Although Augmented Reality (AR) technology has entered many market and knowledge domains such as games and leisure activities, it remains rather limited in digital heritage. After studying the potentiality of using modern AR elements in a museum context, this paper proposes the use of additional game and educational elements in the core AR application in order to enhance the overall on-the-spot museum visitor’s experience. An agile AR application design methodology was followed by taking into account the needs of small-to-medium sized real-world museums. Moreover, a heuristic evaluation protocol was applied by a group of experts in order to test the proof-of-concept AR application, in which some novel elements were proposed such as the AR quiz game. The main findings indicate that enhanced AR experiences in museum settings can make a nice fit with the user environment, physical and perceptual abilities, known metaphors, and user position and motion in 3D space. Moreover, AR services can be provided under a minimum distraction and physical effort. As a conclusion, AR technologies are mature enough to be standardized for museum usage, while the audience seems to be ready to take advantage of the related enhanced museum experiences to maximize both user satisfaction and learning outcomes.

In the previous two decades, knowledge graphs (KGs) have evolved significantly, inspiring developers to build ever-more context-related KGs. Due to this development, artificial intelligence (AI) applications can now access open domain-specific information in a format that is both semantically rich and machine comprehensible. In this article, a framework that depicts functional design for indoor workspaces and urban adaptive design, in order to help architects, artists, and interior designers for the design and construction of an urban or indoor workspace, based on the emotions of human individuals, is introduced. For the creation of online adaptive environments, the framework may incorporate emotional, physiological, visual, and textual measures. Additionally, an information retrieval mechanism that extracts critical information from the framework in order to assist the architects, artists, and the interior designers is presented. The framework provides access to commonsense knowledge about the (re-)design of an urban area and an indoor workspace, by suggesting objects that need to be placed, and other modifications that can be applied to the location, in order to achieve positive emotions. The emotions referred reflect to the emotions experienced by an individual when being in the indoor or urban area, which are pointers for the functionality, the memorability, and the admiration of the location. The framework also performs semantic matching between entities from the web KG ConceptNet, using semantic knowledge from ConceptNet and WordNet, with the ones existing in the KG of the framework. The paper provides a set of predefined SPARQL templates that specifically handle the ontology upon which the knowledge retrieval system is based. The framework has an additional argumentation function that allows users to challenge the knowledge retrieval component findings. In the event that the user prevails in the reasoning, the framework will learn new knowledge.

This paper presents a benchmarking survey on query expansion techniques for social media information retrieval, with a focus on comparing the performance of methods using semantic web technologies. The study evaluated query expansion techniques such as generative AI models and semantic matching algorithms and how they are integrated in a semantic framework. The evaluation was based on cosine similarity metrics, including the Discounted Cumulative Gain (DCG), Ideal Discounted Cumulative Gain (IDCG), and normalized Discounted Cumulative Gain (nDCG), as well as the Mean Average Precision (MAP). Additionally, the paper discusses the use of semantic web technologies as a component in a pipeline for building thematic knowledge graphs from retrieved social media data with extended ontologies integrated for the refugee crisis. The paper begins by introducing the importance of query expansion in information retrieval and the potential benefits of incorporating semantic web technologies. The study then presents the methodologies and outlines the specific procedures for each query expansion technique. The results of the evaluation are presented, as well as the rest semantic framework, and the best-performing technique was identified, which was the curie-001 generative AI model. Finally, the paper summarizes the main findings and suggests future research directions.

This paper presents a system designed to utilize innovative spatial interconnection technologies for sites and events of environmental, cultural and tourist interests. The system will discover and consolidate semantic information from multiple sources, providing the end-user the ability to organize and implement integrated and enhanced tours. The system, called e-xnilatis, will extend existing innovative techniques, including: semi-automated searching and extraction of real-time knowledge from online resources, automated discovery of points of interest as well as events, semantic integration, classification and hierarchy of information from various sources, spatial representation of content, personalized user experience and Augmented Reality (AR) for the interconnection of the digital with the natural environment. A complex online platform and applications for smart devices will be developed so that the user

With the constant growth of social media in our daily lives, a huge amount of information is generated online by multiple social networks. However, what can we actually extract with the science of social media sensing? It is a very challenging task to mine meaningful data out of this vast crowdsourcing volume, which also rapidly changes or ends up being misleading. The scope of this paper is to present different approaches that overcome these challenges and utilize social media information from various sources. This work illustrates applications that: improve the performance of architectural design; preserve the cultural heritage; enhance citizen security; provide early detection for disasters; and discover creeping crisis events. A large variety of analyses are presented, including, among other, disaster or crime event detection, user identity linkage, relevance classification, and community detection techniques. The evaluation of the presented methods is also given in this article, proving that they can be practical and valuable in many applications.

There is great potential in interdisciplinary traveling platforms mingling knowledge about cultural heritage aspects, such as places with schedules providing visits or even containing augmented reality features also, along with environmental concerns to enhance personalized tourist experience and tripping avocation. For an ontological framework to support and nominate trip detours of targeted interests according to end-users, it should incorporate and unify as much heterogeneous information, deriving either from web sources or wherever there are ubiquitously available such as sensors or open databases. A plethora of qualitatively diverse data along with adequate quantities of them escalate the contingent results in terms of conferring a plurality of relevant options which can be utterly manifested through involving axioms with rule-based reasoning functionalities upon properties considered to be irrelevant to each other at first glance. Thus, managing to import predefined concepts from other ontologies, such as temporality or spatiality, and combine them with new defined concepts to tourist assets, such as points of interest, results in novel meaningful relationships never established before. Apart from the utilization of pre-existent resources and logic towards automatic detouring suggestions, a wide-spectrum modeling enables a suitable problem statement relevant to the e-Tracer framework and comprehension of the issues, providing the opportunity of statistical analysis of knowledge when adequate amounts amassed.