Presentation Bias in movie recommendation algorithms

Dissertation presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization Information Analysis and ManagementThe emergence of video on demand (VOD) has transformed the way the content finds its audience. Several improvements have been made on algorithms to provide better movie recommendations to individuals. Given the huge variety of elements that characterize a film (such as casting, genre, soundtrack, amongst others artistic and technical aspects) and that characterize individuals, most of the improvements relied on accomplishing those characteristics to do a better job regarding matching potential clients to each product. However, little attention has been given to evaluate how the algorithms’ result selection are affected by presentation bias. Understanding bias is key to choosing which algorithms will be used by the companies. The existence of a system with presentation bias and feedback loop is already a problem stated by Netflix. In this sense, this research will fill that gap providing a comparative analysis of the bias of the major movie recommendation algorithms

Heeding the silent partner in the Parent-Child Relationship: A new agenda to translate research on children’s perspectives into practice

The parent-child relationship (PCR) lies at the heart of our life experiences and life outcomes. It has been suggested that we are on the cusp of a paradigm shift in our approach to understanding the nature and influence of this relationship, from the currently dominant adult-centric approach to one that includes children’s perspectives. This thesis takes a strategic, translational approach to identifying the work required to realise this shift and to establish an evidence base for clinical practice regarding the PCR and its investigation. In response to identified deficits in the literature and obstacles to progress, several new conceptual and methodological tools were designed. These include: the Gap Analysis – Prospective framework, to facilitate evidence synthesis and to guide a new translational research agenda; the Developmental Research Participation Rubric (DRPR), translating developmental theories into guidelines for enabling the research participation of children of different ages; a Quality of Evidence Rating System, to evaluate diverse empirical methodologies against person-centred, developmentally-sensitive criteria; and a Developmental Interview Framework (DIF), to provide comprehensive, person-centred guidelines for engaging child informants. Applying these tools to clinically relevant research into the PCR, the DRPR indicated middle childhood to be the point at which children are likely to be developmentally ready to be primary informants about their PCR. However, the voices of children were found to be missing from the PCR literature. Furthermore, there was no reliable empirical evidence base to guide interviewing children about familial relationships and other non-forensic, non-diagnostic topics. Consequently, the DIF was used to design and subsequently pilot a developmentally-sensitive interview methodology. It is concluded that a prospective and systematic approach to clinical psychological research into (a) the PCR and (b) interview methodology is both necessary and possible, by flexible use of mixed methods. Both bodies of work will contribute to evidence-based practice with children

Recommender systems in industrial contexts

This thesis consists of four parts: - An analysis of the core functions and the prerequisites for recommender systems in an industrial context: we identify four core functions for recommendation systems: Help do Decide, Help to Compare, Help to Explore, Help to Discover. The implementation of these functions has implications for the choices at the heart of algorithmic recommender systems. - A state of the art, which deals with the main techniques used in automated recommendation system: the two most commonly used algorithmic methods, the K-Nearest-Neighbor methods (KNN) and the fast factorization methods are detailed. The state of the art presents also purely content-based methods, hybridization techniques, and the classical performance metrics used to evaluate the recommender systems. This state of the art then gives an overview of several systems, both from academia and industry (Amazon, Google ...). - An analysis of the performances and implications of a recommendation system developed during this thesis: this system, Reperio, is a hybrid recommender engine using KNN methods. We study the performance of the KNN methods, including the impact of similarity functions used. Then we study the performance of the KNN method in critical uses cases in cold start situation. - A methodology for analyzing the performance of recommender systems in industrial context: this methodology assesses the added value of algorithmic strategies and recommendation systems according to its core functions.Comment: version 3.30, May 201

Barriers and challenges of the assessment framework of the Commission Recommendation (EU) 2019/786 on building renovation by European RTD projects

