Read up different papers and implement them.

[abhinavjain241]

Let's read up on papers describing multiple methods for similarity between tags and questions, and try to implement in a given fixed time frame, like 6-7 days, after which we can meet up, and discuss the different accuracies achieved using all the different methods, and then choose the best one.

People who should do this right now: Me, @pandeyadarsh @nishnik @arnavkj1995

[abhinavjain241]

For example, some methods are:

• LDA (Latent Dirichlet Allocation)
• WMD (Word Mover Distance)
• Naive Bayes Classification

[nishnik]

I am ready for WMD. I have read some papers on it.

On Mon, Mar 7, 2016 at 9:28 PM, Abhinav Jain notifications@github.com
wrote:

For example, some methods are:

• LDA (Latent Dirichlet Allocation)
• WMD (Word Mover Distance)
• Naive Bayes Classification

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Nishant Nikhil
Sophomore
Department of Mathematics
IIT Kharagpur
| Mobile: +91 9933979842 <%2B91%2099339798428>
| Email: nishantnikhil@iitkgp.ac.in
http://www.krssg.in/

[arnavkj1995]

@abhinav - You work on Naive Bayes Algorithm.

On Mon, Mar 7, 2016 at 9:45 PM, Nishant Nikhil notifications@github.com
wrote:

I am ready for WMD. I have read some papers on it.

On Mon, Mar 7, 2016 at 9:28 PM, Abhinav Jain notifications@github.com
wrote:

For example, some methods are:

• LDA (Latent Dirichlet Allocation)
• WMD (Word Mover Distance)
• Naive Bayes Classification

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#1 (comment)

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Nishant Nikhil
Sophomore
Department of Mathematics
IIT Kharagpur
| Mobile: +91 9933979842 <%2B91%2099339798428>
| Email: nishantnikhil@iitkgp.ac.in
http://www.krssg.in/

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