911 resultados para 1145
Resumo:
A common problem with the use of tensor modeling in generating quality recommendations for large datasets is scalability. In this paper, we propose the Tensor-based Recommendation using Probabilistic Ranking method that generates the reconstructed tensor using block-striped parallel matrix multiplication and then probabilistically calculates the preferences of user to rank the recommended items. Empirical analysis on two real-world datasets shows that the proposed method is scalable for large tensor datasets and is able to outperform the benchmarking methods in terms of accuracy.
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In the TREC Web Diversity track, novelty-biased cumulative gain (α-NDCG) is one of the official measures to assess retrieval performance of IR systems. The measure is characterised by a parameter, α, the effect of which has not been thoroughly investigated. We find that common settings of α, i.e. α=0.5, may prevent the measure from behaving as desired when evaluating result diversification. This is because it excessively penalises systems that cover many intents while it rewards those that redundantly cover only few intents. This issue is crucial since it highly influences systems at top ranks. We revisit our previously proposed threshold, suggesting α be set on a query-basis. The intuitiveness of the measure is then studied by examining actual rankings from TREC 09-10 Web track submissions. By varying α according to our query-based threshold, the discriminative power of α-NDCG is not harmed and in fact, our approach improves α-NDCG's robustness. Experimental results show that the threshold for α can turn the measure to be more intuitive than using its common settings.
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INEX investigates focused retrieval from structured documents by providing large test collections of structured documents, uniform evaluation measures, and a forum for organizations to compare their results. This paper reports on the INEX 2008 evaluation campaign, which consisted of a wide range of tracks: Ad hoc, Book, Efficiency, Entity Ranking, Interactive, QA, Link the Wiki, and XML Mining.
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In this paper we describe the preliminary results of a field study which evaluated the use of MiniOrb, a system that employs ambient and tangible interaction mechanisms to allow inhabitants of office environments to report on subjectively perceived office comfort levels. The purpose of this study was to explore the role of ubiquitous computing in the individual control of indoor climate and specifically answer the question to what extent ambient and tangible interaction mechanisms are suited for the task of capturing individual comfort preferences in a non-obtrusive manner. We outline the preliminary results of an in-situ trial of the system.
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This research proposes the development of interfaces to support collaborative, community-driven inquiry into data, which we refer to as Participatory Data Analytics. Since the investigation is led by local communities, it is not possible to anticipate which data will be relevant and what questions are going to be asked. Therefore, users have to be able to construct and tailor visualisations to their own needs. The poster presents early work towards defining a suitable compositional model, which will allow users to mix, match, and manipulate data sets to obtain visual representations with little-to-no programming knowledge. Following a user-centred design process, we are subsequently planning to identify appropriate interaction techniques and metaphors for generating such visual specifications on wall-sized, multi-touch displays.
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Web servers are accessible by anyone who can access the Internet. Although this universal accessibility is attractive for all kinds of Web-based applications, Web servers are exposed to attackers who may want to alter their contents. Alterations range from humorous additions or changes, which are typically easy to spot, to more sinister tampering, such as providing false or damaging information.
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In this paper we contribute to the growing body of research into the use and design of technology in the kitchen. This research aims to identify opportunities for designing technologies that may augment existing cooking traditions and in particular familial recipe sharing practices. Using ethnographic techniques, we identify the homemade cookbook as a significant material and cultural artifact in the family kitchen. We report on findings from our study by providing descriptive accounts of various homemade cookbooks, and offer design considerations for digitally augmenting homemade cookbooks.
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We explore relationships between habits and technology interaction by reporting on older people's experience of the Kinect for Xbox. We contribute to theoretical and empirical understandings of habits in the use of technology to inform understanding of the habitual qualities of our interactions with computing technologies, particularly systems exploiting natural user interfaces. We situate ideas of habit in relation to user experience and usefulness in interaction design, and draw on critical approaches to the concept of habit from cultural theory to understand the embedded, embodied, and situated contexts in our interactions with technologies. We argue that understanding technology habits as a process of reciprocal habituation in which people and technologies adapt to each other over time through design, adoption, and appropriation offers opportunities for research on user experience and interaction design within human-computer interaction, especially as newer gestural and motion control interfaces promise to reshape the ways in which we interact with computers.
