Information_retrieval

Search Personalization

• Topics can be marked as interesting by the user and causes a re-ranking of the results if the user is searching for the same query or if a new search is performed.
• The task was to create web search engine using Solr, parses and indexes .txt and .jpg documents that a given folder contains and to list top 10 relevant files given a query.
• Dataset created using the download.py file. The result obtained is a json file compatible for combining all the documents and types.
• After indexing the file by Solr, the user can enter their query and search query and the top relevant results will be shown on the screen with the rank assigned to the document.

Technologies used during the development

Frontend

1. Angular
2. Apache Solr

Backend

1. Java
2. Python
3. Lucene-8.7.0

Angular project

This project was generated with Angular CLI version 11.0.6.

Code scaffolding

Run ng generate component component-name to generate a new component. You can also use ng generate directive|pipe|service|class|guard|interface|enum|module.

Development server

Run ng serve for a dev server. Navigate to http://localhost:4200/. The app will automatically reload if you change any of the source files.

Build

Run ng build to build the project. The build artifacts will be stored in the dist/ directory. Use the --prod flag for a production build.

Running unit tests

Run ng test to execute the unit tests via Karma.

Running end-to-end tests

Run ng e2e to execute the end-to-end tests via Protractor.

Further help

To get more help on the Angular CLI use ng help or go check out the Angular CLI Overview and Command Reference page.