JOURNAL ARTICLE

Contextual Deep Search using Long Short Term Memory Recurrent Neural Network

Mohammad Arifur RahmanFahad AhmedNafis Ali

Year: 2019 Journal:   2019 International Conference on Robotics,Electrical and Signal Processing Techniques (ICREST) Pages: 39-42

Abstract

The internet is teeming with an ocean worth of information and combing through all that in order to find what one wants can become a daunting task if one does not possess the right tools and techniques. This paper explores one such technique, exploiting the rapidly responsive Long-Short Term Memory Recurrent Neural Networks (LSTM-RNNs) by harnessing the machine learning capabilities of neural networks and eventually, provides contextual search results at the finger tips of the user of the system.

Keywords:
Computer science Recurrent neural network Long short term memory Combing Task (project management) Term (time) Artificial intelligence Artificial neural network Deep learning The Internet Machine learning World Wide Web Engineering

Metrics

2
Cited By
0.26
FWCI (Field Weighted Citation Impact)
13
Refs
0.58
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Data Stream Mining Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence
Time Series Analysis and Forecasting
Physical Sciences →  Computer Science →  Signal Processing
Advanced Image and Video Retrieval Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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