Temporal Question Generation from History Text

no code implementations • ICON 2021 • Harsimran Bedi, Sangameshwar Patil, Girish Palshikar

Temporal analysis of history text has always held special significance to students, historians and the Social Sciences community in general.

Question Generation Question-Generation

Extraction of Message Sequence Charts from Narrative History Text

no code implementations • WS 2019 • Girish Palshikar, Sachin Pawar, Sangameshwar Patil, Swapnil Hingmire, Nitin Ramrakhiyani, Harsimran Bedi, Pushpak Bhattacharyya, Vasudeva Varma

In this paper, we advocate the use of Message Sequence Chart (MSC) as a knowledge representation to capture and visualize multi-actor interactions and their temporal ordering.

Dependency Parsing

IITP at IJCNLP-2017 Task 4: Auto Analysis of Customer Feedback using CNN and GRU Network

no code implementations • IJCNLP 2017 • Deepak Gupta, Pabitra Lenka, Harsimran Bedi, Asif Ekbal, Pushpak Bhattacharyya

Our empirical analysis shows that our models perform well in all the four languages on the setups of IJCNLP Shared Task on Customer Feedback Analysis.

Document Classification Emotion Classification +2

Event Timeline Generation from History Textbooks

no code implementations • WS 2017 • Harsimran Bedi, Sangameshwar Patil, Swapnil Hingmire, Girish Palshikar

Event timeline serves as the basic structure of history, and it is used as a disposition of key phenomena in studying history as a subject in secondary school.

Auto Analysis of Customer Feedback using CNN and GRU Network

1 code implementation • 12 Oct 2017 • Deepak Gupta, Pabitra Lenka, Harsimran Bedi, Asif Ekbal, Pushpak Bhattacharyya

Analyzing customer feedback is the best way to channelize the data into new marketing strategies that benefit entrepreneurs as well as customers.

Marketing