6 citations · 7 across the 4 of their papers we have counts for
5 papers
BERT for Target Apps Selection: Analyzing the Diversity and Performance of BERT in Unified Mobile Search
Negin Ghasemi, Mohammad Aliannejadi, Djoerd Hiemstra
A unified mobile search framework aims to identify the mobile apps that can satisfy a user's information need and route the user's query to them. Previous work has shown that resou…
Exploring task-based query expansion at the TREC-COVID track
Thomas Schoegje, Chris Kamphuis, Koen Dercksen +3
We explore how to generate effective queries based on search tasks. Our approach has three main steps: 1) identify search tasks based on research goals, 2) manually classify search…
Reducing Misinformation in Query Autocompletions
Djoerd Hiemstra
Query autocompletions help users of search engines to speed up their searches by recommending completions of partially typed queries in a drop down box. These recommended query aut…
Comparing Rule-based, Feature-based and Deep Neural Methods for De-identification of Dutch Medical Records
Jan Trienes, Dolf Trieschnigg, Christin Seifert +1
Unstructured information in electronic health records provide an invaluable resource for medical research. To protect the confidentiality of patients and to conform to privacy regu…
Recommending Users: Whom to Follow on Federated Social Networks
Jan Trienes, Andrés Torres Cano, Djoerd Hiemstra
To foster an active and engaged community, social networks employ recommendation algorithms that filter large amounts of contents and provide a user with personalized views of the…