Results 21 to 30 of about 5,654,505 (287)
Recognizing Events in Spatiotemporal Soccer Data
Applied Sciences, 2020 Spatiotemporal datasets based on player tracking are widely used in sports analytics research. Common research tasks often require the analysis of game events, such as passes, fouls, tackles, and shots on goal. However, spatiotemporal datasets usually do
Victor Khaustov, Maxim Mozgovoy
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Modeling Graph Neural Networks and Dynamic Role Sorting for Argument Extraction in Documents
Applied Sciences, 2023 The existing methods for document-level event extraction mainly face two challenges. The first challenge is effectively capturing event information that spans across sentences.
Qingchuan Zhang +4 more
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Detecting and Characterizing Events [PDF]
Proceedings of the 2016 Conference on Empirical Methods in Natural
Language Processing, 2016 Significant events are characterized by interactions between entities (such as countries, organizations, or individuals) that deviate from typical interaction patterns. Analysts, including historians, political scientists, and journalists, commonly read large quantities of text to construct an accurate picture of when and where an event happened, who ...
Allison June-Barlow Chaney +3 more
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Event Detection Explorer: An Interactive Tool for Event Detection Exploration
28th International Conference on Intelligent User Interfaces, 2023 Event Detection (ED) is an important task in natural language processing. In the past few years, many datasets have been introduced for advancing ED machine learning models. However, most of these datasets are under-explored because not many tools are available for people to study events, trigger words, and event mention instances systematically and ...
Wenlong Zhang +5 more
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Rule-Based Non-Intrusive Load Monitoring Using Steady-State Current Waveform Features
Sensors, 2023 Monitoring electricity energy usage can help to reduce power consumption considerably. Among load monitoring techniques, non-intrusive load monitoring (NILM) provides a cost-efficient solution to identify individual load consumption details from the ...
Hussain Shareef +3 more
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TED-S: Twitter Event Data in Sports and Politics with Aggregated Sentiments
Data, 2022 Even though social media contain rich information on events and public opinions, it is impractical to manually filter this information due to data’s vast generation and dynamicity. Thus, automated extraction mechanisms are invaluable to the community. We
Hansi Hettiarachchi +4 more
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Automated Power System Fault Prediction and Precursor Discovery Using Multi-Modal Data
IEEE Access, 2023 Electric power system operators monitor large multi-modal data streams from wide service areas. The current data setups stand to get more complex as utilities add more smart-grid sensors to collect additional data from power system substations and other ...
Mohammad Alqudah +2 more
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EVE: a framework for event detection [PDF]
Evolving Systems, 2012 In this paper, we introduce EVE, a generic framework for event detection where events can also include outliers, model changes and drifts. Various methods for event detection have been proposed for different types of events. However, many of them make the same or very similar prior assumptions but use different notations and formalizations.
Adä, Iris, Berthold, Michael R.
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The Feasibility of Detecting Magnetic Storms With Smartphone Technology
IEEE Access, 2018 In this paper, recent comparison tests are performed on smartphone magnetometer “apps”with a view toward their suitability for detecting and measuring magnetic storm events. Although the iPhone and Samsung smartphone magnetometer sensors in
Sten F. Odenwald
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A Multi-Agent NILM Architecture for Event Detection and Load Classification
Energies, 2020 A multi-agent architecture for a Non-Intrusive Load Monitoring (NILM) solution is presented and evaluated. The underlying rationale for such an architecture is that each agent (load event detection, feature extraction, and classification) outperforms ...
André Eugenio Lazzaretti +11 more
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