Unifying Text, Metadata, and User Network Representations with a Neural Network for Geolocation Prediction

We then propose MetaMLAnn , a neural network based approach to infer microbial communities of unsampled locations given the information from multiple data sources in the

In this paper, we propose to use a Recurrent Neural Network (RNN) to model each user’s posting behaviors on Twitter and incorporate their neighbors’ topic-associated context

In this study, we comprehensively investigate the per- formance of recurrent neural network (i.e., LSTM) on clinical entity recognition and protected health informa- tion

In this dissertation, Neural Network technique is used for developing prediction models for five different versions (2.0, 2.1, 3.0, 3.1, and 3.2) of Eclipse that will assign

In Neural Network based approaches, a number of models for text classifications exist; for exam- ple, Feed-Forward Neural Network model using an average of embeddings of target

This paper presents my research in neural network approach for text messages categorization of collaborative learning skill in online discussion.. Despite of

The authors of this paper propose an alternative approach to the standard RNN used for text generation, which is Recurrent Neural Network Language Model (RNNLM).. What they propose

To resolve the problems, we aim to model the credit risk prediction on dynamic graphs and propose a Temporal- Aware Graph Neural Network (TemGNN) to predict user credit risk. In