/ADM_HW3

Homework_3 for Algorithmic Methods for Data Mining (ADM), MSc in Data Science at La Sapienza University of Rome

Primary LanguageJupyter NotebookMIT LicenseMIT

ADM : HomeWork 3

Github repository to submit ADM's HomeWork 3 - Places of the world.

Work done and compiled by Group 29 made up of the following members:

  • Maria Vittoria Vestini : 1795724
  • Luca Mazzucco : 1997610

The main content is a Jupyter Notebook file named HW_3.ipynb which shows our results for the proposed questions.
It explains and comments steps and approach to develop three different types of Search Engines:

  • Boolean Search Engine : The first included is a basic search engine that allows users to perform boolean queries.
    It relies on simple text matching to identify relevant results

  • TF-IDF Search Engine : The second uses the tf-idf algorithm to rank the relevance of search results.
    It takes into account both the frequency of the search term in the document and the inverse document frequency, which is a measure of how common the search term is across the entire corpus of documents.

  • Location-Based Search Engine : The third search engine is designed to integrate boolean queries with the user's location to provide location-based results.

The BONUS question was not answered.

Other contents:

  • engine.py → Heart of the search engine:
      It contains a class that includes needed functions for text preprocessing and
      and results retrieving from inverted indexes.

  • AlgorithmicQ_CommandLine.ipynb → shows results for Algorithmic Question and Command Line

  • CommandLine.sh → is the bash shell script file for the CommandLine Question.

NOTE :

GitHub doesn't display interactive maps for task number 4, suggested to have a look here instead