Exploiting Synergy Between Ontologies and Recommender Systems

Recommender systems learn about user preferences over time, automatically finding things of similar interest. This reduces the burden of creating explicit queries. Recommender systems do, however, suffer from cold-start problems where no initial information is available early on upon which to base recommendations. Semantic knowledge structures, such as ontologies, can provide valuable domain knowledge and user information. However, acquiring such knowledge and keeping it up to date is not a trivial task and user interests are particularly difficult to acquire and maintain. This paper investigates the synergy between a web-based research paper recommender system and an ontology containing information automatically extracted from departmental databases available on the web. The ontology is used to address the recommender systems cold-start problem. The recommender system addresses the ontology's interest-acquisition problem. An empirical evaluation of this approach is conducted and the performance of the integrated systems measured

The state-of-the-art in personalized recommender systems for social networking

With the explosion of Web 2.0 application such as blogs, social and professional networks, and various other types of social media, the rich online information and various new sources of knowledge flood users and hence pose a great challenge in terms of information overload. It is critical to use intelligent agent software systems to assist users in finding the right information from an abundance of Web data. Recommender systems can help users deal with information overload problem efficiently by suggesting items (e.g., information and products) that match users’ personal interests. The recommender technology has been successfully employed in many applications such as recommending films, music, books, etc. The purpose of this report is to give an overview of existing technologies for building personalized recommender systems in social networking environment, to propose a research direction for addressing user profiling and cold start problems by exploiting user-generated content newly available in Web 2.0

Exploiting synergy between ontologies and recommender systems

Recommender systems learn about user preferences over time, automatically finding things of similar interest. This reduces the burden of creating explicit queries. Recommender systems do, however, suffer from cold-start problems where no initial information is available early on upon which to base recommendations.Semantic knowledge structures, such as ontologies, can provide valuable domain knowledge and user information. However, acquiring such knowledge and keeping it up to date is not a trivial task and user interests are particularly difficult to acquire and maintain. This paper investigates the synergy between a web-based research paper recommender system and an ontology containing information automatically extracted from departmental databases available on the web. The ontology is used to address the recommender systems cold-start problem. The recommender system addresses the ontology's interest-acquisition problem. An empirical evaluation of this approach is conducted and the performance of the integrated systems measured

Personalised trails and learner profiling within e-learning environments

This deliverable focuses on personalisation and personalised trails. We begin by introducing and defining the concepts of personalisation and personalised trails. Personalisation requires that a user profile be stored, and so we assess currently available standard profile schemas and discuss the requirements for a profile to support personalised learning. We then review techniques for providing personalisation and some systems that implement these techniques, and discuss some of the issues around evaluating personalisation systems. We look especially at the use of learning and cognitive styles to support personalised learning, and also consider personalisation in the field of mobile learning, which has a slightly different take on the subject, and in commercially available systems, where personalisation support is found to currently be only at quite a low level. We conclude with a summary of the lessons to be learned from our review of personalisation and personalised trails

Exploring CALL Options for Teaching EFL in Vietnam

Research has demonstrated that computer-assisted language learning (CALL) has the capacity to enhance second language learning. Therefore, in English as a Foreign Language (EFL) contexts like Vietnam, the government has invested in computers in schools as a way to address the lack of quality in education. However, Vietnamese EFL teachers have made little or no use of these computers. The purpose of this Alternate Plan Paper (APP) is to assist Vietnamese ESL teachers in choosing appropriate CALL programs. I select some of the most effective, user-friendly, and cost-effective CALL options for language areas and language skills. The options are selected based on the availability of resources, the teachers\u27 and learners\u27 computer proficiency levels, and the Vietnamese institutional context. The recommended options are also based on my personal experience as a CALL learner and user, and a one-month observation of CALL applications in a classroom at Minnesota State University, Mankato. The paper also discusses the pedagogical principles for using the recommended options effectively and efficiently

New Media Art/ New Funding Models

Investigates the current state of funding for new media artists, with an emphasis on the support structures for innovative creative work that utilizes advanced technologies as the main vehicle for artistic practice

Transforming YouTube into a valid source of knowledge for Anatomy students

[EN] YouTube is a free and easily accessible tool, with growing importance in the teaching field due to the content of the videos and their interaction options through comments, responses and insertion in social networks. However, some limitations can reduce the value of this tool in University teaching if institutional control is not carried out. Our project consists of the search for experiences based on learning Anatomy on YouTube to be able to incorporate this tool in our department. Almost all researchers found that most of students use YouTube as a source of anatomical knowledge, despite limitations and criticism based on ethical and privacy issues, the video experience itself, the YouTube search algorithm, lack of quality control, advertising purposes or excessive video offer. Researchers experienced that most of the available videos had a poor quality and many mistakes, so professors must be involved in the search and selection of the best appropriate videos. We conclude that YouTube can be used as a source of knowledge for anatomical learning. However it is necessary to inform students of the inconveniences and risks, and make a critical selection by the professors of the videos that best fit in the teaching program.Alegre-Martínez, A.; Martínez-Martínez, MI.; Alfonso-Sánchez, JL. (2020). Transforming YouTube into a valid source of knowledge for Anatomy students. En 6th International Conference on Higher Education Advances (HEAd'20). Editorial Universitat Politècnica de València. (30-05-2020):293-300. https://doi.org/10.4995/HEAd20.2020.11044OCS29330030-05-202