Improving Reachability and Navigability in Recommender Systems

In this paper, we investigate recommender systems from a network perspective and investigate recommendation networks, where nodes are items (e.g., movies) and edges are constructed from top-N recommendations (e.g., related movies). In particular, we focus on evaluating the reachability and navigability of recommendation networks and investigate the following questions: (i) How well do recommendation networks support navigation and exploratory search? (ii) What is the influence of parameters, in particular different recommendation algorithms and the number of recommendations shown, on reachability and navigability? and (iii) How can reachability and navigability be improved in these networks? We tackle these questions by first evaluating the reachability of recommendation networks by investigating their structural properties. Second, we evaluate navigability by simulating three different models of information seeking scenarios. We find that with standard algorithms, recommender systems are not well suited to navigation and exploration and propose methods to modify recommendations to improve this. Our work extends from one-click-based evaluations of recommender systems towards multi-click analysis (i.e., sequences of dependent clicks) and presents a general, comprehensive approach to evaluating navigability of arbitrary recommendation networks

Quantitative analysis of networked environments to improve performance of information systems

In this thesis we encounter networks in three contexts i) as the citation networks between documents in citation databases CiteSeer and DBLP, ii) as the structure of e-government websites that is navigated by users and iii) as the social network of users of a photo-sharing site Flickr and a social networking site Yahoo!360. We study the properties of networks present in real datasets, what are the effects of their structure and how this structure can be exploited. We analyze the citation networks between computer science publications and compare them to those described in Physics community. We also demonstrate the bias of citation databases collected autonomously and present mathematical models of this bias. We then analyze the link structure of three websites extracted by exhaustive crawls. We perform a user study with 134 participants on these websites in an lab. We discuss the structure of the link networks and the performance of subjects in locating information on these websites. We finally exploit the knowledge of users' social network to provide higher quality recommendations than current collaborative filtering techniques and demonstrate the performance benefit on two real datasets.Katedra softwarového inženýrstvíDepartment of Software EngineeringFaculty of Mathematics and PhysicsMatematicko-fyzikální fakult

Performance assessment of an architecture with adaptative interfaces for people with special needs

People in industrial societies carry more and more portable electronic devices (e.g., smartphone or console) with some kind of wireles connectivity support. Interaction with auto-discovered target devices present in the environment (e.g., the air conditioning of a hotel) is not so easy since devices may provide inaccessible user interfaces (e.g., in a foreign language that the user cannot understand). Scalability for multiple concurrent users and response times are still problems in this domain. In this paper, we assess an interoperable architecture, which enables interaction between people with some kind of special need and their environment. The assessment, based on performance patterns and antipatterns, tries to detect performance issues and also tries to enhance the architecture design for improving system performance. As a result of the assessment, the initial design changed substantially. We refactorized the design according to the Fast Path pattern and The Ramp antipattern. Moreover, resources were correctly allocated. Finally, the required response time was fulfilled in all system scenarios. For a specific scenario, response time was reduced from 60 seconds to less than 6 seconds

Social network support for data delivery infrastructures

Network infrastructures often need to stage content so that it is accessible to consumers. The standard solution, deploying the content on a centralised server, can be inadequate in several situations. Our thesis is that information encoded in social networks can be used to tailor content staging decisions to the user base and thereby build better data delivery infrastructures. This claim is supported by two case studies, which apply social information in challenging situations where traditional content staging is infeasible. Our approach works by examining empirical traces to identify relevant social properties, and then exploits them. The first study looks at cost-effectively serving the ``Long Tail'' of rich-media user-generated content, which need to be staged close to viewers to control latency and jitter. Our traces show that a preference for the unpopular tail items often spreads virally and is localised to some part of the social network. Exploiting this, we propose Buzztraq, which decreases replication costs by selectively copying items to locations favoured by viral spread. We also design SpinThrift, which separates popular and unpopular content based on the relative proportion of viral accesses, and opportunistically spins down disks containing unpopular content, thereby saving energy. The second study examines whether human face-to-face contacts can efficiently create paths over time between arbitrary users. Here, content is staged by spreading it through intermediate users until the destination is reached. Flooding every node minimises delivery times but is not scalable. We show that the human contact network is resilient to individual path failures, and for unicast paths, can efficiently approximate flooding in delivery time distribution simply by randomly sampling a handful of paths found by it. Multicast by contained flooding within a community is also efficient. However, connectivity relies on rare contacts and frequent contacts are often not useful for data delivery. Also, periods of similar duration could achieve different levels of connectivity; we devise a test to identify good periods. We finish by discussing how these properties influence routing algorithms.This work was supported by a St. John's College Benefactor's Scholarship and a Research Studentship from the Cambridge Philosophical Society

Design of a Recommender System for Participatory Media Built on a Tetherless Communication Infrastructure

