DrAlzahraniProjects/csusb_fall2024_cse6550_team1
Nov 2024 – Nov 2024
1 Month active
Languages Used
Python
Technical Skills
Data CleaningNatural Language ProcessingWeb Scraping
bhavya
PROFILE
Bhavya
During November 2024, the developer contributed to the DrAlzahraniProjects/csusb_fall2024_cse6550_team1 repository by building an HTML cleaning feature for retrieval-augmented generation data preprocessing. They implemented a Python-based sanitizer in RAG.py using BeautifulSoup, focusing on removing scripts, styles, headers, footers, and navigation elements from raw HTML. This approach improved the quality of extracted text, reducing noise in the data pipeline and supporting more accurate downstream retrieval and generation. The work demonstrated practical application of data cleaning, web scraping, and natural language processing skills, delivering a focused solution to enhance data quality for information retrieval systems.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
35
Activity Months1
Your Network
42 people
Work History
November 2024
1 Commits • 1 Features
Nov 1, 2024November 2024 monthly summary: Delivered HTML cleaning for RAG data preprocessing to improve data quality for the retrieval-augmented generation system. Implemented a BeautifulSoup-based sanitizer in RAG.py to strip scripts, styles, headers, footers, and navigation elements from raw HTML before text extraction, resulting in cleaner, more relevant text for indexing and retrieval. This reduces noise in the data pipeline, enhancing retrieval accuracy and downstream generation reliability.
1 Commits • 1 Features
Nov 1, 2024November 2024 monthly summary: Delivered HTML cleaning for RAG data preprocessing to improve data quality for the retrieval-augmented generation system. Implemented a BeautifulSoup-based sanitizer in RAG.py to strip scripts, styles, headers, footers, and navigation elements from raw HTML before text extraction, resulting in cleaner, more relevant text for indexing and retrieval. This reduces noise in the data pipeline, enhancing retrieval accuracy and downstream generation reliability.
November 2024
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance60.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Data CleaningNatural Language ProcessingWeb Scraping
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