Power Grid Monitoring Event Recognition Method Integrating Knowledge Graph and Deep Learning

Named Entity Recognition in Persian Text using Deep Learning

Named entities recognition is a fundamental task in the field of natural language processing. It is also known as a subset of information extraction. The process of recognizing named entities aims at finding proper nouns in the text and classifying them into predetermined classes such as names of people, organizations, and places. In this paper, we propose a named entity recognizer which benefi...

Event Recognition Based on Deep Learning in Chinese Texts

Event recognition is the most fundamental and critical task in event-based natural language processing systems. Existing event recognition methods based on rules and shallow neural networks have certain limitations. For example, extracting features using methods based on rules is difficult; methods based on shallow neural networks converge too quickly to a local minimum, resulting in low recogn...

Integrating Deep Learning and Multiple Instance Learning

Leveraging Complex Event Processing for Grid Monitoring

Currently existing monitoring services for Grid infrastructures typically collect information from local agents and store it as data sets in global repositories. However, for some scenarios querying real-time streams of monitoring information would be extremely useful. In this paper, we evaluate Complex Event Processing technologies applied to real-time Grid monitoring. We present a monitoring ...

Personal Knowledge/Learning Graph

Educational data mining and learning analytics have to date largely focused on specific research questions that provide insight into granular interactions. These insights have been abstracted to include the development of predictive models, intelligent tutors, and adaptive learning. While there are several domains where holistic or systems models have provided additional explanatory power, work...