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cppl

csvediting

dice-website

Knowledge-graph driven website of the DICE research group

fkg-mini-project

Machine Learning (ML) algorithms need data in the form of feature vectors and class labels to come up with a trained model and predict new instances with that trained model. Data stored in Knowledge Graph(s) (KG) is in the form of triples. To apply ML algorithms on KG, we need to convert the individuals in the learning problem into feature vectors. One way to tackle this task is to use KG embedding.

fkg-mini-project-refinement

As often done in node classification on knowledge graphs we use the positive and negative examples to learn concepts in description logics using refinement operators. This way the classifications should not only be accurate but also explainable by looking at the concept, at least for domain experts depending on the ontology.

iitbapp

Django quasi-RESTful API for InstiApp!

instiapp

Android App for Indian Institute of Technology, Bombay

multi-dueling-bandits

seminar-1

sigir20-extractive-snippet-generation-for-arguments

snowden

SNLP

snowden2.0

This repository is for the collaboration of CA Group assignment work.

turtle-project

Just a visual script in Python

vdr

A virtual Dressing Room (VDR)

venter-local-executable