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Case Study

News Content Aggregation Engine

Real-time news aggregation from 1,000+ global sources.

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Key Results

1,000+ sources
15 languages supported
< 5min latency
98% classification accuracy

The Challenge

Processing news in multiple languages, detecting duplicate stories across outlets, and providing real-time categorization with minimal latency.

The Solution

Deployed multilingual BERT models for classification and used locality-sensitive hashing for near-duplicate detection across languages.

Overview

Built a news aggregation platform that collects, categorizes, and summarizes news articles from over 1,000 global news sources in 15 languages.

Tech Stack

PythonTransformersPostgreSQLAirflowDocker

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