THOR: A Hybrid Recommender System for the Personalized Travel Experience

One of the travelers’ main challenges is that they have to spend a great effort to find and choose the most desired travel offer(s) among a vast list of non-categorized and non-personalized items. Recommendation systems provide an effective way to solve the problem of information overload. In this work, we design and implement “The Hybrid Offer Ranker” (THOR), a hybrid, personalized recommender system for the transportation domain. THOR assigns every traveler a unique contextual preference model built using solely their personal data, which makes the model sensitive to the user’s choices. This model is used to rank travel offers presented to each user according to their personal preferences. We reduce the recommendation problem to one of binary classification that predicts the probability with which the traveler will buy each available travel offer. Travel offers are ranked according to the computed probabilities, hence to the user’s personal preference model. Moreover, to tackle the cold start problem for new users, we apply clustering algorithms to identify groups of travelers with similar profiles and build a preference model for each group. To test the system’s performance, we generate a dataset according to some carefully designed rules. The results of the experiments show that the THOR tool is capable of learning the contextual preferences of each traveler and ranks offers starting from those that have the higher probability of being selected

Engaging end-user driven recommender systems: personalization through web augmentation

In the past decades recommender systems have become a powerful tool to improve personalization on the Web. Yet, many popular websites lack such functionality, its implementation usually requires certain technical skills, and, above all, its introduction is beyond the scope and control of end-users. To alleviate these problems, this paper presents a novel tool to empower end-users without programming skills, without any involvement of website providers, to embed personalized recommendations of items into arbitrary websites on client-side. For this we have developed a generic meta-model to capture recommender system configuration parameters in general as well as in a web augmentation context. Thereupon, we have implemented a wizard in the form of an easy-to-use browser plug-in, allowing the generation of so-called user scripts, which are executed in the browser to engage collaborative filtering functionality from a provided external rest service. We discuss functionality and limitations of the approach, and in a study with end-users we assess the usability and show its suitability for combining recommender systems with web augmentation techniques, aiming to empower end-users to implement controllable recommender applications for a more personalized browsing experience.Fil: Wischenbart, Martin. Johannes Kepler University Linz; AustriaFil: Firmenich, Sergio Damian. Universidad Nacional de La Plata. Facultad de Informática. Laboratorio de Investigación y Formación en Informática Avanzada; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; ArgentinaFil: Rossi, Gustavo Héctor. Universidad Nacional de La Plata. Facultad de Informática; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; ArgentinaFil: Bosetti, Gabriela Alejandra. Universidad Nacional de La Plata. Facultad de Informática; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; ArgentinaFil: Kapsammer, Elisabeth. Johannes Kepler University Linz; Austri

Almost Rerere: Learning to resolve conflicts in distributed projects

The concurrent development of applications requires reconciling conflicting code updates by different developers. Recent research on the nature of merge conflicts in open source projects shows that a significant fraction of merge conflicts have limited size (one or two lines of code) and are resolved with simple strategies that use code present in the merged versions. Thus the opportunity arises of supporting the resolution of merge conflicts automatically by learning the way in which developers fix them. In this paper we propose a framework for automating the resolution of merge conflicts which learns from the resolutions made by developers and encodes such knowledge into conflict resolution rules applicable to conflicts not seen before. The proposed approach is text-based, does not depend on the programming languages of the merged files and exploits a well-known and general language (search and replacement regular expressions) to encode the conflict resolution rules. Evaluation results on 14,872 conflicts from 25 projects show that the system can synthesize a resolution for 49% of the conflicts occurred during the merge process (89% if one considers conflicts that have at least one similar conflict in the data set) and can reproduce exactly the same solution that human developers have applied in 55% of the cases (62% for single line conflicts)

Challenges of rapid migration to fully virtual education in the age of the Corona virus pandemic: experiences from across the world

