The explosion of social media allowed individuals to spread information without cost, with little investigation and fewer filters than before. This amplified the old problem fake news, which became a major concern nowadays due negative impact it brings communities. In order tackle rise spreading automatic detection techniques have been researched building on artificial intelligence machine learning. recent achievements deep learning in complex natural language processing tasks, make them...

Recommender systems have significantly developed in recent years parallel with the witnessed advancements both internet of things (IoT) and artificial intelligence (AI) technologies. Accordingly, as a consequence IoT AI, multiple forms data are incorporated these systems, e.g. social, implicit, local personal information, which can help improving recommender systems' performance widen their applicability to traverse different disciplines. On other side, energy efficiency building sector is...

After different consecutive waves, the pandemic phase of Coronavirus disease 2019 does not look to be ending soon for most countries across world. To slow spread COVID-19 virus, several measures have been adopted since start outbreak, including wearing face masks and maintaining social distancing. Ensuring safety in public areas smart cities requires modern technologies, such as deep learning transfer learning, computer vision automatic mask detection accurate control whether people wear...

The computation of relatedness between two fragments text in an automated manner requires taking into account a wide range factors pertaining to the meaning convey, and pairwise relations their words. Without doubt, measure segments must take both lexical semantic Such that captures well aspects may help many tasks, such as retrieval, classification clustering. In this paper we present new approach for measuring words based on implicit links. exploits only word thesaurus order devise links...

Social network analysis has recently gained a lot of interest because the advent and increasing popularity social media, such as blogs, networking applications, microblogging, or customer review sites. In this environment, trust is becoming an essential quality among user interactions recommendation for useful content trustful users crucial all members network. paper, we introduce framework handling in networks, which based on reputation mechanism that captures implicit explicit connections...

Recommender systems have been widely used in different application domains including energy-preservation, e-commerce, healthcare, social media, etc. Such applications require the analysis and mining of massive amounts various types user data, demographics, preferences, interactions, order to develop accurate precise recommender systems. datasets often include sensitive information, yet most are focusing on models' accuracy ignore issues related security users' privacy. Despite efforts...

The recent advances in artificial intelligence namely machine learning and deep learning, have boosted the performance of intelligent systems several ways. This gave rise to human expectations, but also created need for a deeper understanding how think decide. concept explainability appeared, extent explaining internal system mechanics terms. Recommendation are that support decision making, as such, they be explainable order increase user trust improve acceptance recommendations. In this...

Recommender systems are a key technology for many applications, such as e-commerce, streaming media, and social media. Traditional recommender rely on collaborative filtering or content-based to make recommendations. However, these approaches have limitations, the cold start data sparsity problem. This survey paper presents an in-depth analysis of paradigm shift from conventional generative pre-trained-transformers-(GPT)-based chatbots. We highlight recent developments that leverage power...

Web personalization is the process of customizing a site to needs each specific user or set users, taking advantage knowledge acquired through analysis user's navigational behavior. Integrating usage data with content, structure profile enhances results process. In this paper, we present SEWeP, system that makes use both logs and semantics site's content in order personalize it. semantically annotated using conceptual hierarchy (taxonomy). We introduce C-logs, an extended form encapsulates...

Among the large number of efforts that study role technology in energy saving, there exists, first, frameworks for monitoring and controlling consumption households, second, systems suggest best practices to users providers, third, findings focus on motivations trigger a behavioral change toward efficiency. However, is still no work builds habitual behavior individuals use this purpose. In paper, we survey literature aims at understanding consumers then changing it by recommending...

Excessive domestic energy usage is an impediment towards efficiency. Developing countries are expected to witness unprecedented rise in electricity the forthcoming decades. A large amount of research has been directed behavioral change for Thus, it prudent develop intelligent system that combines proper use technology with behavior order sustainably transform end-user at a scale. This paper presents overview our AI-based efficiency framework applications and explains how micro-moments can...

Trajectory data holds pivotal importance in the shipping industry and transcend their significance various domains, including transportation, health care, tourism, surveillance, security. In maritime domain, improved predictions for estimated time of arrival (ETA) optimal recommendations alternate routes when weather conditions deem it necessary can lead to lower costs, reduced emissions, an increase overall efficiency industry. To this end, a methodology that yields route vessels is...

Unmanned Aerial Systems (UAS) have rapidly gained attraction in recent years as a promising solution to revolutionize numerous applications and meet the growing demand for efficient timely delivery services due their highly automated operation framework. Beyond Visual Line of Sight (BVLOS) operations, particular, offer new means delivering added-value via wide range applications. This "plateau productivity" holds enormous promise, but it is challenging equip drone with affordable...

Robots are intelligent machines that capable of autonomously performing intricate sequences actions, with their functionality being primarily driven by computer programs and machine learning models. Educational robots specifically designed used for teaching purposes attain the interest learners in gaining knowledge about science, technology, engineering, arts, mathematics. widely applied different fields primary secondary education, but usage higher education subjects is limited. Even when...

A large part of the hidden web resides in weblog servers; traditional search engines perform poorly on blogs. We present a method for ranking weblogs utilizing both link graph and similarity, based an enhanced weighted capturing crucial features. Rankings are then assigned using our algorithm, BlogRank, which is modified version PageRank.To validate we ran experiments dataset, processed adapted to engine: http://spiderwave.aueb.gr/BlogwaveOur suggest that algorithm enhances quality returned results.

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