localebnb - an airbnb contextual recommender
TRANSCRIPT
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LocalebnbAn Airbnb Contextual Recommender
-G Scott Stukey
(NOTE: best viewed by downloading the PPT)
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Motivation
When booking a private residence, how do you find the perfect neighborhood?
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Problem
No ability to search or
filter by trait!
Airbnb search results
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Problem
No ability to search or
filter by trait!
Airbnb search results
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Hypothesis
Use Airbnb listing descriptions to predict neighborhood traits & customize search results to users’ preferences
Why Airbnb should implement this:
1. Increase user satisfaction by increasing relevance
2. Increase booking rate by reducing bounces (click fatigue)
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SolutionListing Page Neighborhood Guide
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SolutionListing Page Neighborhood Guide
Features
Target
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Scraped Search Results & ListingsETL Scraped Neighborhood
Traits
Cleaned Documents(lemmatization, expand contractions, et al.)Prepping
Modeling Word2Vec / Doc2Vec Naïve
Bayes Random Forest / GBC
Rank/Sort Implemented Custom Scoring Function (inspired by Google Search CTR by position)
MethodologyBeautiful
Soup
NLTK
Word2Vec
+
SVM
TF-IDF Vectorization
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Insights
78-82% accuracy
5 pt liftover naïve bayes
SVM Forest TF-IDFInfrequent words
add value
Airbnb is for foodies
Neighborhood names dominate feature
importance
‘artsy’ model key words doc frequency
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Extensions
• Scrape more descriptions across more cities• Include additional listing information in models• Make neighborhood traits more fluid• Give partial weight to nearby neighborhoods utilizing graph
analytics
How Airbnb could benefit:
• Guide creation of neighborhood guides in new cities
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Thank YouGo to Localebnb.co to try for yourselves.
@gscottstukey