.png){kind=link}
.png){kind=link}
This project is about creating a text categorizer, giving a text it has to return the most consistent theme. To achieve this, the program is trained with text files from a giving topics dataset, and calculates the n-gram for each topic. Then, a jaccard distance is done between all n-grams generated from train dataset and the giving text file. The user can add some topics and text files on the datasets.
The main steps are interaction with user and the datasets, texts preprocessing, n-grams extraction and theme recognition with jaccard distance.
This program has been developed with Python programming language.
The folder contains:
- src folder containing the source files
- resources folder containing
- dataset folder of training topic with texts
- dataset folder of testing topic with texts
- file of stop words
Go into the root folder and launch this command if you want to train the program using dataset:
> python3 src/main.py -train
Or this command if you want to launch the topic recognition of a text file:
> python3 src/main.py -test
EPITA School, SCIA/MTI Master 1 - Project for Search Engine Optimisation Course.
Authors:
- BENSABAT David (bensab_d)
- LAMBERT Valentin (lamber_p)