Facebook-Post-Aggression-Identification

The workshop includes a shared task on ‘Aggression Identification’. The task will be to develop a classifier that could make a 3-way classification in between ‘Overtly Aggressive’, ‘Covertly Aggressive’ and ‘Non-aggressive’ text data.

author-profiling-pan-clef-2018

Author Profiling: Gender Identification in Twitter

Sentinel-2-Image-Scene-Classification-A-Comparison-between-Sen2Cor-and-a-Machine-Learning-Approach

Single-Multilingual-Hate-Speech-Detection-Model

This model was create as a part of SemEval-2019 Task 5 competition.

Automated-Event-Extraction-Model-for-Multiple-Linked-Portuguese-Documents

In recent time, machine learning is booming and researchers are trying to use its application where ever possible. Such street of the domain is legal documents. Here, this paper talks about event extraction from police legal documents. These extracted events are manually verified with linguist and it is able to obtain 95.93\% accuracy. Further, with help of ontological structure, these events are mapped as a knowledge graph. The ontology represents the name entity and events associated with each document. Through SPARQL query, this knowledge base is accessible and with such representation, this helps in accessing the legal document in form of question-answer, making easier in accessing the information.