796 resultados para User-based collaborative filtering


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In this paper a computer program to model and support product design is presented. The product is represented through a hierarchical structure that allows the user to navigate across the product’s components, and it aims at facilitating each step of the detail design process. A graphical interface was also developed, which shows visually to the user the contents of the product structure. Features are used as building blocks for the parts that compose the product, and object-oriented methodology was used as a means to implement the product structure. Finally, an expert system was also implemented, whose knowledge base rules help the user design a product that meets design and manufacturing requirements.

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This study concerns performance measurement and management in a collaborative network. Collaboration between companies has been increased in recent years due to the turbulent operating environment. The literature shows that there is a need for more comprehensive research on performance measurement in networks and the use of measurement information in their management. This study examines the development process and uses of a performance measurement system supporting performance management in a collaborative network. There are two main research questions: how to design a performance measurement system for a collaborative network and how to manage performance in a collaborative network. The work can be characterised as a qualitative single case study. The empirical data was collected in a Finnish collaborative network, which consists of a leading company and a reseller network. The work is based on five research articles applying various research methods. The research questions are examined at the network level and at the single network partner level. The study contributes to the earlier literature by producing new and deeper understanding of network-level performance measurement and management. A three-step process model is presented to support the performance measurement system design process. The process model has been tested in another collaborative network. The study also examines the factors affecting the process of designing the measurement system. The results show that a participatory development style, network culture, and outside facilitators have a positive effect on the design process. The study increases understanding of how to manage performance in a collaborative network and what kind of uses of performance information can be identified in a collaborative network. The results show that the performance measurement system is an applicable tool to manage the performance of a network. The results reveal that trust and openness increased during the utilisation of the performance measurement system, and operations became more transparent. The study also presents a management model that evaluates the maturity of performance management in a collaborative network. The model is a practical tool that helps to analyse the current stage of the performance management of a collaborative network and to develop it further.

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Software plays an important role in our society and economy. Software development is an intricate process, and it comprises many different tasks: gathering requirements, designing new solutions that fulfill these requirements, as well as implementing these designs using a programming language into a working system. As a consequence, the development of high quality software is a core problem in software engineering. This thesis focuses on the validation of software designs. The issue of the analysis of designs is of great importance, since errors originating from designs may appear in the final system. It is considered economical to rectify the problems as early in the software development process as possible. Practitioners often create and visualize designs using modeling languages, one of the more popular being the Uni ed Modeling Language (UML). The analysis of the designs can be done manually, but in case of large systems, the need of mechanisms that automatically analyze these designs arises. In this thesis, we propose an automatic approach to analyze UML based designs using logic reasoners. This approach firstly proposes the translations of the UML based designs into a language understandable by reasoners in the form of logic facts, and secondly shows how to use the logic reasoners to infer the logical consequences of these logic facts. We have implemented the proposed translations in the form of a tool that can be used with any standard compliant UML modeling tool. Moreover, we authenticate the proposed approach by automatically validating hundreds of UML based designs that consist of thousands of model elements available in an online model repository. The proposed approach is limited in scope, but is fully automatic and does not require any expertise of logic languages from the user. We exemplify the proposed approach with two applications, which include the validation of domain specific languages and the validation of web service interfaces.

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In the beginning of its 10th year of existence Facebook has engaged and connected 1.2 billion monthly active users. This article-based dissertation Disconnect.Me – User Engagement and Facebook approaches this engagement from the opposite direction: disconnection. The research articles focus on social media specific phenomena including leaving Facebook, tactical media works such as Web 2.0 SuicideMachine, memorializing dead Facebook users and Facebook trolling. The media theoretical framework for this study is built around affect theory, software studies, biopolitics as well as different critical studies of new media. The argument is that disconnection is a necessary condition of social media connectivity and exploring social media through disconnection – as an empirical phenomenon, future potential and theoretical notion – helps us to understand how users are engaged with social media, its uses and subsequent business models. The results of the study indicate that engagement is a relation that precedes user participation, a notion often used to conceptualize social media. Furthermore, this engagement turns the focus from users’ actions towards the platform and how the platform actively controls users and their behavior. Facebook aims to engage new users and maintain the old ones by renewing its platform and user interface. User engagement with the platform is thus social but also technical and affective. When engaged, the user is positioned to algorithmic connectivity where machinc processes mine user data. This data is but sold also used to affect and engage other users. In the heart of this study is the notion that our networked engagements matter and disconnection can bring us to the current limits of network culture.

