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The purpose of this paper is to provide adaptive access to learning resources in the digital library.

A novel method using ontology-based multi-attribute collaborative filtering is proposed. Digital libraries are those which are fully automated and all resources are in digital form and access to the information available is provided to a remote user as well as a conventional user electronically. To satisfy users' information needs, a humongous amount of newly created information is published electronically in digital libraries. While search applications are improving, it is still difficult for the majority of users to find relevant information. For better service, the framework should also be able to adapt queries to search domains and target learners.

This paper improves the accuracy and efficiency of predicting and recommending personalized learning resources in digital libraries. To facilitate a personalized digital learning environment, the authors propose a novel method using ontology-supported collaborative filtering (CF) recommendation system. The objective is to provide adaptive access to learning resources in the digital library. The proposed model is based on user-based CF which suggests learning resources for students based on their course registration, preferences for topics and digital libraries. Using ontological framework knowledge for semantic similarity and considering multiple attributes apart from learners' preferences for the learning resources improve the accuracy of the proposed model.

The results of this work majorly rely on the developed ontology. More experiments are to be conducted with other domain ontologies.

The proposed approach is integrated into Nucleus, a Learning Management System (https://nucleus.amcspsgtech.in). The results are of interest to learners, academicians, researchers and developers of digital libraries. This work also provides insights into the ontology for e-learning to improve personalized learning environments.

This paper computes learner similarity and learning resources similarity based on ontological knowledge, feedback and ratings on the learning resources. The predictions for the target learner are calculated and top N learning resources are generated by the recommendation engine using CF.

This paper aims to identify and provide a theoretical explanation for the barriers that hinder the adoption of emerging technologies in the architecture, engineering and construction industry, irrespective of the company’s size, specialization or geographical location. In addition, the paper proposes potential areas for future research in this domain.

A list of barriers hindering the adoption of emerging technologies was identified and clarified using a systematic literature review of various scientific sources.

Twenty-five barriers were recognized and explained and some suggestions for future research studies were provided.

The barriers related to a specific country or region or to a specific technology were excluded.

By providing a deeper comprehension of the barriers hindering the adoption of emerging technologies, this review is expected to encourage their adoption in the industry. Furthermore, it could prove valuable in devising effective strategies for the successful implementation of these technologies.

The research aims to determine local food attributes for measuring and evaluating that appeal tourists to the gastronomic city of Phuket, Thailand.

The first step is, the item generation, which includes an in-depth interview. Secondly, scale purification includes the exploratory factor analysis, which generates a preliminary factor structure. In the final step, scale validation, confirmatory component analysis is used to test the items and dimensions.

The 33 items organized into eight dimensions: food quality, authenticity, hygiene, interpersonal, novelty, service provider, foodservice place and value added for a creative city of gastronomy were demonstrated to be valid and reliable after a thorough development process.

The findings assist practitioners in recognizing the many aspects of local food attributes, as well as how destination managers can employ these factors to promote a destination.

This research contributes to the theoretical literature on a gastronomic creative city, with more research into the links between destination management and other important concepts. In terms of the outcomes of a creative city of gastronomy management, this study might serve as a reference for destination managers and travel suppliers.