The refurbishment of buildings is one of the main keys to pursue the targets of the European Green Deal, and to accomplish the European Union has applied two mechanisms among others: the European policy and the European Research and Technological Development (RTD) projects. On the one hand, the EU has published the Commission Recommendation (EU) 2019/786 with an assessment framework composed by Measurable Progress Indicators (MPI) that can be considered the main legal instrument to measure the progress of the decarbonisation together with health & wellness, social and economic related targets of the Directive 2018/844, the Energy Performance of Buildings Directive (EPBD). On the other hand, the RTD projects also pursue the targets of the EU but following their own assessment methodology com-posed by Key Performance Indicators (KPIs). Considering the parallelism of these two mechanisms, the objective of this study is to analyse the applicability of the EU's assessment framework by the RTD pro-jects, establishing a critical point of view of the viability of the MPIs and identifying the barriers and chal-lenges of the evaluation system proposed by the EU. Regarding the methodology, the applicability of MPIs by RTD projects has been analysed in five stages: (1) Identification and listing of the MPIs of EU Recommendation; (2) selection of European RTD projects; (3) identification of the KPIs applied by the projects; (4) study of the concordance of the MPIs of the Commission Recommendation's assessment framework and the KPIs of the RTD projects; (5) evaluation of the barriers and challenges of the applica-bility of the EU's MPIs based on the level of agreement with the projects' KPIs. This investigation shows that although some evaluation scopes of the Commission Recommendation (EU) 2019/786 do agree with high degree with RTD projects, many MPIs present barriers related to the low reliability, the absence of standardised calculation methods, and the lack of data. Besides, the assessment framework of the Commission Recommendation (EU) 2019/786 also presents challenges to improve the evaluation of the building renovation like calibration techniques, standardised input data and the shortlisting of the MPIs to improve the effectiveness of the method. The main conclusion is that the readjustment of the assessment framework proposed in the Recommendation (EU) 2019/786 is needed. This readjustment is proposed to be done by shortlisting the MPIs and defining standardised measurement methods in order to build a common roadmap that could be followed and assessed homogenously towards the decarbon-isation of the European building stock.Part of the work presented in this paper belongs to the research Project LOCAL-REGEN (PID2019-104871RB-C22), funded by the Ministry of Science and Innovation – State Research Agency/10.13039/501100011033. Moreover, this research work is part of the corresponding author's Doctoral Thesis that aims to investigate the holistic assessment of technical renovation solutions of residential buildings in the Basque Country funded by the Predoctoral Training Programme for Non-Doctor Research Personnel of the Department of Education of the Basque Government (PRE_2021_1_0247)

Sustainable lighting product development underpinned by online data mining and life cycle assessment

The accurate acquisition of customer requirement information is an important part in product planning and positioning, it plays a decisive role in the success of products in the market. the rapid development of e-commerce makes increasing more consumers shopping online and a big volume of customer reviews are posted on different Websites. The online reviews contain valuable opinions of customers, enabling designers to understand their concerns. In this research, an integrated approach has been developed to mine customer requirements according to the online reviews collected from e-commerce sites to form product design specifications. The main research contents include the following aspects: (1) development of useful online review prediction and classification approach; (2) online review implicit product features and sentiment analysis based on the constructed feature and sentiment lexicon; (3) built a knowledge base containing customer requirements mined from online reviews; (4) conduct a dedicated environmental and social LCA on the proposed domestic lighting product by using a professional LCA software. In this study, multiple models and technologies/methods have been successfully implemented: review helpfulness classification model has been constructed based on the training set and test set by tuning and optimizing; proposes a new approach to implicit feature and sentiment analysis, based on explicit formal feature-emotion sentences, implicit feature sentences and implicit sentiment sentences, combined with a feature lexicon, a 1V1/1Vn sentiment-feature rule base and the feature-emotion word pairs are extracted; based on the preliminary analysis results of feature extraction and sentiment analysis, combined with KANO model to establish user requirement mining rules, and consider satisfaction, propose the user demand priority to obtain the final list of user requirements; a real industrial context with lighting product manufacturer (ONA) in Spain has involved with the lighting product life cycle analysis and development for new product. The analytical results of these studies present an in-depth modelling and analysis on the sustainable lighting product lifecycle with the aid of real manufacturing data

Australian guideline on prevention of foot ulceration: part of the 2021 Australian evidence-based guidelines for diabetes-related foot disease

Background: There are no current Australian guidelines on the prevention of diabetes-related foot ulceration (DFU). A national expert panel aimed to systematically identify and adapt suitable international guidelines to the Australian context to create new Australian evidence-based guidelines on prevention of first-ever and/or recurrent DFU. These guidelines will include for the first-time considerations for rural and remote, and Aboriginal and Torres Strait Islander peoples. Methods: The National Health and Medical Research Council procedures were followed to adapt suitable international guidelines on DFU prevention to the Australian health context. This included a search of public databases after which the International Working Group on the Diabetic Foot (IWGDF) prevention guideline was deemed the most appropriate for adaptation. The 16 IWGDF prevention recommendations were assessed using the ADAPTE and GRADE systems to decide if they should be adopted, adapted or excluded for the new Australian guideline. The quality of evidence and strength of recommendation ratings were re-evaluated with reference to the Australian context. This guideline underwent public consultation, further revision, and approval by national peak bodies. Results: Of the 16 original IWGDF prevention recommendations, nine were adopted, six were adapted and one was excluded. It is recommended that all people at increased risk of DFU are assessed at intervals corresponding to the IWGDF risk ratings. For those at increased risk, structured education about appropriate foot protection, inspection, footwear, weight-bearing activities, and foot self-care is recommended. Prescription of orthotic interventions and/or medical grade footwear, providing integrated foot care, and self-monitoring of foot skin temperatures (contingent on validated, user-friendly and affordable systems becoming available in Australia) may also assist in preventing DFU. If the above recommended non-surgical treatment fails, the use of various surgical interventions for the prevention of DFU can be considered. Conclusions: This new Australian evidence-based guideline on prevention of DFU, endorsed by 10 national peak bodies, provides specific recommendations for relevant health professionals and consumers in the Australian context to prevent DFU. Following these recommendations should achieve better DFU prevention outcomes in Australia