15 citations · 71 across the 12 of their papers we have counts for
12 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…
Resource Selection for Federated Search on the Web
Dong Nguyen, Thomas Demeester, Dolf Trieschnigg +1
A publicly available dataset for federated search reflecting a real web environment has long been absent, making it difficult for researchers to test the validity of their federate…
Beyond Movie Recommendations: Solving the Continuous Cold Start Problem in E-commerceRecommendations
Julia Kiseleva, Alexander Tuzhilin, Jaap Kamps +6
Many e-commerce websites use recommender systems or personalized rankers to personalize search results based on their previous interactions. However, a large fraction of users has…
Predicting Relevance based on Assessor Disagreement: Analysis and Practical Applications for Search Evaluation
Thomas Demeester, Robin Aly, Djoerd Hiemstra +2
Evaluation of search engines relies on assessments of search results for selected test queries, from which we would ideally like to draw conclusions in terms of relevance of the re…
Determine the User Country of a Tweet
Han van der Veen, Djoerd Hiemstra, Tijs van den Broek +2
In the widely used message platform Twitter, about 2% of the tweets contains the geographical location through exact GPS coordinates (latitude and longitude). Knowing the location…
Separate Training for Conditional Random Fields Using Co-occurrence Rate Factorization
Zhemin Zhu, Djoerd Hiemstra, Peter Apers +1
The standard training method of Conditional Random Fields (CRFs) is very slow for large-scale applications. As an alternative, piecewise training divides the full graph into pieces…
A database approach to information retrieval: The remarkable relationship between language models and region models
Djoerd Hiemstra, Vojkan Mihajlovic
In this report, we unify two quite distinct approaches to information retrieval: region models and language models. Region models were developed for structured document retrieval.…
MIREX: MapReduce Information Retrieval Experiments
Djoerd Hiemstra, Claudia Hauff
We propose to use MapReduce to quickly test new retrieval approaches on a cluster of machines by sequentially scanning all documents. We present a small case study in which we use…