Advanced Literature's Table Access Information Retrieval engine This project implements a scientific paper search engine. The search engine is built using Apache Lucene, a high-performance, full-featured text search engine library. The REST backend is built using Spring Boot. The Python scripts are used for data processing tasks.
- Java Application: The main application logic is implemented in Java using Spring Boot. It can be accessed via the configured endpoints.
- Python Scripts: The Python scripts can be used for various data processing tasks.
To test the search engine, you can use the following URL: altair-search.web.app
- Install Maven: Make sure Maven is installed on your system.
- Build the Project: Navigate to the project directory and run:
cd search_engine mvn clean install - Run the Application: Use the following command to run the Spring Boot application:
mvn spring-boot:run
- Install pip: Ensure pip is installed on your system.
- Run Python Scripts: Execute the desired Python scripts using:
.data_preprocessing/run.sh
- Python: Used for scripting and data processing.
- pip: Python package installer used to manage dependencies.
- Java: Used for the main application logic.
- Spring Boot: Java framework used to create stand-alone, production-grade Spring-based applications.
- Maven: Build automation tool used for managing the Java project's dependencies and build lifecycle.
- Lucene: Used for indexing and searching the scientific papers.
src/main/java: Contains the Java source code.src/main/resources: Contains the resources for the Java application.src/test/java: Contains the Java test cases.python_scripts: Contains the Python scripts.pom.xml: Maven configuration file.requirements.txt: Python dependencies file.
- Fork the repository.
- Create a new branch (
git checkout -b feature-branch). - Commit your changes (
git commit -am 'Add new feature'). - Push to the branch (
git push origin feature-branch). - Create a new Pull Request.
This project is licensed under the MIT License.