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Analyzing the text of Airbnb property listings and building two different Search Engines that, given as input a query, return the houses that match the query.

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JoannaBroniarek/NLP-Data-Analysis-AirBnb

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Find the perfect place to stay in Texas!

Joanna Broniarek, Alice Shirinà, Daniele Sanna.

The project consists in analyzing the text of Airbnb property listings and building two different Search Engines that, given as input a query, return the houses that match the query.

Data Source

  • Airbnb_Texas_Rentals.csv https://www.kaggle.com/PromptCloudHQ/airbnb-property-data-from-texas

Jupyter Notebooks Descriptions

  1. Homework_3.ipynb - This jupyter notebook contains the implementation of Search_Engine_1, Search_Engine_2 and the definition of scoring functions. Some of the used functions are located in the function.py file.

For correct working of Search Engines it is necessary to run Creating_Files.ipyn notebook. Search Engine 1 is using "vocabulary.txt", "inv_indx.txt" files. Search Engine 2 is using "vocabulary.txt", "inv_indx_tfidf.txt" files.

  1. Creating_Files.ipynb - In this notebook we create and save the following files "vocabulary.txt", "inv_indx.txt", "inv_indx_tfidf.txt" according to the data.

  2. GeoMap.ipynb - There is an implementation of the Geomap for searching documents according to their locations.

Scripts

  1. functions.py - external file with definitions of functions used in the Homework_3 notebook.

Technology

  • Python 3.6.4

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Analyzing the text of Airbnb property listings and building two different Search Engines that, given as input a query, return the houses that match the query.

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