Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Sandip Modha"'
Publikováno v:
Proceedings of the 14th Annual Meeting of the Forum for Information Retrieval Evaluation.
Autor:
Shrey Satapara, Prasenjit Majumder, Thomas Mandl, Sandip Modha, Hiren Madhu, Tharindu Ranasinghe, Marcos Zampieri, Kai North, Damith Premasiri
Publikováno v:
Proceedings of the 14th Annual Meeting of the Forum for Information Retrieval Evaluation.
Publikováno v:
Journal of Experimental & Theoretical Artificial Intelligence. 34:499-525
Modeling text in a numerical representation is a prime task for any Natural Language Processing downstream task such as text classification. This paper attempts to study the effectiveness of text r...
Publikováno v:
Expert Systems with Applications. 215:119342
Autor:
Sandip Modha, Thomas Mandl, Gautam Kishore Shahi, Hiren Madhu, Shrey Satapara, Tharindu Ranasinghe, Marcos Zampieri
Publikováno v:
Forum for Information Retrieval Evaluation.
Publikováno v:
Social Network Analysis and Mining. 11
A daily summary or digest from microblogs allows social media users to stay up to date on what happened today on their favorite topic. Summarizing microblogs is a non-trivial task. This paper presents a summarization system built over the Twitter str
Publikováno v:
FIRE
This paper presents the HASOC track and its two parts. HASOC is dedicated to evaluate technology for finding Offensive Language and Hate Speech. HASOC is creating test collections for languages with few resources and English for comparison. The first
Publikováno v:
SN Computer Science. 1
This paper presents online hate speech as a societal and computational challenge. Offensive content detection in social media is considered as a multilingual, multi-level, multi-class classification problem for three Indo-European languages. This res
Autor:
Mohana Dave, Chintak Mandlia, Aditya Patel, Thomas Mandl, Daksh Patel, Prasenjit Majumder, Sandip Modha
Publikováno v:
FIRE (Working Notes)
The identification of Hate Speech in Social Media is of great importance and receives much attention in the text classification community. There is a huge demand for research for languages other than English. The HASOC track intends to stimulate deve
Publikováno v:
SemEval@NAACL-HLT
This paper presents the participation of team DA-LD-Hildesheim of Information Retrieval and Language Processing lab at DA-IICT, India in Semeval-19 OffenEval track. The aim of this shared task is to identify offensive content at fined-grained level g