Multimodal hybrid recommender systems combine diverse data types and user preferences to deliver more accurate recommendations.However, this approach may not fully capture user preferences. Additional feedback, like reviews and sentiments, can provide ...

Taking an interdisciplinary approach to surveying issues around gender bias in textual and visual AI, we present literature on gender bias detection and mitigation in NLP, CV, as well as combined visual-linguistic models. We identify conceptual parallels ...

In crowdsourced testing, prioritizing numerous test reports is critical for improving developer review efficiency. Many researchers have proposed methods for prioritizing crowdsourced test reports for mobile applications, however, web crowdsourced test ...

Background: Humor is a fundamental part of human communication, with prior work linking positive humor in the workplace to positive outcomes, such as improved performance and job satisfaction. Aims: This study aims to investigate programming-related ...

Abstractive text summarization is a task in natural language processing that automatically generates the summary from the source document in a human-written form with minimal loss of information. Research in text summarization has shifted towards ...

Social media include diverse interaction metrics related to user popularity, the most evident example being the number of user followers. The latter has raised concerns about the credibility of the posts by the most popular creators. However, ...

• There exists concern about the credibility of social media financial posts.
• We propose a credibility assessment solution combining ML and NLP.
• Creators’ reputation is verified with actual market data.
• The outcome of this ...

Mathematical formulas are commonly used to demonstrate theories and basic fundamentals in the Science, Technology, Engineering, and Mathematics (STEM) domain. The burgeoning research in the STEM domain results in the mass production of scientific ...

With the development of Deep Learning, Natural Language Processing (NLP) applications have reached or even exceeded human-level capabilities in certain tasks. Although NLP applications have shown good performance, they can still have bugs like traditional ...

This paper analyzes 88 million hacker forum posts of a publicly available dataset and 75,000 online articles over a 20-year timespan, studying the potential of hacker forums as a proactive Cyber Threat Intelligence (CTI) source. Using a custom Natural ...

Sentiment analysis is a process of dealing with people's opinions, remarks, and comments to extract valuable insights from them. Sentiment analysis can be used for various purposes like market analysis, campaign monitoring, decision-making, etc. In recent ...

User stories are informal, non-technical descriptions of features from a user's perspective that guide collaboration and iterative development in Agile projects. However, ambiguities in user stories can lead to miscommunication among stakeholders. Design ...

Understanding the modus operandi of adversaries aids organizations to employ efficient defensive strategies and share intelligence in the community. This knowledge is often present in unstructured natural language text within threat analysis reports. A ...

ESG reports contain crucial information about the corporations' environmental impact, social responsibilities, and governance. Many compliance audits rely on answering questions based on these reports. Moreover, for tasks such as Scope 3 GHG emissions ...

The proliferation of hate speech has intensified alongside advancements in internet technology, rendering the enhancement of hate speech detection accuracy. Traditional approaches have predominantly concentrated on augmenting pre-training and ...

Back-translation (BT) is an effective semi-supervised learning framework in neural machine translation (NMT). A pre-trained NMT model translates monolingual sentences and makes synthetic bilingual sentence pairs for the training of the other NMT ...

This study details the technical design and evaluation of a Multimodal Learning Analytics (MMLA) system designed to enhance spoken language acquisition in language café settings. Utilizing the MMLA Model for Design and Analysis (MAMDA) framework, ...

This paper presents the development and evaluation of a Vietnamese Large Language Model (LLM) specifically designed to solve elementary math problems, marking a significant step forward in the application of artificial intelligence in education ...

Establishing rapport between authors and readers of scientific texts is essential for supporting readers in understanding texts as intended, facilitating socio-discursive practices within disciplinary communities, and helping in identifying ...

The history-based content present on Wikipedia has been used for various NLP-related research. For large-scale analysis, efficient retrieval of past states of Wikipedia is a prerequisite. However, the lack of efficient tools for managing the massive ...

With the proliferation of informal content on various social media platforms in the form of posts, comments, and feedback, the importance of analyzing text in code-mixed form is gaining importance. Telugu, a low-resource Indian language, has a lot of ...