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Kille, Benjamin (author), Lommatzsch, Andreas (author), Hopfgartner, Frank (author), Larson, M.A. (author), Brodt, Torben (author)The CLEF NewsREEL challenge allows researchers to evaluate news recommendation algorithms both online (NewsREEL Live) and offline (News-REEL Replay). Compared with the previous year NewsREEL challenged participants with a higher volume of messages and new news portals. In the 2017 edition of the CLEF NewsREEL challenge a wide variety of new...conference paper 2017
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Liang, Yu (author), Loni, B. (author), Larson, M.A. (author)In the CLEF NewsREEL 2017 challenge, we build a delegation model based on the contextual bandit algorithm. Our goal is to investigate whether a bandit approach combined with context extracted from the user side, from the item side and from user-item interaction can help choose the appropriate recommender from a recommender algorithm pool for the...conference paper 2017
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Kille, Benjamin (author), Lommatzsch, Andreas (author), Hopfgartner, Frank (author), Larson, M.A. (author), de Vries, A.P. (author)Recommender System research has evolved to focus on developing algorithms capable of high performance in online systems. This development calls for a new evaluation infrastructure that supports multi-dimensional evaluation of recommender systems. Today’s researchers should analyze algorithms with respect to a variety of aspects including...conference paper 2017
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Lofi, C. (author), Tintarev, N. (author)Requests for recommendation can be seen as a form of query for candidate items, ranked by relevance. Users are however o‰en<br/>unable to crisply de€ne what they are looking for. One of the core concepts of natural communication for describing and explaining<br/>complex information needs in an intuitive fashion are analogies: e.g., “What is to...conference paper 2017
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Yang, J. (author), Cantador, Iván (author), Nurbakova, Diana (author), Cortés-Cediel, María E. (author), Bozzon, A. (author)This manifesto summarises the outcomes of the 1st Workshop on Recommender Systems for Citizens (CitRec'17), held at the 11th ACM Conference on Recommender Systems, in August 2017 in Como, Italy. We discuss challenges and opportunities for the development of recommender systems for citizens, including: the clarification of the role of recommender...conference paper 2017
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Arnason, B. (author)The tremendous growth of the Internet brings with it a massive amount of data that users are exposed to on a daily basis. Consequently, information filtering techniques like recommender systems have become increasingly important to sift through the data and find what is relevant to a particular user. A recent approach for recommender systems,...master thesis 2016
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Simes, A. (author)When talking about personalization online, Google CEO Eric Schmidt recently said "it will be very hard for people to watch or consume something that has not in some sense been tailored for them." This level of personalized filtering of content has worried academics and activists. Many argue that users will be trapped in a so-called "Filter...master thesis 2016
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Brojerdyan, M. (author)The supply and demand of the Dutch office market is not in balance. 15,7% of all the offices are vacant. The most vacancy can be found in Amsterdam. Amsterdam is a big city with a large population and a large group of immigrants. There is a shortage of different types of housing, which means that transformation of vacant offices into housing...master thesis 2016
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Shariat Torbaghan, S. (author)The new energy policy of the European Union (EU) with the core objectives of competitiveness, reliability and sustainability, has driven Europe into a transition towards a low carbon & sustainable electricity supply systems. Under the new policy, the European energy systems are pursing two major objectives. First is to shift the focus from...doctoral thesis 2016
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Nateghizad, M. (author), Erkin, Z. (author), Lagendijk, R.L. (author)In smart grids, providing power consumption statistics to the customers and generating recommendations for managing electrical devices are considered to be effective methods that can help to reduce energy consumption. Unfortunately, providing power consumption statistics and generating recommendations rely on highly privacy-sensitive smart...journal article 2016
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Delic, Amra (author), Neidhardt, Julia (author), Nguyen, Thuy-Ngoc (author), Ricci, Francesco (author), Rook, L. (author), Werthner, Hannes (author), Zanker, Markus (author)Most research on group recommender systems relies on the assumption that individuals have conflicting preferences; in order to generate group recommendations the system should identify a fair way of aggregating these preferences. Both empirical studies and theoretical frameworks have tried to identify the most effective preference aggregation...conference paper 2016
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Samar, T. (author), Bellogin, A. (author), De Vries, A.P. (author)The most common approach to measuring the effectiveness of Information Retrieval systems is by using test collections. The Contextual Suggestion (CS) TREC track provides an evaluation framework for systems that recommend items to users given their geographical context. The specific nature of this track allows the participating teams to identify...journal article 2015
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Wafula, J.B. (author)Many software systems are designed to be long-lived due to the costs involved in developing new systems. Changes in these systems are inevitable due to constant modifications in requirements that are necessitated by the constantly changing nature of the business environment or detection of faults.To adapt their software to all these changing...master thesis 2015
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Sen, A. (author)People love listening to music and so do we. Today, music streams are readily available through services such as YouTube, Spotify and Apple Music. The digitization of music has eased the way for users to gain access to large collections of music through the Internet. With all this music around us, it would be expected that music discovery is a...master thesis 2015
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Chandrasekaran Ayyanathan, P.S.N. (author)Since the advent of Web 2.0, users have not only increasingly created content, but also contributed reactions to content in the form of comments. Comments are challenging to analyze due to their short lengths and informal style, meaning that any individual comment provides very little data to work with and is highly variable. However, comments...master thesis 2015
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Claus, J.J.H. (author)This thesis consists of two main parts: Part 1- A qualitative user study of ten interviews, referred to as Study 1, that is addressed in ‘Violins, ovens and hiking shoes: How experience enablers affect people’s subjective well-being in comparison to material- and experiential acquisitions’ Part 2- A quantitative user study of 209 participants...master thesis 2015
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Nagaram, A.R. (author)Social coding platforms can provide initial understanding about the skills exhibited by the developers on these platforms. In contexts where candidates social profile information is useful for recruiting software developers, the information regarding the developers on these platforms can be leveraged by the recruiters with some software...master thesis 2015
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Visser, J.V.G. (author)As the open data movement is growing, more and more data becomes available for developers to be re-used. New applications based on these data are rapidly being developed and can help to solve societal problems. One of these new applications to solve societal problems, is to use energy data to quantitatively help decision makers in the urban...master thesis 2015
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Basak, D. (author)Crowdsourcing and Human computation have enabled industry, and scientists to create innovative solutions by harnessing organized collective human effort. In human computation platforms, it is observed that workers spend a considerable amount of time searching for appropriate tasks, thus losing revenues that they could have made and, ultimately,...master thesis 2014
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Rentmeester, M. (author)Most recommender systems recommend items from a single domain. However, usually users’ preferences span across multiple domains. Cross-domain recommender systems can successfully recommend items in multiple domains when there is knowledge about the user’s preferences for items in at least one of the domains and when there is knowledge about...master thesis 2014