In this project, Vector Space Model is implemented for information retrieval. The weighting scheme used for VSM model is tf * idf scores which is a combination of both tf (term frequency of term t in a document) and idf (inverse document frequency computing as (log(df)/ N).
The dataset for this model is a collection of 448 abstracts of some computer science journal. The language of all these documents are English. In addition to this, stopwords file for preprocesing and gold-queries results for validation testing is also provided.
The UI is rendered on HTML Template via FastAPI **Steps to excute FastAPI app
- py -m pip install fastapi uvicorn Jinja2
- py -m uvicorn filename:app --reload
- In the output, there is a line something like:
INFO: Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit) That line shows the URL where your app is being served, in your local machine.
- Open the browser at http://127.0.0.1:8000.