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This study is a qualitative action research by its nature with elements of personal design in the form of a tangible model implementation framework construction. Utilized empirical data has been gathered via two questionnaires in relation to the arranged four workshop events with twelve individual participants. Five of them represented maintenance customers, three maintenance service providers and four equipment providers respectively. Further, there are two main research objectives in proportion to the two complementary focusing areas of this thesis. Firstly, the value-based life-cycle model, which first version has already been developed prior to this thesis, requires updating in order to increase its real-life applicability as an inter-firm decision-making tool in industrial maintenance. This first research objective is fulfilled by improving appearance, intelligibility and usability of the above-mentioned model. In addition, certain new features are also added. The workshop participants from the collaborating companies were reasonably pleased with made changes, although further attention will be required in future on the model’s intelligibility in particular as main results, charts and values were all reckoned as slightly hard to understand. Moreover, upgraded model’s appearance and added new features satisfied them the most. Secondly and more importantly, the premises of the model’s possible inter-firm implementation process need to be considered. This second research objective is delivered in two consecutive steps. At first, a bipartite open-books supported implementation framework is created and its different characteristics discussed in theory. Afterwards, the prerequisites and the pitfalls of increasing inter-organizational information transparency are studied in empirical context. One of the main findings was that the organizations are not yet prepared for network-wide information disclosure as dyadic collaboration was favored instead. However, they would be willing to share information bilaterally at least. Another major result was that the present state of companies’ cost accounting systems will definitely need implementation-wise enhancing in future since accurate and sufficiently detailed maintenance data is not available. Further, it will also be crucial to create supporting and mutually agreed network infrastructure. There are hardly any collaborative models, methods or tools currently in usage. Lastly, the essential questions about mutual trust and predominant purchasing strategies are cooperation-wise important. If inter-organizational activities are expanded, a more relational approach should be favored in this regard. Mutual trust was also recognized as a significant cooperation factor, but it is hard to measure in reality.

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End-user development is a very common but often largely overlooked phenomenon in information systems research and practice. End-user development means that regular people, the end-users of software, and not professional developers are doing software development. A large number of people are directly or indirectly impacted by the results of these non-professional development activities. The numbers of users performing end-user development activities are difficult to ascertain precisely. But it is very large, and still growing. Computer adoption is growing towards 100% and many new types of computational devices are continually introduced. In addition, other devices not previously programmable are becoming so. This means that, at this very moment, hundreds of millions of people are likely struggling with development problems. Furthermore, software itself is continually being adapted for more flexibility, enabling users to change the behaviour of their software themselves. New software and services are helping to transform users from consumers to producers. Much of this is now found on-line. The problem for the end-user developer is that little of this development is supported by anyone. Often organisations do not notice end-user development and consequently neither provide support for it, nor are equipped to be able to do so. Many end-user developers do not belong to any organisation at all. Also, the end-user development process may be aggravating the problem. End-users are usually not really committed to the development process, which tends to be more iterative and ad hoc. This means support becomes a distant third behind getting the job done and figuring out the development issues to get the job done. Sometimes the software itself may exacerbate the issue by simplifying the development process, deemphasising the difficulty of the task being undertaken. On-line support could be the lifeline the end-user developer needs. Going online one can find all the knowledge one could ever need. However, that does still not help the end-user apply this information or knowledge in practice. A virtual community, through its ability to adopt the end-user’s specific context, could surmount this final obstacle. This thesis explores the concept of end-user development and how it could be supported through on-line sources, in particular virtual communities, which it is argued here, seem to fit the end-user developer’s needs very well. The experiences of real end-user developers and prior literature were used in this process. Emphasis has been on those end-user developers, e.g. small business owners, who may have literally nowhere to turn to for support. Adopting the viewpoint of the end-user developer, the thesis examines the question of how an end-user could use a virtual community effectively, improving the results of the support process. Assuming the common situation where the demand for support outstrips the supply.

