Recent papers
Please look at Google Scholar to see the list of my most recept up-to-date papers, and be sure to check out https://techatbloomberg.com/ai as well!
News Article Retrieval in Context for Event-centric Narrative Creation
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 develop event-centric narratives. Given an incomplete narrative that specifies a main event and a context, we aim to retrieve news…
Contextualizing Trending Entities in News Stories
Trends are those keywords, phrases, or names that are mentioned most often on social media or in news in a particular timeframe.They are an effective way for human news readers to both discover and stay focused on the most relevant information of the day. In this work, we consider trends…
Uncertainty over Uncertainty: Investigating the Assumptions, Annotations, and Text Measurements of Economic Policy Uncertainty
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 established economic index that measures economic policy uncertainty from keyword occurrences in news. This index, which is shown to correlate with firm investment, employment,…
Evaluating the Calibration of Knowledge Graph Embeddings for Trustworthy Link Prediction
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 the calibration of KGE models, or the extent to which they output confidence scores that reflect the expected correctness of predicted knowledge graph…
Knowledge Graphs: An Information Retrieval Perspective
In this survey, we provide an overview of the literature on knowledge graphs (KGs) in the context of information retrieval (IR). Modern IR systems can benefit from information available in KGs in multiple ways, independent of whether the KGs are publicly available or proprietary ones. We provide an overview of…
CrossBERT: A Triplet Neural Architecture for Ranking Entity Properties
Task-based Virtual Personal Assistants (VPAs) such as the Google Assistant, Alexa, and Siri are increasingly being adopted for a wide variety of tasks. These tasks are grounded in real-world entities and actions (e.g., book a hotel, organise a conference, or requesting funds). In this work we tackle the task of…
Proceedings of the KG-BIAS Workshop 2020 at AKBC 2020
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 remediating bias in KGs, but also identifying other biases such as how and which languages are represented in automatically constructed…
Novel Entity Discovery from Web Tables
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-oriented efforts to determine which entities and relationships are missing from the KB. As such they require a significant…
Identifying Notable News Stories
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 increasingly prevalent. One critical component that is required in such systems is a method to automatically determine how notable a certain news story…