This document will provide details regarding the web application auto-summarizer, providing details on the application summary, details of files, terminology, as well as technical details regarding the development of the application.
auto-summarizer can be cloned using both HTTPS and SSH via git commands, it requires maven to successfully import the Stanford NLP parser to handle getting parts of speech of certain sentences.
To download and be able to make edits to the auto-summarizer project you will need to install git here.
This project is a Maven project so you should Maven installed. You can follow the directions to install maven at the following:
- Mac/OSX
- If Homebrew is installed, run
brew install mavenin your terminal - Windows
- Linux: from the terminal run
wget http://mirror.olnevhost.net/pub/apache/maven/binaries/apache-maven-3.2.1-bin.tar.gzto install maven.
Navigate in your terminal/command-prompt to the folder in which you would like to store the application.
In your terminal/command-prompt type in git clone https://github.com/jkys/auto-summarizer.git and press enter or return to start downloading all the files into the select folder.
Navigate in your terminal/command-prompt to the folder in which you would like to store the application.
In your terminal/command-prompt type in git clone git@github.com:jkys/auto-summarizer.git and press enter or return to start downloading all the files into the select folder.
The auto-summarizer application is a program entirely written in Java, which when given an article or block of text, it will attempt to condense that text to certain percentage of words to allow quicker reading while keeping the most amount of important details.
The processes and techniques used in the application are derived from a branch of artificial intelligence called natural language processing. The following topics were heavily used within the application term frequency/inverse document frequency and [part of speech tagging](part-of-speech tagging).
- Stanford NLP Library - For the NLP processor
- Java
- Jonathan Keys - Initial work/maintenance
- Colby Daly - Initial work
See also the list of contributors who participated in this project.
This project is licensed under the MIT License - see the LICENSE.md file for details
- A big thank you for the incredibly in depth and well documented Stanford NLP library as it was a tremendous help in learning natural language processing.