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FoodForThought

Background

Normally, it is human nature to see product/restaurant review before purchasing/dininig. But it reviews doesn't quantify the product. For example if restaurant reviews are good doesn't mean that all dishes in the restaurant are good vice versa.

Solution

Generate itemized sentiment of product using reviews.

Process

  1. Data preparation

         - Get restaurant information. Name, Place, Reviews and Food Menu.

         - Get food details to generate food mentions from reviews

  1. Train matcher to extract mentions from review

  2. Match food menu item with mention to generate itemized sentiment.

Prerequisite

  • Python2.7 need to be installed
  • Scala2.10 need to be installed
  • Apache Spark need to be configured on local machine or cluster.
  • Install Spacy and configure spacy english corpus

      pip install spacy==1.9.0
      python -m spacy.en.download all

Run

Cleanse data with spark

spark-submit python/generate_data.py --master local[4] --driver-memory 2g --executor-memory 2g

Train spacy matcher

python python/match_trainer.py

Run analysis

python python/analysis.py

Output

restaurant_name restaurant_items review_id review_text mention_text sentiment
King Palace butter chicken-chicken tikka masala-ginger chicken-kashmiri chicken-beef chilli-beef nihari-chicken curry-lamb kidney-haalem-shrimp curry-mango chicken-beef chilli-aloo palak-palak paneer-vegetable pulav-chicken pulav-mutter pulav-chicken pulav Vxs3pjcVGQWxNSil0fU-kg Had Butter chicken with rice there yesterday. The food was not fresh. Extremely overpriced for the quality. They should probably cut the prices in half there, because the service/food is not worth it. butter chicken 2
Aloha Hawaiian Bbq chicken mix-seafood combo-fried shrimp sandwich-pork sandwich-hamburger steak-garlic shrimp-bbq pork 02c6UETmG6iXHnN0Ymqddw Not the best in Vegas but pretty good. They deliver too and that's awesome, especially if you lazy. Love their hamburger steak and musubis! hamburger steak 5

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