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https://github.com/shrebox/Personified-Chatbot

A personified chatbot responding to a query based on the answering pattern of Dr. APJ Abdul Kalam using Information Retrieval, Natural Language Processing, and Deep Learning techniques.
https://github.com/shrebox/Personified-Chatbot

apj-abdul-kalam chatbot deep-learning information-retrieval lstm natural-language-processing nlp ranking-algorithm seq2seq-chatbot seq2seq-model summarization word2vec

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A personified chatbot responding to a query based on the answering pattern of Dr. APJ Abdul Kalam using Information Retrieval, Natural Language Processing, and Deep Learning techniques.

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README 

        
[![DOI](https://zenodo.org/badge/DOI/10.13140/RG.2.2.28964.09602.svg)](https://www.researchgate.net/deref/http%3A%2F%2Fdx.doi.org%2F10.13140%2FRG.2.2.28964.09602?_sg%5B0%5D=ApGORUVG1cBpNrnt9rvmz-ph0V9Q1S-B0MNYPCFbHB_CIqf9M4-2aqvNXMKavH-5plON5qiVr3nw4ots-C1J88exnw.ieGbmNeyS6_ywMiraavaTI9s-uUHq6x6S6AXlePwTKqf6VCcbbdeh5nirtz6xeJVCu7udFxrw7bJ-b3HqXMQbA)



![alt text](https://github.com/shrebox/Personified-Chatbot-I-am-Kalam/blob/master/Poster-1.jpg)



If you end up using this code or the data, please cite our paper:

```

@unknown{unknown,

author = {Arya, Shreyash and Uberoi, Anannya and Dhawan, Sarthika and Chakraborty, Tanmoy},

year = {2019},

month = {02},

pages = {},

title = {“I am Kalam” - Analyzing and Generating Kalam's Answer Patterns},

doi = {10.13140/RG.2.2.28964.09602}

}



```

Cite work [here](https://www.researchgate.net/publication/343963547_I_am_Kalam_-_Analyzing_and_Generating_Kalam's_Answer_Patterns)!



# *'I am Kalam'* - Reliving Kalam’s Words



:bulb: The work was presented at the [_Workshop on AI for Computational Social Systems (ACSS 2019), IIIT-Delhi_](http://lcs2.iiitd.edu.in/acss19/).



Analyzing answer pattern of APJ Abdul Kalam and responding to a query following his answering pattern. We are applying RNNs to generate answers to user queries. 



> **Dataset**: Dataset has been scrapped from interviews available on various websites form the google search results.


> **Files**: dataset/ directory containes different extracted data forms.


> **Code**: code/ directory contains codes from IR-IE model, seq2seq model, preprocessing and evaluation.



IR-IE model
 



	$ python sen2vec_my.py



	** sent2vec library needs to be installed from https://github.com/epfml/sent2vec.


	** pre trained model torontobooks_unigrams.bin need to be downloaded and kept in same directory.



seq2seq model
 



	$ python main.py 

	

	to train the system and save the model named as model.npz.


	Set inference_mode=1 for testing purpose and run python main.py.



## References

- https://github.com/facebookarchive/NAMAS 


- https://github.com/zwc12/Summarization 


- https://datascience.stackexchange.com/questions/23969/sentence-similarity-prediction 


- https://rare-technologies.com/doc2vec-tutorial/ 


- http://nlp.town/blog/sentence-similarity/ 


- https://radimrehurek.com/gensim/models/keyedvectors.html 


- https://machinelearningmastery.com/develop-word-embeddings-python-gensim/ 


- https://github.com/epfml/sent2vec 


- https://pdfs.semanticscholar.org/ffbb/1d120c3c2881431933c6f928b851824913c4.pdf?_ga=2.35884901.416918627.1538253292-1431390683.1533485502


- https://arxiv.org/pdf/1603.06155.pdf 


- https://people.cs.umass.edu/~ashutoshchou/persona_chatbot_report.pdf 


- https://github.com/ashutosh-choudhary/conversational_agent_personified


- https://towardsdatascience.com/personality-for-your-chatbot-with-recurrent-neural-networks-2038f7f34636


- https://github.com/manumathewthomas/Chat-with-Joey


- https://github.com/inikdom/neural-chatbot


- https://github.com/tensorlayer/seq2seq-chatbot 


- https://github.com/epfml/sent2vec 


- http://adventuresinmachinelearning.com/keras-lstm-tutorial/






Tada! (:) :v::alien: