I need a solution for keyword clustering. The task must be done with Python/Jupyter Notebook.
Here's the original dataframe (see the attached pdf):
-there's hundreds of keywords.
-each keyword has a list of 10 urls associated with them
The ultimate goal is to aggregate keywords by similarity.
The following tasks need to be done:
1. Compare every list to all the other lists (example: Keyword#1 has 4 urls in common with Keyword#57)
2. Create a table for each keyword containing the all the other keywords and their level of similarity
3. Find a way to regroup keywords (using the method/python library of your choice), avoiding too much overlapping between groups (since keywords can belong to several clusters). Based on the similarity of the lists of urls (not lemmas)
4. Create a table for each cluster containing all the related keywords
The final result should be available through a Jupyter Notebook.
Each step should be documented.
23 freelancere byder i gennemsnit €134 på dette job
Hello I have read your project description and am very interested in your project. I have experienced in developing Python and Jupyter/NoteBook I will work very hard and best for you. Best Regards
Hello! This project is very funny and very fit to me. I'm interested in algorithm and optimization. I'm good at python programming; can use several python packages for data analysis. Thanks.
Hello! I am a python developer. I looked at your project and it seems interesting. I have all necessary skills required for this project. Ping me to discuss in detail.
Hi,i'm a data scientist with a BS degree in computer science i will do your task as fast as i can and i will achieve it exactly as you want,don't worry about any thing contact me for discussion
I am a student studying Data science and I have worked on quite a few projects in data science in jupyter notebook. I have good energy and time to do this.