From 0681c5b85c3fc1f782668b505d868c76a152c228 Mon Sep 17 00:00:00 2001 From: Ikenna Oluigbo <ikenna-victor.oluigbo@etu.univ-lyon1.fr> Date: Wed, 7 Dec 2022 03:36:40 +0000 Subject: [PATCH] Update README.md --- README.md | 31 +++++++++++++++---------------- 1 file changed, 15 insertions(+), 16 deletions(-) diff --git a/README.md b/README.md index a1f211f..7dbb45e 100644 --- a/README.md +++ b/README.md @@ -1,8 +1,6 @@ -# SemiSupervisedEmbeddingFramework +## SemiSupervisedEmbeddingFramework - - -## Getting started +# Getting Started To make it easy for you to get started with GitLab, here's a list of recommended next steps. @@ -44,18 +42,10 @@ Use the built-in continuous integration in GitLab. *** -# Editing this README - -When you're ready to make this README your own, just edit this file and use the handy template below (or feel free to structure it however you want - this is just a starting point!). Thank you to [makeareadme.com](https://www.makeareadme.com/) for this template. - -## Suggestions for a good README -Every project is different, so consider which of these sections apply to yours. The sections used in the template are suggestions for most open source projects. Also keep in mind that while a README can be too long and detailed, too long is better than too short. If you think your README is too long, consider utilizing another form of documentation rather than cutting out information. - -## Name -Choose a self-explaining name for your project. +# A Semi-supervised Node Embedding Framework for Attributed Networks ## Description -Let people know what your project can do specifically. Provide context and add a link to any reference visitors might be unfamiliar with. A list of Features or a Background subsection can also be added here. If there are alternatives to your project, this is a good place to list differentiating factors. +A scalable Framework for learning representation for network nodes, while preserving the neighborhood topology and node contextual attributes in the Learned Embedding. This method improves upon the random walk approach through a decision function, which learn quality vector representations useful for different downstream learning tasks. The probability walk builds a node corpus comprising sampled nodes with similar contextual attributes and structural patterns, which is trained using a NLP (natural language processing) technique. We evaluate the effectiveness of our model by comparing it with other baseline methods on three downstream tasks: Clustering, Link Prediction, and Node Classification. Our model shows better performance compared to these baselines. ## Badges On some READMEs, you may see small images that convey metadata, such as whether or not all the tests are passing for the project. You can use Shields to add some to your README. Many services also have instructions for adding a badge. @@ -63,8 +53,17 @@ On some READMEs, you may see small images that convey metadata, such as whether ## Visuals Depending on what you are making, it can be a good idea to include screenshots or even a video (you'll frequently see GIFs rather than actual videos). Tools like ttygif can help, but check out Asciinema for a more sophisticated method. -## Installation -Within a particular ecosystem, there may be a common way of installing things, such as using Yarn, NuGet, or Homebrew. However, consider the possibility that whoever is reading your README is a novice and would like more guidance. Listing specific steps helps remove ambiguity and gets people to using your project as quickly as possible. If it only runs in a specific context like a particular programming language version or operating system or has dependencies that have to be installed manually, also add a Requirements subsection. +## Installation +The codes are written in Python 3 environment. + +Use the package manager pip to install the necessary python libraries + +``` +pip install gensim +pip install numpy +pip install networkx +pip install tqdm +``` ## Usage Use examples liberally, and show the expected output if you can. It's helpful to have inline the smallest example of usage that you can demonstrate, while providing links to more sophisticated examples if they are too long to reasonably include in the README. -- GitLab