60 citations · 547 across the 40 of their papers we have counts for
10 papers · 1 filter
Asynchronous Training of Word Embeddings for Large Text Corpora
Avishek Anand, Megha Khosla, Jaspreet Singh +2
Word embeddings are a powerful approach for analyzing language and have been widely popular in numerous tasks in information retrieval and text mining. Training embeddings over hug…
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…
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…
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…
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…
Node Representation Learning for Directed Graphs
Megha Khosla, Jurek Leonhardt, Wolfgang Nejdl +1
We propose a novel approach for learning node representations in directed graphs, which maintains separate views or embedding spaces for the two distinct node roles induced by the…
Interpreting search result rankings through intent modeling
Jaspreet Singh, Avishek Anand
Given the recent interest in arguably accurate yet non-interpretable neural models, even with textual features, for document ranking we try to answer questions relating to how to i…
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…
User Fairness in Recommender Systems
Jurek Leonhardt, Avishek Anand, Megha Khosla
Recent works in recommendation systems have focused on diversity in recommendations as an important aspect of recommendation quality. In this work we argue that the post-processing…
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…