CEP-Wizard: Automatic Deployment of Distributed Complex Event Processing

Shin, Yooju; Yoon, Susik; Trirat, Patara; Lee, Jae-Gil

doi:10.1109/icde.2019.00225

Cited by 5 publications

(2 citation statements)

References 7 publications

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“…organizations to make strategic decisions. This calls for practical solutions for online news story discovery, thereby enabling downstream tasks such as summarization and recommendation [12,24,45], event detection and tracking [34,49,50], and curation (e.g., Google News).…”

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confidence: 99%

SCStory: Self-supervised and Continual Online Story Discovery

Yoon

Lee

2023

Proceedings of the ACM Web Conference 2023

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We present a framework SCStory for online story discovery, that helps people digest rapidly published news article streams in realtime without human annotations. To organize news article streams into stories, existing approaches directly encode the articles and cluster them based on representation similarity. However, these methods yield noisy and inaccurate story discovery results because the generic article embeddings do not effectively reflect the storyindicative semantics in an article and cannot adapt to the rapidly evolving news article streams. SCStory employs self-supervised and continual learning with a novel idea of story-indicative adaptive modeling of news article streams. With a lightweight hierarchical embedding module that first learns sentence representations and then article representations, SCStory identifies story-relevant information of news articles and uses them to discover stories. The embedding module is continuously updated to adapt to evolving news streams with a contrastive learning objective, backed up by two unique techniques, confidence-aware memory replay and prioritized-augmentation, employed for label absence and data scarcity problems. Thorough experiments on real and the latest news data sets demonstrate that SCStory outperforms existing state-of-the-art algorithms for unsupervised online story discovery.

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confidence: 99%

SCStory: Self-supervised and Continual Online Story Discovery

Yoon

Lee

2023

Proceedings of the ACM Web Conference 2023

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“…Isso é feito para tentar manter o sistema disponível pelo maior tempo possível, mesmo que nem todos os eventos inseridos possam ser processados. Shin et al (2019) criaram um sistema de distribuição independente das ferramentas de detecção de CEP, chamado CEP-Wizard, onde o usuário passa informações sobre o uso de recursosdo sistema e sobre o tipo de evento a ser detectado e o sistema define em qual nó esse tipo de evento será alocado. O uso de informações como o tipo e a taxa de fluxo dos eventos de entrada permite que o sistema consiga distribuir a alocação para que o uso de recursos seja igualmente distribuído.…”

Section: Distribuição De Tipos De Evento Baseada Em Desempenhounclassified

Processamento de eventos complexos nativo de nuvem para cidades inteligentes

Scattone¹

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Durante o tempo de duração do mestrado, passei por várias fases de aprendizado, onde tive a sorte de encontrar várias pessoas que se tornaram meus colegas e amigos. Primeiramente, tenho que reconhecer o valor do apoio que meus amigos da graduação, que influenciaram na minha decisão de vir para o IME-USP na pós-graduação e me apoiaram psicologicamente durante todo o curso o mestrado, sempre que pedia ajuda, Fernando Augusto Joaquim, Lucas Magno, Rafaela Gesing, Naim Elias Comar, Fábio Chagas da Silva, Rodrigo Frausino e muitos outros que conheci durante minha graduação no Instituto de Física. No primeiro ano, onde cursei todas as disciplinas obrigatórias, as quais não tinha certeza de que estava preparado para cursar, foi ótimo poder me aproximar e contar com o apoio, técnico e emocional, da minha colega de orientadora e amiga próxima, Fernanda de Camargo Magano e da sua turma de amigos do curso de Computação,

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Distributed mobile CEP for collaborative social computing

Pérez-Vereda,

Canal,

Hervás

2024

Computing

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Smartphones have become highly personalized interfaces between people and the technology ecosystem around them. In this sense, they play a key role for a technology shift from the current Internet of Things to a future human-centric paradigm of an Internet of People, automatically adapting smart things and services to the preferences and context of their users. In this paper, we propose the use of Complex Event Processing (CEP) engines deployed in the users’ smartphones granting them context-awareness capabilities in order to react to external stimulus, and enabling them to interact both with smart things and services in the surroundings of the users. With that purpose, we have designed a communication architecture that interconnects CEP engines running on smartphones, providing a framework for building applications for Mobile-based Collaborative Social Computing (MCSC). For that, we make use of previous works of the authors with Digital Avatars, a framework which promotes the use of smartphones for inferring and sharing a unique digital avatar or virtual profile of each user. The resulting framework, which we have called Collaborative CEP, allows to implement complex interactions among users, and between them and the IoT, a common need in Collaborative Social Computing applications. We provide a proof of concept based on the implementation of a Cops and Robbers game to test the expressiveness and correct functioning of the framework, and we evaluate its performance and efficiency.

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CEP-Wizard: Automatic Deployment of Distributed Complex Event Processing

Cited by 5 publications

References 7 publications

SCStory: Self-supervised and Continual Online Story Discovery

SCStory: Self-supervised and Continual Online Story Discovery

Processamento de eventos complexos nativo de nuvem para cidades inteligentes

Distributed mobile CEP for collaborative social computing

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