We address the challenge of providing low-cost, universal access of useful information to people in different parts of the globe. We achieve this by following two strategies. First, we focus on the delivery of information through computerized devices and prototype new methods for making that delivery possible in a secure, low-cost, and universal manner. Second, we focus on the use of participatory media, such as blogs, in the context of news related content, and develop methods to recommend useful information that will be of interest to users. To achieve the first goal, we have designed a low-cost wireless system for Internet access in rural areas, and a smartphone-based system for the opportunistic use of WiFi connectivity to reduce the cost of data transfer on multi-NIC mobile devices. Included is a methodology for secure communication using identity based cryptography. For the second goal of identifying useful information, we make use of sociological theories regarding social networks in mass-media to develop a model of how participatory media can offer users effective news-related information. We then use this model to design a recommender system for participatory media content that pushes useful information to people in a personalized fashion. Our algorithms provide an order of magnitude better performance in terms of recommendation accuracy than other state-of-the-art recommender systems. Our work provides some fundamental insights into the design of low-cost communication systems and the provision of useful messages to users in participatory media through a multi-disciplinary approach. The result is a framework that efficiently and effectively delivers information to people in remote corners of the world

Software Perfomance Assessment at Architectural Level: A Methodology and its Application

Las arquitecturas software son una valiosa herramienta para la evaluación de las propiedades cualitativas y cuantitativas de los sistemas en sus primeras fases de desarrollo. Conseguir el diseño adecuado es crítico para asegurar la bondad de dichas propiedades. Tomar decisiones tempranas equivocadas puede implicar considerables y costosos cambios en un futuro. Dichas decisiones afectarían a muchas propiedades del sistema, tales como su rendimiento, seguridad, fiabilidad o facilidad de mantenimiento. Desde el punto de vista del rendimiento software, la ingeniería del rendimiento del software (SPE) es una disciplina de investigación madura y comúnmente aceptada que propone una evaluación basada en modelos en las primeras fases del ciclo de vida de desarrollo software. Un problema en este campo de investigación es que las metodologías hasta ahora propuestas no ofrecen una interpretación de los resultados obtenidos durante el análisis del rendimiento, ni utilizan dichos resultados para proponer alternativas para la mejora de la propia arquitectura software. Hasta la fecha, esta interpretación y mejora requiere de la experiencia y pericia de los ingenieros software, en especial de expertos en ingeniería de prestaciones. Además, a pesar del gran número de propuestas para evaluar el rendimiento de sistemas software, muy pocos de estos estudios teóricos son posteriormente aplicados a sistemas software reales. El objetivo de esta tesis es presentar una metodología para el asesoramiento de decisiones arquitecturales para la mejora, desde el punto de vista de las prestaciones, de las sistemas software. La metodología hace uso del Lenguaje Unificado de Modelado (UML) para representar las arquitecturas software y de métodos formales, concretamente redes de Petri, como modelo de prestaciones. El asesoramiento, basado en patrones y antipatrones, intenta detectar los principales problemas que afectan a las prestaciones del sistema y propone posibles mejoras para mejoras dichas prestaciones. Como primer paso, estudiamos y analizamos los resultados del rendimiento de diferentes estilos arquitectónicos. A continuación, sistematizamos los conocimientos previamente obtenidos para proponer una metodología y comprobamos su aplicabilidad asesorando un caso de estudio real, una arquitectura de interoperabilidad para adaptar interfaces a personas con discapacidad conforme a sus capacidades y preferencias. Finalmente, se presenta una herramienta para la evaluación del rendimiento como un producto derivado del propio ciclo de vida software

Network analysis of shared interests represented by social bookmarking behaviors

Social bookmarking is a new phenomenon characterized by a number of features including active user participation, open and collective discovery of resources, and user-generated metadata. Among others, this study pays particular attention to its nature of being at the intersection of personal information space and social information space. While users of a social bookmarking site create and maintain their own bookmark collections, the users' personal information spaces, in aggregate, build up the information space of the site as a whole. The overall goal of this study is to understand how social information space may emerge when personal information spaces of users intersect and overlap with shared interests. The main purpose of the study is two-fold: first, to see whether and how we can identify shared interest space(s) within the general information space of a social bookmarking site; and second, to evaluate the applicability of social network analysis to this end. Delicious.com, one of the most successful instances of social bookmarking, was chosen as the case. The study was carried out in three phases asking separate yet interrelated questions concerning the overall level of interest overlap, the structural patterns in the network of users connected by shared interests, and the communities of interest within the network. The results indicate that, while individual users of delicious.com have a broad range of diverse interests, there is a considerable level of overlap and commonality, providing a ground for creating implicit networks of users with shared interests. The networks constructed based on common bookmarks revealed intriguing structural patterns commonly found in well-established social systems, including a core periphery structure with a high level of connectivity, which form a basis for efficient information sharing and knowledge transfer. Furthermore, an exploratory analysis of the network communities showed that each community has a distinct theme defining the shared interests of its members, at a high level of coherence. Overall, the results suggest that networks of people with shared interests can be induced from their social bookmarking behaviors and such networks can provide a venue for investigating social mechanisms of information sharing in this new information environment. Future research can be built upon the methods and findings of this study to further explore the implication of the emergent and implicit network of shared interests

Combining SOA and BPM Technologies for Cross-System Process Automation

This paper summarizes the results of an industry case study that introduced a cross-system business process automation solution based on a combination of SOA and BPM standard technologies (i.e., BPMN, BPEL, WSDL). Besides discussing major weaknesses of the existing, custom-built, solution and comparing them against experiences with the developed prototype, the paper presents a course of action for transforming the current solution into the proposed solution. This includes a general approach, consisting of four distinct steps, as well as specific action items that are to be performed for every step. The discussion also covers language and tool support and challenges arising from the transformation