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Preprint submitted to Information Processing & Management Tags are a convenient way to label resources on the web. An interesting question is whether one can determine the semantic meaning of tags in the absence of some predefined formal structure like a thesaurus. Many authors have used the usage data for tags to find their emergent semantics. Here, we argue that the semantics of tags can be captured by comparing the contexts in which tags appear. We give an approach to operationalizing this idea by defining what we call paradigmatic similarity: computing co-occurrence distributions of tags with tags in the same context, and comparing tags using information theoretic similarity measures of these distributions, mostly the Jensen-Shannon divergence. In experiments with three different tagged data collections we study its behavior and compare it to other distance measures. For some tasks, like terminology mapping or clustering, the paradigmatic similarity seems to give better results than similarity measures based on the co-occurrence of the documents or other resources that the tags are associated to. We argue that paradigmatic similarity, is superior to other distance measures, if agreement on topics (as opposed to style, register or language etc.), is the most important criterion, and the main differences between the tagged elements in the data set correspond to different topics
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There is a central dilemma embedded in the relationship between teachers and researchers. Teachers know the story of the classroom well, but they are seldom asked to tell their stories, nor do they usually have the opportunity. Researchers, on the other hand, are skilled at telling certain things about classrooms, but they often miss the central stories that are there. This divergence can lead to different opinions on what teaching is about and what is important within it. To bridge this gap, we describe an approach which puts the teacher and the student at the centre. With respect to emotional and behavioural problems of students, we underline the notion of student-teacher compatibility, deriving from theories emphasizing the transactional/reciprocal nature of human behaviour. One of the aims of the Lectorship and Knowledge Network Behavioural Problems in School Practice, is to identify at-risk-teachers (i.e. those most vulnerable to the presence of behaviourally challenging students and parents) so that interventions, both in initial teacher training as well as in inservice training can be applied to help them develop adequate attitudes and coping-skills. In clinical supervision, peer coaching or reflective practice, these teachers can be helped to consider in what way student and parental problem behaviour contribute to their loss of satisfaction, their feelings of self doubt, perceived disruption of the teaching process, and their frustration working with parents.
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In this paper, we investigate the efficiency of ray queries on the CPU in the context of path tracing, where ray distributions are mostly random. We show that existing schemes that exploit data locality to improve ray tracing efficiency fail to do so beyond the first diffuse bounce, and analyze the cause for this. We then present an alternative scheme inspired by the work of Pharr et al. in which we improve data locality by using a data-centric breadth-first approach. We show that our scheme improves on state-of-the-art performance for ray distributions in a path tracer.
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The shift from home and custom-made clothing to mass-produced ready-mades in 20 th-century Europe has been the subject of studies from multiple disciplines and across various locations. Contributing to this field of studies, and extending the analysis until the present day, a group of female consumers living in Amsterdam in the 1950s and 2010s were interviewed about their sartorial habits. The study identifies a discrepancy between common manufacturing processes and values related to identity as a central cause of this shift. Furthermore it explores how such a discrepancy can be found again today, arguing that this divergence is leading to the re-emergence of customized production.
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This paper researches perceptions of the concept of price fairness in the Dutch coffee market. We distinguish four alternative standards of fair prices based on egalitarian, basic rights, capitalistic and libertarian approaches. We investigate which standards are guiding the perceptions of price fairness of citizens and coffee trade organizations. We find that there is a divergence in views between citizens and key players in the coffee market. Whereas citizens support the concept of fairness derived from the basic rights approach, holding that the price should provide coffee farmers with a minimum level of subsistence, representatives of Dutch coffee traders hold the capitalistic view that the free world market price is fair.
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Education plays a major role in this paradox: the cultural diversity that is increased by immigration is eliminated by successful education: education aims to maximise the opportunities for every child within the emerging global culture and thus reduce cultural diversity. The road from the Enlightenment that would bring us a better world is increasingly proving to be a dead end, especially with regard to the climate and the depletion of the resources the planet can provide (ecology). Just now that a global culture has emerged into which all those other cultures are assimilated, the question is whether cultures that deal more sustainably with ecology and have problems accommodating to global culture, should not be given more voice in the transition to a more sustainable global culture. It is argued that in popular music forms an example in which successful productions have a multitude of cultural styles, from world music to hip-hop to rock. In fact, almost everyone from various cultural backgrounds can relate to a certain style. Pop music therefore does not necessarily work as an institution that reduces diversity. Education does just that, unconsciously, and often with extensive inclusion programs. She could learn from pop music!
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In a study commissioned by the Association of Dutch Municipalities (VNG), the applied research group European Impact has compiled the results from interviews executed by approximately 240 European Studies students at The Hague University of Applied Sciences. The purpose of this report is to compare and contrast the situation of intra-EU labor migrants (hereafter referred to as EU mobile citizens) in regard to registration, housing, and information flows in 12 different municipalities across the EU. Based on semi-structured interviews with municipal workers and individuals from employment agencies/companies from the selected municipalities, the picture that emerges is one of divergence. There are significant variations regarding the registration procedure and information flows for EU mobile citizens across the selected municipalities. For registration, differences include where the registration takes place, the amount of collaboration between municipalities and employment agencies/companies on registering EU mobile citizens, and the importance of addresses in the registration process. Regarding information flows across the selected municipalities, there are significant variations in the amount and type of information available to EU mobile citizens, the number of languages information is available in,as well as how the information is organized (i.e. in a centralized or decentralized way). Furthermore, while all the member states in which the selected municipalities are located provide information regarding registration on the Single Digital Gateway, not all provide information about renting housing. As for housing, the results revealed that most of the selected municipalities face issues with housing and that EU mobile citizens typically find housing either via their employers or personal network. Based on the results, a list of potential best practices and policy areas that could be improved was compiled. Furthermore, in order to have a stronger overview of policy developments in the field of EU mobile citizens among different municipalities, the VNG could consider hosting a Community of Practice with different municipalities across the EU as well as monitoring Interreg Europe projects focused on improving the situation of EU mobile citizens.
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This chapter concerns the practical aspects of creating experiences that matter. It describes the basics of the creative process focusing on skills and requirements. Essential qualities are presented, such as awareness, a curious attitude, and perseverance. The difference between divergence and convergence is also considered, and the Innovation Engine is explained. It is important to understand the experience phenomenon in order to be able to develop meaningful experiences. The different realms of experience are touched upon as an introduction to the Interactive Experience Model. This model illustrates the three key contexts that influence an interactive experience the namely sociocultural, personal and physical contexts. The chapter continues with a description of the Customer Journey Canvas and how it functions both as a monitoring and as a creative tool for experience design. The various options for the optimal final selection are tested and selected using scenario writing and prototyping. The importance of fast failure and iteration are emphasized. Finally, the chapter returns to the co-creation intentions of the Imagineering process.
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A common strategy to assign keywords to documents is to select the most appropriate words from the document text. One of the most important criteria for a word to be selected as keyword is its relevance for the text. The tf.idf score of a term is a widely used relevance measure. While easy to compute and giving quite satisfactory results, this measure does not take (semantic) relations between words into account. In this paper we study some alternative relevance measures that do use relations between words. They are computed by defining co-occurrence distributions for words and comparing these distributions with the document and the corpus distribution. We then evaluate keyword extraction algorithms defined by selecting different relevance measures. For two corpora of abstracts with manually assigned keywords, we compare manually extracted keywords with different automatically extracted ones. The results show that using word co-occurrence information can improve precision and recall over tf.idf.
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