Project to study information retrieval and e-commerce search topics like Relevance tuning, NLP, semantic search, LTR, ....

• Elasticsearch (> 6.0)
• Python 3
• Yelp free dataset

First run virtualevn:

1. cd saiyan
2. virtualenv venv
3. source venv/bin/activate
4. $pip3 install -r requirements.txt

Then run indexer:

• everything: $python indexer.py or $python indexer.py all
• Only places: $python indexer.py places
• Only photos: $python indexer.py photos
• Only reviews: $python indexer.py reviews
• Categories: $python category_indexer.py

1. cd saiyan
2. virtualenv venv
3. source venv/bin/activate
4. python3 -m flask run

1. cd saiyan/frontend
2. virtualenv venv
3. source venv/bin/activate
4. python3 -m http.server

• search: /search?q=term
• explore: /explore?q=term
• extract: /explore?q=text

• search: /#/ (compare match strategies and highlights found terms)
• visualize: /#/visualize (visualize rank changes through photos)
• extract: /#/visualize (extract entities)

Yelp free dataset: https://www.yelp.com/dataset (thanks)

Flask + AngularJs inspired by: https://github.com/bonzanini/CheerMeApp-demo (thanks)