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Citizen science projects have demonstrated the advantages of people with limited relevant prior knowledge participating in research. However, there is a difference between engaging the general public in a scientific project and entering an established expert community to conduct research. This paper describes our ongoing acoustic biodiversity monitoring collaborations with the bird watching community. We report on findings gathered over six years from participation in bird walks, observing conservation efforts, and records of personal activities of experienced birders. We offer an empirical study into extending existing protocols through in-context collaborative design involving scientists and domain experts.
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The common reasons for those in organizations adopting large config- urable packaged software products are compelling. Problems with the existing software situation, the supposed predictability and perceived business benefits of packaged software, and various social influences, can lead to packages being preferred to custom approaches. Yet, for every reason, there is a potential associated problem that must be understood before an informed adoption decision can be made...
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Mitigating domestic food waste reduces its environmental and economic impacts. In our study, we have identified the use of mobile technology to support behaviour change as a key tool to assist the process of reducing food waste. This paper reports on three mobile applications designed to reduce domestic food waste: Fridge Pal, LeftoverSwap and EatChaFood. The paper examines how each app can influence consumer knowledge of domestic food supply, location, and literacy. We discuss our findings with respect to three considerations: (i) assisting with the user’s food supply and location knowledge; (ii) improving the user’s food literacy; (iii) facilitating social food sharing of excess food. We present new insights for mobile interventions that encourage changes towards more sustainable behaviours to reduce food waste.
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Young males are over-represented in road crashes. Part of the problem is their proneness to boredom, a hardwired personality factor that can lead to risky driving. This paper presents a theoretical understanding of boredom in the driving context and demonstrates convincing arguments to investigate the role of boredom further. Specifically, this paper calls for the design of innovative technologies and applications that make safe driving more pleasurable and stimulating for young males, e.g., by applying gamification techniques. We propose two design concepts through the following questions: A. Can the simulation of risky driving reduce actual risky driving? B. Can the replacement of risky driving stimuli with alternative stimuli reduce risky driving? We argue that considering these questions in the future design of automotive user-interfaces and personal ubiquitous computing devices could effectively reduce risky driving behaviours among young males.
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This research draws on theories of emergence to inform the creation of an artistic and direct visualization. This is an interactive artwork and drawing tool for creative participant experiences. As is discussed, emergence is characteristically creative. It is also debated across and within disciplines, resulting in a range of understandings as well as models. This paper shows how one field’s understanding of emergence (complexity theory) can be used to facilitate emergence in another domain (design research) and, importantly provide the opportunity for someone to act creatively. This paper begins with a brief review of some theories of emergence to show how they interrelate and can effect the perception of emergent structures in an observer, and, correspondingly, the design for creative experience. This is subsequently demonstrated in the second section of the paper where an interactive artwork and drawing application, Of me with me, is presented. This artwork by the author was created during collaboration with community artists from Cerebral Palsy League. The discussion covers the application of emergence theories to create this visualization in order facilitate the perception of structures and creative behaviours in a participant and to facilitate self-efficacy in the community artist user group.
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Many websites offer the opportunity for customers to rate items and then use customers' ratings to generate items reputation, which can be used later by other users for decision making purposes. The aggregated value of the ratings per item represents the reputation of this item. The accuracy of the reputation scores is important as it is used to rank items. Most of the aggregation methods didn't consider the frequency of distinct ratings and they didn't test how accurate their reputation scores over different datasets with different sparsity. In this work we propose a new aggregation method which can be described as a weighted average, where weights are generated using the normal distribution. The evaluation result shows that the proposed method outperforms state-of-the-art methods over different sparsity datasets.
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Twitter is a very popular social network website that allows users to publish short posts called tweets. Users in Twitter can follow other users, called followees. A user can see the posts of his followees on his Twitter profile home page. An information overload problem arose, with the increase of the number of followees, related to the number of tweets available in the user page. Twitter, similar to other social network websites, attempts to elevate the tweets the user is expected to be interested in to increase overall user engagement. However, Twitter still uses the chronological order to rank the tweets. The tweets ranking problem was addressed in many current researches. A sub-problem of this problem is to rank the tweets for a single followee. In this paper we represent the tweets using several features and then we propose to use a weighted version of the famous voting system Borda-Count (BC) to combine several ranked lists into one. A gradient descent method and collaborative filtering method are employed to learn the optimal weights. We also employ the Baldwin voting system for blending features (or predictors). Finally we use the greedy feature selection algorithm to select the best combination of features to ensure the best results.