Neural Network for Snippets

A favorite topic, how do we make sense and value of written knowledge?

A Neural Network to Extract Knowledgeable Snippets and Documents 

Tech Xplore   By Ingrid Fadelli

Chinese Academy of Sciences researchers have created a convolutional neural network (CNN)-based model to extract knowledgeable snippets and annotate documents. The model can outperform current analytical tools while undergoing shorter training periods. The model is designed to comprehend the abstract concept of documents in different domains collaboratively and evaluate whether a document is knowledgeable, defined as one "containing multiple knowledgeable snippets, which describe concepts, properties of entities, or the relations among entities." The researchers say the network structure of their SSNN joint CNN-based model is "low-level Sharing, high-level Splitting," in which the low-level layers are shared for different domains while the high-level layers outside the network receive separate training to identify the differences of dissimilar domains. The team assessed SSNN's effectiveness on a dataset of real documents from three content domains on the WeChat messaging/social media/mobile payment platform. The model performed consistently better than other CNN models while saving time and memory usage due to shorter and more efficient training processes. In the future, the model could help build comprehensive knowledge databases and innovative services that answer user queries in real time. .... "