PRO-SER: Project Search Engine & Repository Using Pattern Matching & NLP

This brief synopsis on the title PRO-SER: Project Search Engine and Repository using Pattern Matching and NLP, introduces and examines the idea of academic project search engine predicated on the few recently done industry implementation and research studies, directions are supplied on the best way to enhance the search techniques for search engine and search motors with several model search engines like Google Scholar Search engine, Bing Scholar Search Engine, IEEE Xplore Search engine, Quora Search Engine, Stack Overflow Search Engine, Amazon Search Engine, Facebook Search Engines. This project report deliberates on use of python as a programming language along with Flask Library with the use of advanced Machine Learning tools and techniques along with Search techniques and algorithms like Cosine Similarity. Advanced features like Auto suggestion, and pattern matching along with Python File Handling concepts are also being incorporated to make search experience better. The design towards search engine is like the engine iterates over the data, by finding and counting words that are similar and for the recommendation after finding similar ones, the engine checks the current project title of the source and compares with the corresponding project title of the similar targets and then finds the project title that is next.