The large and growing amount of digital data creates a pressing need for approaches capable of indexing and retrieving multimedia content. A traditional and fundamental challenge consists of effectively and efficiently performing nearest-neighbor ...

Ranking systems are instrumental in shaping user experiences by determining the relevance and order of presented items. However, current approaches, particularly those revolving around user-centric reputation scoring, raise ethical concerns associated ...

Effective meetings are effortful, but traditional videoconferencing systems offer little support for reducing this effort across the meeting lifecycle. Generative AI (GenAI) has the potential to radically redefine meetings by augmenting intentional ...

Generative Artificial Intelligence empowered conversational agents (chatbots) seem to be increasingly used in various settings including education. While student teachers are key stakeholders in supporting and improving education, not many studies ...

Hybridge is an experimental system for exploring the design of remote inclusion for hybrid meetings. In-room users see remote participants on individual displays positioned around a table, and remotes see video feeds from the room integrated into a ...

Current online meeting technologies lack holistic support for reducing the effort of planning and running meetings. We present CoExplorer2D and CoExplorerVR, generative AI (GenAI)-driven technology probes for exploring the significant transformative ...

Responsible design of AI systems is a shared goal across HCI and AI communities. Responsible AI (RAI) tools have been developed to support practitioners to identify, assess, and mitigate ethical issues during AI development. These tools take many forms (...

Sparse representation learning based on Pre-trained Language Models has seen a growing interest in Information Retrieval. Such approaches can take advantage of the proven efficiency of inverted indexes and inherit desirable IR priors such as explicit ...

Recent studies have demonstrated that finely tuned deep neural networks (DNNs) are susceptible to adversarial attacks. Conventional physical attacks employ stickers as perturbations, achieving robust adversarial effects but compromising ...

In view of the invisibility and robustness of the existing physical attacks, the authors propose the adversarial catoptric light, which uses genetic algorithm to optimise the physical parameters of the catoptric light to perform black‐box physical ...

Tobin's q has been interpreted as a forward looking indicator of firm performance. In this paper, we use it as a lead indicator in period t to find out its effect on firm performance in period t + 2. The conceptual framework used in the paper has Tobin's ...

The goal of organizational security awareness programs is to positively influence employee security behaviors. However, organizations may struggle to determine program effectiveness, often relying on training policy compliance metrics (e.g., ...

Blockchain has attracted more and more attention of academia, industry, and government in recent decades. Different usage demands have inspired various blockchain designs, forming different blockchain systems, which leads to information islands. Many ...

To solve the problems of low information collection accuracy, recall and evaluation accuracy in traditional methods, an evaluation method of online learning effectiveness for college students based on social network data mining is proposed. A web crawler ...

In order to mine the user's preference and interest from the user's historical behaviour in the big data to make a personalised recommendation, a DRR model is constructed based on deep reinforcement learning, and the performance of the DRR model is ...

This research integrates online learning supported by students' smart phones and a tutoring system CSIEC into a university course of English as a foreign language, through one semester with 548 students and eight lecturers from 13 classes. The treatment ...

The aim of this assessment is to assess the effectiveness of the digital development of commercial banks in Uzbekistan. To accomplish the aim of this assessment, identifying the highest ranked banks in the effectiveness of digital development in ...

This study aims to identify whether using vocabulary.com as Computer Assisted Language Learning (CALL) is proven to be effective in terms of vocabulary acquisition and to what extent the increment of their vocabulary acquisition in a classroom setting. ...

Industrial search and recommendation systems mostly follow the classic multi-stage information retrieval paradigm: matching, pre-ranking, ranking, and re-ranking stages. To account for system efficiency, simple vector-product based models are commonly ...

Many recent Natural Language Processing (NLP) task formulations, such as question answering and fact verification, are implemented as a two-stage cascading architecture. In the first stage an IR system retrieves "relevant'' documents containing the ...

Building on contingency theory and the input–process–output model, this paper investigates the relationships between customer relationship management (CRM) technology adoption, customization capability, CRM effectiveness, and strategic alignment. By ...