Related papers: Query-Focused Scenario Construction
Many financial jobs rely on news to learn about causal events in the past and present, to make informed decisions and predictions about the future. With the ever-increasing amount of news available online, there is a need to automate the…
We present a new context based event indexing and event ranking model for News Articles. The context event clusters formed from the UNL Graphs uses the modified scoring scheme for segmenting events which is followed by clustering of events.…
With the implementation of the new EU regulation 2022/1426 regarding the type-approval of the automated driving system (ADS) of fully automated vehicles, scenario-based testing has gained significant importance in evaluating the performance…
Scaling clustering algorithms to massive data sets is a challenging task. Recently, several successful approaches based on data summarization methods, such as coresets and sketches, were proposed. While these techniques provide provably…
In most of today's emergency scenarios information plays a crucial role. Therefore, information has to be constantly collected and shared among all rescue team members and this requires new innovative technologies. In this paper a…
In today's world, we follow news which is distributed globally. Significant events are reported by different sources and in different languages. In this work, we address the problem of tracking of events in a large multilingual stream.…
We describe a gold standard corpus of protest events that comprise of various local and international sources from various countries in English. The corpus contains document, sentence, and token level annotations. This corpus facilitates…
In stochastic optimisation, the large number of scenarios required to faithfully represent the underlying uncertainty is often a barrier to finding efficient numerical solutions. This motivates the scenario reduction problem: by find a…
In order to extract event information from text, a machine reading model must learn to accurately read and interpret the ways in which that information is expressed. But it must also, as the human reader must, aggregate numerous individual…
The goal of sequential event prediction is to estimate the next event based on a sequence of historical events, with applications to sequential recommendation, user behavior analysis and clinical treatment. In practice, the next-event…
Many prediction tasks of real-world applications need to model multi-order feature interactions in user's event sequence for better detection performance. However, existing popular solutions usually suffer two key issues: 1) only focusing…
Media narratives wield tremendous power in shaping public opinion, yet computational approaches struggle to capture the nuanced storytelling structures that communication theory emphasizes as central to how meaning is constructed. Existing…
Clustering web documents has numerous applications, such as aggregating news articles into meaningful events, detecting trends and hot topics on the Web, preserving diversity in search results, etc. At the same time, the importance of named…
Computational modeling is crucial for understanding and analyzing complex systems. In biology, model creation is a human dependent task that requires reading hundreds of papers and conducting wet lab experiments, which would take days or…
Content analysis of news stories (whether manual or automatic) is a cornerstone of the communication studies field. However, much research is conducted at the level of individual news articles, despite the fact that news events (especially…
People from all over the world use social media to share thoughts and opinions about events, and understanding what people say through these channels has been of increasing interest to researchers, journalists, and marketers alike. However,…
Automatic summarization of mass-emergency events plays a critical role in disaster management. The second edition of CrisisFACTS aims to advance disaster summarization based on multi-stream fact-finding with a focus on web sources such as…
When optimizing problems with uncertain parameter values in a linear objective, decision-focused learning enables end-to-end learning of these values. We are interested in a stochastic scheduling problem, in which processing times are…
We propose a method for online news stream clustering that is a variant of the non-parametric streaming K-means algorithm. Our model uses a combination of sparse and dense document representations, aggregates document-cluster similarity…
Query suggestion refers to the task of suggesting relevant and related queries to a search engine user to help in query formulation process and to expedite information retrieval with minimum amount of effort. It is highly useful in…