Related papers: An Event Network for Exploring Open Information
Event datasets in the financial domain are often constructed based on actual application scenarios, and their event types are weakly reusable due to scenario constraints; at the same time, the massive and diverse new financial big data…
Event detection on social media has attracted a number of researches, given the recent availability of large volumes of social media discussions. Previous works on social media event detection either assume a specific type of event, or…
Social networks are quickly becoming the primary medium for discussing what is happening around real-world events. The information that is generated on social platforms like Twitter can produce rich data streams for immediate insights into…
Event prediction is the ability of anticipating future events, i.e., future real-world occurrences, and aims to support the user in deciding on actions that change future events towards a desired state. An event prediction method learns the…
In this paper, we define event expression over sentences of natural language and semantic relations between events. Based on this definition, we formally consider text understanding process having events as basic unit.
Social Media websites have disseminated digital devices to the public, making information sharing easier and faster. Exchanging textual data is the most popular communication among social media users. It has become a necessity for…
We investigate a graph-based approach to exploratory data analysis in the context of network security monitoring. Given a possibly large batch of event logs describing ongoing activity, we first represent these events as a bipartite…
Extracting key information from documents represents a large portion of business workloads and therefore offers a high potential for efficiency improvements and process automation. With recent advances in Deep Learning, a plethora of Deep…
This paper examines the summarization of events that evolve through time. It discusses different types of evolution taking into account the time in which the incidents of an event are happening and the different sources reporting on the…
Event-specific concepts are the semantic concepts designed for the events of interest, which can be used as a mid-level representation of complex events in videos. Existing methods only focus on defining event-specific concepts for a small…
Extracting informative arguments of events from news articles is a challenging problem in information extraction, which requires a global contextual understanding of each document. While recent work on document-level extraction has gone…
We consider the problem of event detection based upon a (typically multivariate) data stream characterizing some system. Most of the time the system is quiescent - nothing of interest is happening - but occasionally events of interest…
Event Detection (ED) aims to identify event trigger words from a given text and classify it into an event type. Most of current methods to ED rely heavily on training instances, and almost ignore the correlation of event types. Hence, they…
This report describes and illustrates several modelling techniques proposed by Communication Analysis; namely Communicative Event Diagram, Message Structures and Event Specification Templates. The Communicative Event Diagram is a business…
EventNet is a large-scale video corpus and event ontology consisting of 500 events associated with event-specific concepts. In order to improve the quality of the current EventNet, we conduct the following steps and introduce EventNet…
The probing classifiers framework has been employed for interpreting deep neural network models for a variety of natural language processing (NLP) applications. Studies, however, have largely focused on sentencelevel NLP tasks. This work is…
Statistical analysis on networks has received growing attention due to demand from various emerging applications. In dynamic networks, one of the key interests is to model the event history of time-stamped interactions amongst nodes. We…
Event extraction, the technology that aims to automatically get the structural information from documents, has attracted more and more attention in many fields. Most existing works discuss this issue with the token-level multi-label…
This paper concerns an Information Extraction process for building a dynamic Legislation Network from legal documents. Unlike supervised learning approaches which require additional calculations, the idea here is to apply Information…
Event data is the basis for all process mining analysis. Most process mining techniques assume their input to be an event log. However, event data is rarely recorded in an event log format, but has to be extracted from raw data. Event log…