Modeling Retrieval Problem using Neural Networks

Despite the buzz surrounding deep neural networks (DNN) models for information retrieval, the literature is still lacking a systematic basic investigation on how generally we can model the retrieval problem using neural networks. Modeling the retrieval problem in the context of neural networks means the general way that we frame the problem with regards to […]

Hierarchical Re-estimation of Topic Models for Measuring Topical Diversity

Our paper "Hierarchical Re-estimation of Topic Models for Measuring Topical Diversity", with Hosein Azarbonyad, Tom Kenter, Maarten Marx, Jaap Kamps, and Maarten de Rijke, has been accepted as a long paper at The 39th European Conference on Information Retrieval (ECIR'17). \o/ Quantitative notions of topical diversity in text documents are useful in several contexts, e.g., […]

Telling how to narrow it down: Effect of Browsing Path Recommendation on Exploratory Search

Our paper "Telling how to narrow it down: Effect of Browsing Path Recommendation on Exploratory Search", with Glorianna Jagfeld, Hosein Azarbonyad, Alex Olieman, Jaap Kamps, Maarten Marx, has been accepted as a short paper at The ACM SIGIR Conference on Human Information Interaction & Retrieval (CHIIR'17). \o/ There are several information needs requiring sophisticated human-computer […]

Poison Pills and Antidots: Inoculating Relevance Feedback

"Poison Pills and Antidots: Inoculating Relevance Feedback", an article published in Amsterdam Science Magazine as one of the cool contributions of our CIKM2016 paper. We also have a extended abstract describing this part, accepted to be presented in DIR2016 "Inoculating Relevance Feedback Against Poison Pills", with Hosein Azarbonyad, Jaap Kamps, Djoerd Hiemstra and Maarten Marx. […]

ICTIR 2016 BEST PAPER AWARD

We have got the "Best paper Award" in The ACM International Conference on the Theory of Information Retrieval (ICTIR2016) for our paper "On Horizontal and Vertical Separation in Hierarchical Text Classification". \o/ Please take a look at my posts on "From Probability Ranking Principle to Strong Separation Principle", and "Two-dimensional separability in Hierarchical Text Classification") for more information on […]

The Healing Power of Poison: Helpful Non-relevant Documents in Feedback

Our paper "The Healing Power of Poison: Helpful Non-relevant Documents in Feedback", with Samira Abnar and Jaap Kamps, has been accepted as a short paper at The 25th ACM International Conference on Information and Knowledge Management (CIKM'16). \o/ Query expansion based on feedback information is one of the classic approaches for improving the performance of […]

Luhn Revisited: Significant Words Language Models

Our paper "Luhn Revisited: Significant Words Language Models", with Hosein Azarbonyad, Jaap Kamps, Djoerd Hiemstra and Maarten Marx, has been accepted as a long paper at The 25th ACM International Conference on Information and Knowledge Management (CIKM'16). \o/ On of the key factors affecting search quality is the fact that our queries are ultra-short statements […]

On Horizontal and Vertical Separation in Hierarchical Text Classification

Our paper "On Horizontal and Vertical Separation in Hierarchical Text Classification", with Hosein Azarbonyad, Jaap Kamps, and Maarten Marx, has been accepted as a long paper at The ACM International Conference on the Theory of Information Retrieval (ICTIR'16). \o/ Hierarchy is an effective and common way of representing information and many real-world textual data can […]