Sentiment Analysis Platform

Large-Scale NLP Processing System

Built a distributed sentiment analysis platform processing over 3 billion data points with 30% accuracy improvement using PaddlePaddle and Elasticsearch.

Overview

Developed a comprehensive sentiment analysis platform capable of processing massive amounts of social media and news data. The system improved model accuracy by 30% compared to previous solutions and successfully handled over 3 billion data points.

Key Features

Real-time sentiment analysis

Multi-language support

Scalable microservices architecture

Custom model training pipeline

Analytics dashboard

Challenges

Processing 3+ billion data points

Real-time analysis requirements

Model accuracy optimization

System scalability

Solutions

Implemented distributed processing with Kubernetes

Optimized models using PaddlePaddle framework

Built efficient data pipeline with Elasticsearch

Applied advanced NLP techniques

Results & Impact

Processed over 3 billion data points

Achieved 30% improvement in accuracy

Deployed scalable microservices architecture

Reduced processing time by 50%

Project Info

Role

Senior Software Engineer

Company

Big Data Co., Ltd.

Timeline

2021-12 - 2023-04

1 year 5 months

Technologies

PythonPaddlePaddleElasticsearchDockerKubernetesRabbitMQRedis