The social disruption caused by the sudden eruption of the Corona Virus pandemic has shaken the whole world, influencing all levels of education immensely. Notwithstanding there was a lack of preparedness for this global public health emergency which continues to affect all aspects of work and life. The problem is, naturally, multifaceted, fast evolving and complex, affecting everyone, threatening our well-being, the global economy, the environment and all societal and cultural norms and our everyday activities. In a recent UNESCO report it is noted that nearly a billion and a quarter (which is 67,7 % of the total number) of learners have been affected by the Corona Virus pandemic worldwide. The education sector at all levels has been one of the hardest hit sectors particularly as the academic/school year was in full swing. The impact of the pandemic is widespread, representing a health hazard worldwide. Being such, it profoundly affects society as a whole, and its members that are, in particular, i) individuals (the learners, their parents, educators, support staff), ii) schools, training organisations, pedagogical institutions and education systems, iii) quickly transformed policies, methods and pedagogies to serve the newly appeared needs of the latter. Lengthy developments of such scale usually take years of consultation, strategic planning and implementation. In addition to raising awareness across the population of the dangers of the virus transmission and instigating total lockdown, it has been necessary to develop mechanisms for continuing the delivery of education as well as demanding mechanisms for assuring the quality of the educational experience and educational results. There is often scepticism about securing quality standards in such a fast moving situation. Often in the recent past, the perception was that courses and degrees leading to an award are inferior if the course modules (and sometimes its assessment components) were wholly online. Over the last three decades most Higher Education institutions developed both considerable infrastructure and knowhow enabling distance mode delivery schools (Primary and Secondary) had hardly any necessary infrastructure nor adequate knowhow for enabling virtual education. In addition, community education and various training providers were mainly delivered face-to-face and that had to either stop altogether or rapidly convert materials, exercises and tests for online delivery and testing. A high degree of flexibility and commitment was demanded of all involved and particularly from the educators, who undertook to produce new educational materials in order to provide online support to pupils and students. Apart from the delivery mode of education, which is serving for certificated programmes, it is essential to ensure that learners’ needs are thoroughly and continuously addressed and are efficiently supported throughout the Coronavirus or any other future lockdown. The latter can be originated by various causes and reasons that vary in nature, such as natural or socioeconomical. Readiness, thus, in addition to preparedness, is the primary key question and solution when it comes to quality education for any lockdown. In most countries, the compulsory primary and secondary education sectors have been facing a more difficult challenge than that faced by Higher Education. The poor or in many cases non-existent technological infrastructure and low technological expertise of the teachers, instructors and parents, make the delivery of virtual education difficult or even impossible. The latter, coupled with phenomena such as social exclusion and digital divide where thousands of households do not have adequate access to broadband Internet, Wi-Fi infrastructure and personal computers hamper the promising and strenuous virtual solutions. The shockwaves of the sudden demands on all sectors of society and on individuals required rapid decisions and actions. We will not attempt to answer the question “Why was the world unprepared for the onslaught of the Coronavirus pandemic” but need to ascertain the level of preparedness and readiness particularly of the education sector, to effect the required rapid transition. We aimed to identify the challenges, and problems faced by the educators and their institutions. Through first-hand experiences we also identify best practices and solutions reached. Thus we constructed a questionnaire to gather our own responses but also experiences from colleagues and members of our environment, family, friends, and colleagues. This paper reports the first-hand experiences and knowledge of 33 co-authors from 27 institutions and from 13 different countries from Europe, Asia, and Africa. The communication technologies and development platforms used are identified; the challenges faced as well as solutions and best practices are reported. The findings are consolidated into the four areas explored i.e. Development Platforms, Communications Technologies, Challenges/Problems and Solutions/Best Practices. The conclusion summarises the findings into emerging themes and similarities. Reflections on the lasting impact of the effect of Coronavirus on education, limitations of study, and indications of future work complete the paper

Autonomy and Intelligence in the Computing Continuum: Challenges, Enablers, and Future Directions for Orchestration

Future AI applications require performance, reliability and privacy that the existing, cloud-dependant system architectures cannot provide. In this article, we study orchestration in the device-edge-cloud continuum, and focus on AI for edge, that is, the AI methods used in resource orchestration. We claim that to support the constantly growing requirements of intelligent applications in the device-edge-cloud computing continuum, resource orchestration needs to embrace edge AI and emphasize local autonomy and intelligence. To justify the claim, we provide a general definition for continuum orchestration, and look at how current and emerging orchestration paradigms are suitable for the computing continuum. We describe certain major emerging research themes that may affect future orchestration, and provide an early vision of an orchestration paradigm that embraces those research themes. Finally, we survey current key edge AI methods and look at how they may contribute into fulfilling the vision of future continuum orchestration.Comment: 50 pages, 8 figures (Revised content in all sections, added figures and new section