Transforming unstructured text into structured and meaningful forms, organized by useful
category labels, is a fundamental step in text mining for downstream analysis and …

Legal case retrieval is a special Information Retrieval (IR) task focusing on legal case
documents. Depending on the downstream tasks of the retrieved case documents, users' …

The exchange of meta-information has always formed part of information behavior. In this
article, we show that this rule also extends to conversational search. Information about the …

Deep Learning Hard (DL-HARD) is a new annotated dataset designed to more effectively
evaluate neural ranking models on complex topics. It builds on TREC Deep Learning (DL) …

Abstract Visual Question Answering (VQA) entails answering questions about images. We
introduce the first VQA dataset in which all contents originate from an authentic use case …

We present an approach to identify argumentative questions among web search queries.
Argumentative questions ask for reasons to support a certain stance on a controversial topic …

We adapt previous literature on search tasks for developing a domain-specific search
engine that supports the search tasks of policy workers. To characterise the search tasks we …

With large language models (LLMs), conversational search engines shift how users retrieve
information from the web by enabling natural conversations to express their search intents …

Conversational Search (CS) is the task of retrieving relevant documents from a corpus within
a conversational context, combining retrieval with conversational context modeling. With the …

Understanding debtor personas is crucial for collectors to empathize with debtors and
develop more effective collection strategies. In this paper, we take the first step towards …