DE eng

Search in the Catalogues and Directories

Hits 1 – 15 of 15

1
Jibes & Delights: A Dataset of Targeted Insults and Compliments to Tackle Online Abuse​ ...
BASE
Show details
2
ViTA: Visual-Linguistic Translation by Aligning Object Tags ...
BASE
Show details
3
HASOCOne@FIRE-HASOC2020: Using BERT and Multilingual BERT models for Hate Speech Detection ...
Dowlagar, Suman; Mamidi, Radhika. - : arXiv, 2021
BASE
Show details
4
Multilingual Pre-Trained Transformers and Convolutional NN Classification Models for Technical Domain Identification ...
Dowlagar, Suman; Mamidi, Radhika. - : arXiv, 2021
BASE
Show details
5
Automatic Learning Assistant in Telugu ...
BASE
Show details
6
gundapusunil at SemEval-2020 Task 9: Syntactic Semantic LSTM Architecture for SENTIment Analysis of Code-MIXed Data ...
Gundapu, Sunil; Mamidi, Radhika. - : arXiv, 2020
BASE
Show details
7
A SentiWordNet Strategy for Curriculum Learning in Sentiment Analysis ...
BASE
Show details
8
Word Level Language Identification in English Telugu Code Mixed Data ...
Gundapu, Sunil; Mamidi, Radhika. - : arXiv, 2020
BASE
Show details
9
A Sentiwordnet Strategy for Curriculum Learning in Sentiment Analysis
In: Natural Language Processing and Information Systems (2020)
BASE
Show details
10
Conversational implicatures in English dialogue: Annotated dataset ...
BASE
Show details
11
BCSAT : A Benchmark Corpus for Sentiment Analysis in Telugu Using Word-level Annotations ...
Abstract: The presented work aims at generating a systematically annotated corpus that can support the enhancement of sentiment analysis tasks in Telugu using word-level sentiment annotations. From OntoSenseNet, we extracted 11,000 adjectives, 253 adverbs, 8483 verbs and sentiment annotation is being done by language experts. We discuss the methodology followed for the polarity annotations and validate the developed resource. This work aims at developing a benchmark corpus, as an extension to SentiWordNet, and baseline accuracy for a model where lexeme annotations are applied for sentiment predictions. The fundamental aim of this paper is to validate and study the possibility of utilizing machine learning algorithms, word-level sentiment annotations in the task of automated sentiment identification. Furthermore, accuracy is improved by annotating the bi-grams extracted from the target corpus. ... : Accepted as Long Paper at Student Research Workshop in 56th Annual Meeting of the Association for Computational Linguistics, ACL-2018 ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://arxiv.org/abs/1807.01679
https://dx.doi.org/10.48550/arxiv.1807.01679
BASE
Hide details
12
Automatic Target Recovery for Hindi-English Code Mixed Puns ...
BASE
Show details
13
Towards Automation of Sense-type Identification of Verbs in OntoSenseNet(Telugu) ...
BASE
Show details
14
Towards Enhancing Lexical Resource and Using Sense-annotations of OntoSenseNet for Sentiment Analysis ...
BASE
Show details
15
Context and Humor: Understanding Amul advertisements of India ...
Mamidi, Radhika. - : arXiv, 2018
BASE
Show details

Catalogues
0
0
0
0
0
0
0
Bibliographies
0
0
0
0
0
0
0
0
0
Linked Open Data catalogues
0
Online resources
0
0
0
0
Open access documents
15
0
0
0
0
© 2013 - 2024 Lin|gu|is|tik | Imprint | Privacy Policy | Datenschutzeinstellungen ändern