Titlebook: Web Information Systems Engineering – WISE 2020; 21st International C Zhisheng Huang,Wouter Beek,Yanchun Zhang Conference proceedings 2020

GLOSS

Automatic Action Extraction for Short Text Conversation Using Unsupervised Learninga burden on workers. There is a necessity to analyze large amounts of data automatically to extract actionable information. Multiple studies were conducted on action extraction to identify actions such as promises and requests. Most of these studies used supervised learning methods. The key problem

难解

esculent

犬儒主义者

合适

A Text Mining Approach to Extract and Rank Innovation Insights from Research Projectsdeas to innovate. Recently, commercial and research projects have undergone an exponential growth, leading the open challenge of identifying possible insights on interesting aspects to work on. The existing literature has focused on the identification of goals, topics, and keywords in a single piece

Pillory

An Active Learning Based Hybrid Neural Network for Joint Information Extractiono tackle this challenging problem, we firstly propose a joint machine extraction method based on a hybrid neural network which takes three common NLP tasks—named entity recognition (NER), relation extraction (RE) and event extraction (EE) into consideration. Then, based on the joint model, we propos

嘲笑

轻率的你

ABLA: An Algorithm for Repairing Structure-Based Locators Through Attribute Annotationsneed to extract information, this growth also has brought the necessity to adapt web pages to user requirements, create annotations or test web applications. Due to the evolution of web pages, the complexity of the implementation of these techniques has increased. Being able to test, annotate, adapt

perimenopause

Automatic Action Extraction for Short Text Conversation Using Unsupervised Learninga burden on workers. There is a necessity to analyze large amounts of data automatically to extract actionable information. Multiple studies were conducted on action extraction to identify actions such as promises and requests. Most of these studies used supervised learning methods. The key problem

MANIA

A Densely Connected Encoder Stack Approach for Multi-type Legal Machine Reading Comprehensionach of MRC is the deep neural network based model which learns multi-level semantic information with different granularities layer by layer, and it converts the original data from shallow features into abstract features. Owing to excessive abstract semantic features learned by the model at the top o