Praboda Rajapaksha

• PhD in Computer Science
• Research Fellow at Institut Polytechnique de Paris

Visual Polysemy Disambiguation (VPD) and Visual Word Sense Disambiguation (VWSD) are challenging tasks for both computer vision and NLP since an image can have diverse contextual interpretations, ranging from visual representations to abstract concepts. In this paper, we propose a novel approach to address the challenges of VPD and VWSD by leveragi...

Pruning, as a technique to reduce the complexity and size of Transformer-based models, has gained significant attention in recent years. While various models have been successfully pruned, pruning BERT poses unique challenges due to their fine-grained structure and overparameterization. However, by carefully considering these factors, it is possibl...

Detecting the underlying human values within arguments is essential across various domains, ranging from social sciences to recent computational approaches. Identifying these values remains a significant challenge due to their vast numbers and implicit usage in discourse. This study explores the potential of emotion analysis as a key feature in imp...

Traffic flow prediction is an important feature for smart cities, as it helps in implementing effective traffic policies. However, accurate prediction and successful traffic management rely on reliable traffic information, which may not always be available due to the deployment and management costs of a specialized traffic intensity sensor infrastr...

The prevalence of offensive content on online communication and social media platforms is growing more and more common, which makes its detection difficult, especially in multilingual settings. The term “Offensive Language” encompasses a wide range of expressions, including various forms of hate speech and aggressive content. Therefore, exploring m...

Clustering incomplete multiview data in real-world applications has become a topic of recent interest. However, producing clustering results from multiview data with missing views and different degrees of missing data points is a challenging task. To address this issue, we propose a co-clustering method for incomplete multiview data by sparse low-r...

The conventional approaches for traffic intensity (TI) detection in Smart Cities use specialized sensors such as loop detectors, cameras, and radar. These sensors come with high costs, limited reuse, and specialized maintenance. Thus, we propose the utilization of general-purpose sensing, which involves the use of cost-effective and easily deployab...

Sexism detection remains as an extremely low-resource task for most of the languages including Chinese. To address this issue, we propose a zero-shot cross-lingual method to detect sexist speech in Chinese and perform qualitative and quantitative analyses on the data we employed. The proposed method aims to explicitly model the knowledge transfer p...

The Internet of Things (IoT) consists of a myriad of smart devices and offers tremendous innovation opportunities in industry, homes, and businesses to enhance the productivity and the quality of life. However, ecosystem of infrastructures and the services associated with IoT devices have introduced a new set of vulnerabilities and threats, resulti...

Background: Video anomaly detection has always been a hot topic and attracting an increasing amount of attention. Much of the existing methods on video anomaly detection depend on processing the entire video rather than considering only the significant context. This paper proposes a novel video anomaly detection method named COVAD, which mainly foc...

Recent years brought an exponential growth of social media which revolutionized freedom of speech but significantly increased the propagation of hate speech and hate-based activities. Therefore, constructive countermeasures are necessary to prevent escalating hateful content on online social media. Many recent works target explicit hate speech, but...

With the freedom of communication provided in online social media, hate speech has increasingly generated. This leads to cyber conflicts affecting social life at the individual and national levels. As a result, hateful content classification is becoming increasingly demanded for filtering hate content before being sent to the social networks. This...

Clickbait can be a spam or an advert which more often provides a link to a commercial website, or it might be a headline to a news media website which makes money from page views by providing eye-catchy headlines with deceptive news. This paper focuses on the latter one to identify clickbaits that use news headlines to publish news items in Twitter...

Internet users are likely to be victims to clickbait assuming as legitimate news. The notoriety of clickbait can be partially attributed to misinformation as clickbait use an attractive headline that is deceptive, misleading or sensationalized. A major type of clickbait are in the form of spam and advertisements that are used to redirect users to w...

Social networking sites (SNSs) facilitate the sharing of ideas and information through different types of feedback including publishing posts, leaving comments and other type of reactions. However, some comments or feedback on SNSs are inconsiderate and offensive, and sometimes this type of feedback has a very negative effect on a target user. The...

Social networking sites (SNSs) facilitate the sharing of ideas and information through different types of feedback including publishing posts, leaving comments and other type of reactions. However, some comments or feedback on SNSs are inconsiderate and offensive, and sometimes this type of feedback has a very negative effect on a target user. The...

Online piracy is an important challenge in the motion-pictures industry. Several studies claimed that unauthorized content in online venues are reducing substantially the BoxOffice revenues while few other studies were not in favor of this claim. To understand better the impact of this phenomena, a study based on a large dataset is needed to analys...

In recent times, news medias avail oneself of online social media platforms for news promotion, sharing and commentary to a large extent mainly in Twitter, Facebook, and Reddit. Therefore, in the literature, researchers have been used machine learning and text mining techniques to attain useful insights from the news media data in social media in-o...

The rising popularity of social media has radically changed the way news content is propagated, including interactive attempts with new dimensions. To date, traditional news media such as newspapers, television and radio have already adapted their activities to the online news media by utilizing social media, blogs, websites etc. This paper provide...

Available big data have proliferated rapidly in the last decade and continue to grow in popularity. The existing new data sources such as Online Social Networks (OSNs) and Internet of Things (IoT) influence many digital aspects in-order to shape/reshape normal life of people and other related parties such as businesses, stockholders etc. Urban mobi...