The goal of this project is to offer a basic set of tools to build and evaluate ranking algorithms. In order to achieve this we have implemented:
- A superclass named ranker, which includes some basic utilities to provide a quickstart for the development of new techniques.
- A top-k retrieval function to retrieve the top-k reated nodes of the network based on a min-hip for high efficiency.
- An implementation of the Jaccard Similarity Coefficient computation, which exploits the use of unordered sets for high efficiency.
- A multithreading library, which allows to parallelize the main (like we did) and also any possible ranker.
- A CSR matrix representation, to allow an efficient handling of the network matrices, also improved through the usage of buffers.
Also, 3 ranking algorithms are already implemented: Power-Method based PageRank, Power-Method based HITS, and InDegree.
In order to run this project a c++ compiler and make are required.
To run the project using the make utility, the user needs to move in the directory containing the .hpp and .cpp files, and using the following commands:
make # To compile the project.
make exec # To run the compiled project.
make clean # To clean previous compiled versions of the project.Can be easily expanded, and offers also a multithreading library for an easier handling of thread pools. The implemented barrier might need some further tweaks in order to be used inside of ranking algorithms (in order to avoid any deadlock).
git clone https://github.com/jgurakuqi/ranker-comparatorMIT License
Copyright (c) 2023 Jurgen Gurakuqi, Elsa Sejdi
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