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Gaining insights from Question/Answering systems using Graph Algorithms

Hi everybody
this project is about applying Neo4j graph algorithms (or the GDS library) to gain insights from question / answering systems such as StackExchange (SE). Examples of insights include (but are not limited to ) ranking users (using PageRank algorithm), personalised ranking of users, (using PPR) and community detection.
The project is at its beginning: we have already imported data from SE Network about users and their interactions as CSV files. We have already modelled a first type of user interaction as (user) -[:comments] -> (user) in Neo4j graph and we are currently working on modelling other user interactions (votes, answers)...

Our project can be applied to any SE sub-network such as StackOverflow, AskUbuntu, etc. since all the sub-networks share the same database schema.

We hope the discovered knowledge will help enhance user interactions in Q/A systems, for instance by recommending posts according to user profiles, unveiling existing communities, etc.

We will create a related GitHub project soon.

5 REPLIES 5

sameerG
Graph Buddy

Hi Douikifli
Is above mentioned project ready.Can I install it for preview?

Hi Sameer,

sorry for my late reply. We have just completed the project. I'll post details about the application we developed and the way to use it.

Regards,

Doulkifli

Hi Doulkifli

Do you have the GitHub url so that I can review it and see if it generates any useful insights
Regards
Sameer

Hi Sameer,

Sorry for my late reply. We completed the project a couple of months ago. Indeed, I have a GitHub url but I have to add the projects files. Once added, I'll inform you.

Regards,

Doulkifli

Hi Sameer, I've just added the project files in my GitHub Space. You can access it here

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