.IR2018★ 30 cited

History by Diversity: Helping Historians search News Archives

Jaspreet Singh, Wolfgang Nejdl, Avishek Anand

Longitudinal corpora like newspaper archives are of immense value to historical research, and time as an important factor for historians strongly influences their search behaviour…

cs.IR2018★ 3 cited

EXS: Explainable Search Using Local Model Agnostic Interpretability

Jaspreet Singh, Avishek Anand

Retrieval models in information retrieval are used to rank documents for typically under-specified queries. Today machine learning is used to learn retrieval models from click logs…

cs.IR2018★ 35 cited

Posthoc Interpretability of Learning to Rank Models using Secondary Training Data

Jaspreet Singh, Avishek Anand

Predictive models are omnipresent in automated and assisted decision making scenarios. But for the most part they are used as black boxes which output a prediction without understa…