The number of applications in Google Play has increased dramatically in recent years. On Google Play, users can write detailed reviews and rate apps, with these ratings significantly influencing app success and download numbers. Reviews often include notable information like feature requests, which are valuable for software maintenance. Users can update their reviews and ratings anytime. Studies indicate that apps with ratings below three stars are typically avoided by potential users. Since 2013, Google Play has allowed developers to respond to user reviews, helping resolve issues and potentially boosting overall ratings and download rates. However, responding to reviews is time-consuming, and only 13% to 18% of developers engage in this practice. To address this challenge, we propose a method to prioritize reviews based on response priority. We collected and preprocessed review data, extracted both textual and semantic features, and assessed their impact on the importance of responses. We labelled reviews as requiring a response or not and trained four different machine learning models to prioritize them. We evaluated the models performance using metrics such as F1-Score, Accuracy, Precision, and Recall. Our findings indicate that the XGBoost model is the most effective for prioritizing reviews needing a response.

The rapid advancement of Extended Reality (XR, encompassing AR, MR, and VR) and spatial computing technologies forms a foundational layer for the emerging Metaverse, enabling innovative applications across healthcare, education, manufacturing, and entertainment. However, research in this area is often limited by the lack of large, representative, and highquality application datasets that can support empirical studies and the development of new approaches benefiting XR software processes. In this paper, we introduce XRZoo, a comprehensive and curated dataset of XR applications designed to bridge this gap. XRZoo contains 12,528 free XR applications, spanning nine app stores, across all XR techniques (i.e., AR, MR, and VR) and use cases, with detailed metadata on key aspects such as application descriptions, application categories, release dates, user review numbers, and hardware specifications, etc. By making XRZoo publicly available, we aim to foster reproducible XR software engineering and security research, enable cross-disciplinary investigations, and also support the development of advanced XR systems by providing examples to developers. Our dataset serves as a valuable resource for researchers and practitioners interested in improving the scalability, usability, and effectiveness of XR applications. XRZoo will be released and actively maintained.

In this paper, we explore the challenges of ensuring security and privacy for users from diverse demographic backgrounds. We propose a threat modeling approach to identify potential risks and countermeasures for product inclusion in security and privacy. We discuss various factors that can affect a user's ability to achieve a high level of security and privacy, including low-income demographics, poor connectivity, shared device usage, ML fairness, etc. We present results from a global security and privacy user experience survey and discuss the implications for product developers. Our work highlights the need for a more inclusive approach to security and privacy and provides a framework for researchers and practitioners to consider when designing products and services for a diverse range of users.

Intelligent virtual assistants are currently designed to perform tasks or services explicitly mentioned by users, so multiple related domains or tasks need to be performed one by one through a long conversation with many explicit intents. Instead, human assistants are capable of reasoning (multiple) implicit intents based on user utterances via commonsense knowledge, reducing complex interactions and improving practicality. Therefore, this paper proposes a framework of multi-domain dialogue systems, which can automatically infer implicit intents based on user utterances and then perform zero-shot prompting using a large pre-trained language model to trigger suitable single task-oriented bots. The proposed framework is demonstrated effective to realize implicit intents and recommend associated bots in a zero-shot manner.

Any major trend or world event, from the coronavirus pandemic to the cryptocurrency frenzy, will quickly be used as fodder in digital phishing attacks and other online scams. In recent months, it has become clear that the same would happen for large language models and generative AI. Today, researchers from the security firm Sophos are warning that the latest incarnation of this is showing up in Google Play and Apple's App Store, where scammy apps are pretending to offer access to OpenAI's chatbot service ChatGPT through free trials that eventually start charging subscription fees. There are paid versions of OpenAI's GPT and ChatGPT for regular users and developers, but anyone can try the AI chatbot for free on the company's website. The scam apps take advantage of people who have heard about this new technology--and perhaps the frenzy of people clamoring to use it--but don't have much additional context for how to try it themselves.

Use your smartphone to record yourself for 30 seconds, our artificial intelligence-powered referee reads your movements and scores your performance. The better you move, the more you'll win. Challenge yourself, your friends or famous athletes in freestyle football or dance and earn prizes playing the sports you love.

Spotlyf is an AI-powered social media platform that works on content authenticity & appreciates its user to share valuable posts. Spotlyf acknowledge the true power of Social Media by embracing authentic, original & genuine content. SpotLyf welcomes everyone to create a positive social impact on each other lives for their Digital well-being. We aim to connect valued lives across the globe. With its advanced core A.I. Technology SpotLyf helps you to discover meaningful content & pull out misleading social activities.

With Cere, you can chat about anything and everything under the sun, and get instant, personalized responses tailored to your unique needs and preferences. Our chatbot is powered by advanced natural language processing (NLP) technology, allowing it to understand your queries and provide accurate, helpful answers. We live in a world where information is at our fingertips. However, we often struggle to keep up with the pace of technological advancements and the sheer volume of data available to us. That's where Cere comes in!

Artificial Intelligence - AI Are you looking for an Artificial Intelligence manual or an Artificial Intelligence tutorial? You have come to the right place. This app is designed to give everyone a basic understanding of Artificial Intelligence (AI). It will provide an overview of the different types of AI, how it is used in various industries, and the ethical considerations involved. After reviewing this app, viewers will gain a better understanding of AI, its capabilities and how it can be applied in their organizations.

Replika is a #1 chatbot companion powered by artificial intelligence. Replika is for anyone who wants a friend with no judgment, drama, or social anxiety involved. You can form an actual emotional connection, share a laugh, or get real with an AI that's so good it almost seems human. Replika is an AI friend that is just as unique as you are. No two Replikas are exactly alike.