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Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

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Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

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Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

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Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

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Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

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This thesis is concerned with the state and parameter estimation in state space models. The estimation of states and parameters is an important task when mathematical modeling is applied to many different application areas such as the global positioning systems, target tracking, navigation, brain imaging, spread of infectious diseases, biological processes, telecommunications, audio signal processing, stochastic optimal control, machine learning, and physical systems. In Bayesian settings, the estimation of states or parameters amounts to computation of the posterior probability density function. Except for a very restricted number of models, it is impossible to compute this density function in a closed form. Hence, we need approximation methods. A state estimation problem involves estimating the states (latent variables) that are not directly observed in the output of the system. In this thesis, we use the Kalman filter, extended Kalman filter, Gauss–Hermite filters, and particle filters to estimate the states based on available measurements. Among these filters, particle filters are numerical methods for approximating the filtering distributions of non-linear non-Gaussian state space models via Monte Carlo. The performance of a particle filter heavily depends on the chosen importance distribution. For instance, inappropriate choice of the importance distribution can lead to the failure of convergence of the particle filter algorithm. In this thesis, we analyze the theoretical Lᵖ particle filter convergence with general importance distributions, where p ≥2 is an integer. A parameter estimation problem is considered with inferring the model parameters from measurements. For high-dimensional complex models, estimation of parameters can be done by Markov chain Monte Carlo (MCMC) methods. In its operation, the MCMC method requires the unnormalized posterior distribution of the parameters and a proposal distribution. In this thesis, we show how the posterior density function of the parameters of a state space model can be computed by filtering based methods, where the states are integrated out. This type of computation is then applied to estimate parameters of stochastic differential equations. Furthermore, we compute the partial derivatives of the log-posterior density function and use the hybrid Monte Carlo and scaled conjugate gradient methods to infer the parameters of stochastic differential equations. The computational efficiency of MCMC methods is highly depend on the chosen proposal distribution. A commonly used proposal distribution is Gaussian. In this kind of proposal, the covariance matrix must be well tuned. To tune it, adaptive MCMC methods can be used. In this thesis, we propose a new way of updating the covariance matrix using the variational Bayesian adaptive Kalman filter algorithm.

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Several companies are trying to improve their operation efficiency by implementing an enterprise resource planning (ERP) system that makes it possible to control the resources of the company in real time. However, the success of the implementation project is not a foregone conclusion; a significant part of these projects end in a failure, one way or another. Therefore it is important to investigate ERP system implementation more closely in order to increase understanding about factors influencing ERP system success and to improve the probability of a successful ERP implementation project. Consequently, this study was initiated because a manufacturing case company wanted to review the success of their ERP implementation project. To be exact, the case company hoped to gain both information about the success of the project and insight for future implementation improvement. This study investigated ERP success specifically by examining factors that influence ERP key-user satisfaction. User satisfaction is one of the most commonly applied indicators of information system success. The research data was mainly collected by conducting theme interviews. The subjects of the interviews were six key-users of the newly implemented ERP system. The interviewees were closely involved in the implementation project. Furthermore, they act as representative users that utilize the new system in everyday business processes. The collected data was analyzed by thematizing. Both data collection and analysis were guided by a theoretical frame of reference. This frame was based on previous research on the subject. The results of the study aligned with the theoretical framework to large extent. The four principal factors influencing key-user satisfaction were change management, contractor service, key-user’s system knowledge and characteristics of the ERP product itself. One of the most significant contributions of the research is that it confirmed the existence of a connection between change management and ERP key-user satisfaction. Furthermore, it discovered two new sub-factors influencing contractor service related key-user satisfaction. In addition, the research findings indicated that in order to improve the current level of key-user satisfaction, the case company should pay special attention to system functionality improvement and enhancement of the key-users’ knowledge. During similar implementation projects in the future, it would be important to assure the success of change management and contractor service related processes.

