Publications (10)
Document Filtering for Long-tail Entities
Ridho Reinanda, Edgar Meij, Maarten de Rijke
Filtering relevant documents with respect to entities is an essential task in the context of knowledge base construction and maintenance. It entails processing a time-ordered strea…
Novel Entity Discovery from Web Tables
Shuo Zhang, Edgar Meij, Krisztian Balog +1
When working with any sort of knowledge base (KB) one has to make sure it is as complete and also as up-to-date as possible. Both tasks are non-trivial as they require recall-orien…
News Article Retrieval in Context for Event-centric Narrative Creation
Nikos Voskarides, Edgar Meij, Sabrina Sauer +1
Writers such as journalists often use automatic tools to find relevant content to include in their narratives. In this paper, we focus on supporting writers in the news domain to d…
Identifying Notable News Stories
Antonia Saravanou, Giorgio Stefanoni, Edgar Meij
The volume of news content has increased significantly in recent years and systems to process and deliver this information in an automated fashion at scale are becoming increasingl…
Benchmark Granularity and Model Robustness for Image-Text Retrieval
Mariya Hendriksen, Shuo Zhang, Ridho Reinanda +3
Image-Text Retrieval (ITR) systems are central to multimodal information access, with Vision-Language Models (VLMs) showing strong performance on standard benchmarks. However, thes…
Evaluating the Calibration of Knowledge Graph Embeddings for Trustworthy Link Prediction
Tara Safavi, Danai Koutra, Edgar Meij
Little is known about the trustworthiness of predictions made by knowledge graph embedding (KGE) models. In this paper we take initial steps toward this direction by investigating…
Proceedings of the KG-BIAS Workshop 2020 at AKBC 2020
Edgar Meij, Tara Safavi, Chenyan Xiong +3
The KG-BIAS 2020 workshop touches on biases and how they surface in knowledge graphs (KGs), biases in the source data that is used to create KGs, methods for measuring or remediati…
Dense Retrieval Adaptation using Target Domain Description
Helia Hashemi, Yong Zhuang, Sachith Sri Ram Kothur +3
In information retrieval (IR), domain adaptation is the process of adapting a retrieval model to a new domain whose data distribution is different from the source domain. Existing…
Weakly-supervised Contextualization of Knowledge Graph Facts
Nikos Voskarides, Edgar Meij, Ridho Reinanda +5
Knowledge graphs (KGs) model facts about the world, they consist of nodes (entities such as companies and people) that are connected by edges (relations such as founderOf). Facts e…
Uncertainty over Uncertainty: Investigating the Assumptions, Annotations, and Text Measurements of Economic Policy Uncertainty
Katherine A. Keith, Christoph Teichmann, Brendan O'Connor +1
Methods and applications are inextricably linked in science, and in particular in the domain of text-as-data. In this paper, we examine one such text-as-data application, an establ…