YourMOOC4all: a recommender system for MOOCs based on collaborative filtering implementing UDL

YourMOOC4all is a pilot research project to collect feedback requests regarding accessible design for Massive Open Online Courses (MOOCs). In this online application, a specific website offers the possibility for any learner to freely judge if a particular MOOC complies Universal Design for Learning (UDL) principles. User feedback is of great value for the future development of MOOC platforms and MOOC educational resources, as it will help to follow De-sign for All guidelines. YourMOOC4all is a recommender system which gathers valuable information directly from learners to improve aspects such as the quality, accessibility and usability of this online learning environment. The final objective of collecting user’s feedback is to advice MOOC providers about the missing means for meeting learner needs. This paper describes the pedagogical and technological background of YourMOOC4all and its use cases

Empirical Comparison of Graph Embeddings for Trust-Based Collaborative Filtering

In this work, we study the utility of graph embeddings to generate latent user representations for trust-based collaborative filtering. In a cold-start setting, on three publicly available datasets, we evaluate approaches from four method families: (i) factorization-based, (ii) random walk-based, (iii) deep learning-based, and (iv) the Large-scale Information Network Embedding (LINE) approach. We find that across the four families, random-walk-based approaches consistently achieve the best accuracy. Besides, they result in highly novel and diverse recommendations. Furthermore, our results show that the use of graph embeddings in trust-based collaborative filtering significantly improves user coverage.Comment: 10 pages, Accepted as a full paper on the 25th International Symposium on Methodologies for Intelligent Systems (ISMIS'20

Personalised aesthetics with residual adapters

The use of computational methods to evaluate aesthetics in photography has gained interest in recent years due to the popularization of convolutional neural networks and the availability of new annotated datasets. Most studies in this area have focused on designing models that do not take into account individual preferences for the prediction of the aesthetic value of pictures. We propose a model based on residual learning that is capable of learning subjective, user specific preferences over aesthetics in photography, while surpassing the state-of-the-art methods and keeping a limited number of user-specific parameters in the model. Our model can also be used for picture enhancement, and it is suitable for content-based or hybrid recommender systems in which the amount of computational resources is limited.Comment: 12 pages, 4 figures. In Iberian Conference on Pattern Recognition and Image Analysis proceeding

Q methodology and a Delphi poll: a useful approach to researching a narrative approach to therapy

Q methodology and a Delphi poll combined qualitative and quantitative methods to explore definitions of White and Epston's (1990) narrative approach to therapy among a group of UK practitioners. A Delphi poll was used to generate statements about narrative therapy. The piloting of statements by the Delphi panel identified agreement about theoretical ideas underpinning narrative therapy and certain key practices. A wider group of practitioners ranked the statements in a Q sort and made qualitative comments about their sorting. Quantitative methods (principal components analysis) were used to extract eight accounts of narrative therapy, five of which are qualitatively analysed in this paper. Agreement and differences were identified across a range of issues, including the social construction of narratives, privileging a political stance or narrative techniques and the relationship with other therapies, specifically systemic psychotherapy. Q methodology, combined with the Delphi poll, was a unique and innovative feature of this study

Acne and smoking: is there a relationship?

BACKGROUND: There are contradictory reports on the relationship between acne vulgaris and cigarette smoking. The objective of this study was to examine the relation between acne and cigarette smoking in a case-control study. METHODS: A questionnaire on smoking habits was offered to 350 patients with acne vulgaris and 350 patients suffering from skin diseases other than acne, aged 15 – 40 years, attending in a skin clinic in Tehran, Iran. The patients completed the questionnaires anonymously in the waiting room. RESULTS: Two hundred and ninety-three patients with acne (response rate 83.7 %) and 301 patients with other skin diseases (response rate 86.0 %) completed the questionnaires. Twelve acne patients (4.1 %) and 27 control patients (9.0 %) were current smokers (odds ratio = 0.43, 95% confidence limits 0.22 – 0.87, p < 0.05). But after adjustment for sex, this difference was not significant (odds ratio: 0.61, 95% CI: 0.30–1.26, p > 0.05, Mantel-Haenszel test). CONCLUSION: An association between acne and cigarette smoking was not found in this study

An interdisciplinary intervention for older Taiwanese patients after surgery for hip fracture improves health-related quality of life

Abstract Background The effects of intervention programs on health-related quality of life (HRQOL) of patients with hip fracture have not been well studied. We hypothesized that older patients with hip fracture who received our interdisciplinary intervention program would have better HRQOL than those who did not. Methods A randomized experimental design was used. Older patients with hip fracture (N = 162), 60 to 98 years old, from a medical center in northern Taiwan were randomly assigned to an experimental (n = 80) or control (n = 82) group. HRQOL was measured by the SF-36 Taiwan version at 1, 3, 6, and 12 months after discharge. Results The experimental group had significantly better overall outcomes in bodily pain (&#946; = 9.38, p = 0.002), vitality (&#946; = 9.40, p &lt; 0.001), mental health (&#946; = 8.16, p = 0.004), physical function (&#946; = 16.01, p &lt; 0.001), and role physical (&#946; = 22.66, p &lt; 0.001) than the control group at any time point during the first year after discharge. Physical-related health outcomes (physical functioning, role physical, and vitality) had larger treatment effects than emotional/mental- and social functioning-related health outcomes. Conclusions This interdisciplinary intervention program may improve health outcomes of elders with hip fracture. Our results may provide a reference for health care providers in countries using similar programs with Chinese/Taiwanese immigrant populations. Trial registration NCT01052636http://deepblue.lib.umich.edu/bitstream/2027.42/78259/1/1471-2474-11-225.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78259/2/1471-2474-11-225.pdfPeer Reviewe

Science that "knows" and science that "asks"

Clinician-researchers and experimental scientists do not speak the same language; they have different professional environments and different end-points in their research. This creates considerable problems of comprehension and communication, which constitute a major drawback in multidisciplinary work such as translational medicine. A stereotypic representation of both these worlds is presented as a starting point to encourage debate on this issue

Tag-Aware Recommender Systems: A State-of-the-art Survey

In the past decade, Social Tagging Systems have attracted increasing attention from both physical and computer science communities. Besides the underlying structure and dynamics of tagging systems, many efforts have been addressed to unify tagging information to reveal user behaviors and preferences, extract the latent semantic relations among items, make recommendations, and so on. Specifically, this article summarizes recent progress about tag-aware recommender systems, emphasizing on the contributions from three mainstream perspectives and approaches: network-based methods, tensor-based methods, and the topic-based methods. Finally, we outline some other tag-related works and future challenges of tag-aware recommendation algorithms.Comment: 19 pages, 3 figure

Research opportunities for argumentation in social networks

Nowadays, many websites allow social networking between their users in an explicit or implicit way. In this work, we show how argumentation schemes theory can provide a valuable help to formalize and structure on-line discussions and user opinions in decision support and business oriented websites that held social networks between their users. Two real case studies are studied and analysed. Then, guidelines to enhance social decision support and recommendations with argumentation are provided.This work summarises results of the authors joint research, funded by an STMS of the Agreement Technologies COST Action 0801, by the Spanish government grants [CONSOLIDER-INGENIO 2010 CSD2007-00022, and TIN2012-36586-C03-01] and by the GVA project [PROMETEO 2008/051].Heras Barberá, SM.; Atkinson, KM.; Botti Navarro, VJ.; Grasso, F.; Julian Inglada, VJ.; Mcburney, PJ. (2013). Research opportunities for argumentation in social networks. 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