Search Results for author: Mohammed Hasanuzzaman

Found 17 papers, 2 papers with code

Detecting Violation of Human Rights via Social Media

no code implementations CSRNLP (LREC) 2022 Yash Pilankar, Rejwanul Haque, Mohammed Hasanuzzaman, Paul Stynes, Pramod Pathak

Social media is not just meant for entertainment, it provides platforms for sharing information, news, facts and events.

Relation

Identifying Complaints from Product Reviews: A Case Study on Hindi

1 code implementation ICON 2020 Raghvendra Pratap Singh, Rejwanul Haque, Mohammed Hasanuzzaman, Andy Way

Automatic recognition of customer complaints on products or services that they purchase can be crucial for the organisations, multinationals and online retailers since they can exploit this information to fulfil their customers’ expectations including managing and resolving the complaints.

Machine Translation NMT +1

Investigating the validity of structure learning algorithms in identifying risk factors for intervention in patients with diabetes

no code implementations21 Mar 2024 Sheresh Zahoor, Anthony C. Constantinou, Tim M Curtis, Mohammed Hasanuzzaman

Diabetes, a pervasive and enduring health challenge, imposes significant global implications on health, financial healthcare systems, and societal well-being.

Federated Split Learning with Only Positive Labels for resource-constrained IoT environment

no code implementations25 Jul 2023 Praveen Joshi, Chandra Thapa, Mohammed Hasanuzzaman, Ted Scully, Haithem Afli

Among various techniques in a DCML framework, federated split learning, known as splitfed learning (SFL), is the most suitable for efficient training and testing when devices have limited computational capabilities.

Enabling All In-Edge Deep Learning: A Literature Review

no code implementations7 Apr 2022 Praveen Joshi, Mohammed Hasanuzzaman, Chandra Thapa, Haithem Afli, Ted Scully

Secondly, this paper presents enabling technologies, such as model parallelism and split learning, which facilitate DL training and deployment at edge servers.

Edge-computing Model Compression +3

Multimodal Neural Machine Translation for Low-resource Language Pairs using Synthetic Data

no code implementations WS 2018 Koel Dutta Chowdhury, Mohammed Hasanuzzaman, Qun Liu

In this paper, we investigate the effectiveness of training a multimodal neural machine translation (MNMT) system with image features for a low-resource language pair, Hindi and English, using synthetic data.

Machine Translation Question Answering +3

Fine-Grained Temporal Orientation and its Relationship with Psycho-Demographic Correlates

no code implementations NAACL 2018 Sabyasachi Kamila, Mohammed Hasanuzzaman, Asif Ekbal, Pushpak Bhattacharyya, Andy Way

In this paper, we propose a very first study to demonstrate the association between the sentiment view of the temporal orientation of the users and their different psycho-demographic attributes by analyzing their tweets.

Decision Making

ADAPT at IJCNLP-2017 Task 4: A Multinomial Naive Bayes Classification Approach for Customer Feedback Analysis task

no code implementations IJCNLP 2017 Pintu Lohar, Koel Dutta Chowdhury, Haithem Afli, Mohammed Hasanuzzaman, Andy Way

In this paper, we analyse the real world samples of customer feedback from Microsoft Office customers in four languages, i. e., English, French, Spanish and Japanese and conclude a five-plus-one-classes categorisation (comment, request, bug, complaint, meaningless and undetermined) for meaning classification.

Classification General Classification +3

Demographic Word Embeddings for Racism Detection on Twitter

no code implementations IJCNLP 2017 Mohammed Hasanuzzaman, Ga{\"e}l Dias, Andy Way

Most social media platforms grant users freedom of speech by allowing them to freely express their thoughts, beliefs, and opinions.

Classification General Classification +1

Temporal Orientation of Tweets for Predicting Income of Users

no code implementations ACL 2017 Mohammed Hasanuzzaman, Sabyasachi Kamila, M Kaur, eep, Sriparna Saha, Asif Ekbal

Automatically estimating a user{'}s socio-economic profile from their language use in social media can significantly help social science research and various downstream applications ranging from business to politics.

regression TAG +1

Building Tempo-HindiWordNet: A resource for effective temporal information access in Hindi

no code implementations LREC 2016 Dipawesh Pawar, Mohammed Hasanuzzaman, Asif Ekbal

In this paper, we put forward a strategy that supplements Hindi WordNet entries with information on the temporality of its word senses.

General Classification

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