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Advances in technology have provided new ways of using entertainment and game technology to foster human interaction. Games and playing with games have always been an important part of people’s everyday lives. Traditionally, human-computer interaction (HCI) research was seen as a psychological cognitive science focused on human factors, with engineering sciences as the computer science part of it. Although cognitive science has made significant progress over the past decade, the influence of people’s emotions on design networks is increasingly important, especially when the primary goal is to challenge and entertain users (Norman 2002). Game developers have explored the key issues in game design and identified that the driving force in the success of games is user experience. User-centered design integrates knowledge of users’ activity practices, needs, and preferences into the design process. Geocaching is a location-based treasure hunt game created by a community of players. Players use GPS (Global Position System) technology to find “treasures” and create their own geocaches; the game can be developed when the players invent caches and used more imagination to creations the caches. This doctoral dissertation explores user experience of geocaching and its applications in tourism and education. Globally, based on the Geocaching.com webpage, geocaching has been played about 180 countries and there are more than 10 million registered geocachers worldwide (Geocaching.com, 25.11.2014). This dissertation develops and presents an interaction model called the GameFlow Experience model that can be used to support the design of treasure hunt applications in tourism and education contexts. The GameFlow Model presents and clarifies various experiences; it provides such experiences in a real-life context, offers desirable design targets to be utilized in service design, and offers a perspective to consider when evaluating the success of adventure game concepts. User-centered game designs have adapted to human factor research in mainstream computing science. For many years, the user-centered design approach has been the most important research field in software development. Research has been focusing on user-centered design in software development such as office programs, but the same ideas and theories that will reflect the needs of a user-centered research are now also being applied to game design (Charles et al. 2005.) For several years, we have seen a growing interest in user experience design. Digital games are experience providers, and game developers need tools to better understand the user experience related to products and services they have created. This thesis aims to present what the user experience is in geocaching and treasure hunt games and how it can be used to develop new concepts for the treasure hunt. Engineers, designers, and researchers should have a clear understanding of what user experience is, what its parts are, and most importantly, how we can influence user satisfaction. In addition, we need to understand how users interact with electronic products and people, and how different elements synergize their experiences. This doctoral dissertation represents pioneering work on the user experience of geocaching and treasure hunt games in the context of tourism and education. The research also provides a model for game developers who are planning treasure hunt concepts.

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Motivated by a recently proposed biologically inspired face recognition approach, we investigated the relation between human behavior and a computational model based on Fourier-Bessel (FB) spatial patterns. We measured human recognition performance of FB filtered face images using an 8-alternative forced-choice method. Test stimuli were generated by converting the images from the spatial to the FB domain, filtering the resulting coefficients with a band-pass filter, and finally taking the inverse FB transformation of the filtered coefficients. The performance of the computational models was tested using a simulation of the psychophysical experiment. In the FB model, face images were first filtered by simulated V1- type neurons and later analyzed globally for their content of FB components. In general, there was a higher human contrast sensitivity to radially than to angularly filtered images, but both functions peaked at the 11.3-16 frequency interval. The FB-based model presented similar behavior with regard to peak position and relative sensitivity, but had a wider frequency band width and a narrower response range. The response pattern of two alternative models, based on local FB analysis and on raw luminance, strongly diverged from the human behavior patterns. These results suggest that human performance can be constrained by the type of information conveyed by polar patterns, and consequently that humans might use FB-like spatial patterns in face processing.