@article{Hegenberg2015, author = {Hegenberg, J. and Herrmann, R. and Ziegner, D. and Schmidt, L. and Guenther, T. and Müller, A. O. and Kroll, A. and Barz, T. and Schulz, D.}, interhash = {b8fdce7b4127794de827775e464ceff4}, intrahash = {df4a4f970a86b6374bd9ef6931b8b224}, journal = {Technische Sicherheit}, language = {deutsch}, month = {Mai}, mrtnote = {peer, robotair,pke}, number = 5, owner = {duerrbaum}, pages = {16-22}, title = {Forschungsprojekt RobotAir: Praxistaugliches Boden-Luft-Servicerobotersystem für die Inspektion industrieller Druckluftversorgung und die Verbesserung der Arbeitsumgebungsfaktoren}, volume = 5, year = 2015 } @article{Hegenberg2015, author = {Hegenberg, J. and Herrmann, R. and Ziegner, D. and Schmidt, L. and Guenther, T. and Müller, A. O. and Kroll, A. and Barz, T. and Schulz, D.}, interhash = {b8fdce7b4127794de827775e464ceff4}, intrahash = {df4a4f970a86b6374bd9ef6931b8b224}, journal = {Technische Sicherheit}, language = {deutsch}, month = {Mai}, mrtnote = {peer, robotair,pke}, number = 5, owner = {duerrbaum}, pages = {16-22}, title = {Forschungsprojekt RobotAir: Praxistaugliches Boden-Luft-Servicerobotersystem für die Inspektion industrieller Druckluftversorgung und die Verbesserung der Arbeitsumgebungsfaktoren}, volume = 5, year = 2015 } @book{balbymarinho2012recommender, abstract = {Social Tagging Systems are web applications in which users upload resources (e.g., bookmarks, videos, photos, etc.) and annotate it with a list of freely chosen keywords called tags. This is a grassroots approach to organize a site and help users to find the resources they are interested in. Social tagging systems are open and inherently social; features that have been proven to encourage participation. However, with the large popularity of these systems and the increasing amount of user-contributed content, information overload rapidly becomes an issue. Recommender Systems are well known applications for increasing the level of relevant content over the “noise” that continuously grows as more and more content becomes available online. In social tagging systems, however, we face new challenges. While in classic recommender systems the mode of recommendation is basically the resource, in social tagging systems there are three possible modes of recommendation: users, resources, or tags. Therefore suitable methods that properly exploit the different dimensions of social tagging systems data are needed. In this book, we survey the most recent and state-of-the-art work about a whole new generation of recommender systems built to serve social tagging systems. The book is divided into self-contained chapters covering the background material on social tagging systems and recommender systems to the more advanced techniques like the ones based on tensor factorization and graph-based models.}, author = {Balby Marinho, L. and Hotho, A. and Jäschke, R. and Nanopoulos, A. and Rendle, S. and Schmidt-Thieme, L. and Stumme, G. and Symeonidis, P.}, doi = {10.1007/978-1-4614-1894-8}, interhash = {0bb7f0588cd690d67cc73e219a3a24fa}, intrahash = {87d6883ebd98e8810be45d7e7e4ade96}, isbn = {978-1-4614-1893-1}, month = feb, publisher = {Springer}, series = {SpringerBriefs in Electrical and Computer Engineering}, title = {Recommender Systems for Social Tagging Systems}, url = {http://link.springer.com/book/10.1007/978-1-4614-1894-8}, year = 2012 } @book{balbymarinho2012recommender, abstract = {Social Tagging Systems are web applications in which users upload resources (e.g., bookmarks, videos, photos, etc.) and annotate it with a list of freely chosen keywords called tags. This is a grassroots approach to organize a site and help users to find the resources they are interested in. Social tagging systems are open and inherently social; features that have been proven to encourage participation. However, with the large popularity of these systems and the increasing amount of user-contributed content, information overload rapidly becomes an issue. Recommender Systems are well known applications for increasing the level of relevant content over the “noise” that continuously grows as more and more content becomes available online. In social tagging systems, however, we face new challenges. While in classic recommender systems the mode of recommendation is basically the resource, in social tagging systems there are three possible modes of recommendation: users, resources, or tags. Therefore suitable methods that properly exploit the different dimensions of social tagging systems data are needed. In this book, we survey the most recent and state-of-the-art work about a whole new generation of recommender systems built to serve social tagging systems. The book is divided into self-contained chapters covering the background material on social tagging systems and recommender systems to the more advanced techniques like the ones based on tensor factorization and graph-based models.}, author = {Balby Marinho, L. and Hotho, A. and Jäschke, R. and Nanopoulos, A. and Rendle, S. and Schmidt-Thieme, L. and Stumme, G. and Symeonidis, P.}, doi = {10.1007/978-1-4614-1894-8}, interhash = {0bb7f0588cd690d67cc73e219a3a24fa}, intrahash = {87d6883ebd98e8810be45d7e7e4ade96}, isbn = {978-1-4614-1893-1}, month = feb, publisher = {Springer}, series = {SpringerBriefs in Electrical and Computer Engineering}, title = {Recommender Systems for Social Tagging Systems}, url = {http://link.springer.com/book/10.1007/978-1-4614-1894-8}, year = 2012 } @inproceedings{ls_leimeister, address = {Berlin, Germany}, author = {Heußner, M. and Ackermann, L. and Widy, O. and Schmidt, L. and Pippert, M. and Bienhaus, D. and Durward, D. and Prinz, A. and Wegener, R. and Leimeister, J.M.}, booktitle = {6. Deutscher AAL-Kongress 2013 - Themenschwerpunkt: AAL in der gesundheitlichen Versorgungskette: Zuhause – Unterwegs – im Krankenhaus – in der Reha – in der Pflege – im Hospiz }, interhash = {45c5b8b92b496a3d98a94c5266fc3ca9}, intrahash = {59b6c12fb12fa66f7b8ff066e04f9fdd}, note = 367, title = {AAL-Weiterbildung für Pflege und Handwerk: erste Ergebnisse einer Anforderungsanalyse}, year = 2013 } @book{balbymarinho2012recommender, abstract = {Social Tagging Systems are web applications in which users upload resources (e.g., bookmarks, videos, photos, etc.) and annotate it with a list of freely chosen keywords called tags. This is a grassroots approach to organize a site and help users to find the resources they are interested in. Social tagging systems are open and inherently social; features that have been proven to encourage participation. However, with the large popularity of these systems and the increasing amount of user-contributed content, information overload rapidly becomes an issue. Recommender Systems are well known applications for increasing the level of relevant content over the “noise” that continuously grows as more and more content becomes available online. In social tagging systems, however, we face new challenges. While in classic recommender systems the mode of recommendation is basically the resource, in social tagging systems there are three possible modes of recommendation: users, resources, or tags. Therefore suitable methods that properly exploit the different dimensions of social tagging systems data are needed. In this book, we survey the most recent and state-of-the-art work about a whole new generation of recommender systems built to serve social tagging systems. The book is divided into self-contained chapters covering the background material on social tagging systems and recommender systems to the more advanced techniques like the ones based on tensor factorization and graph-based models.}, author = {Balby Marinho, L. and Hotho, A. and Jäschke, R. and Nanopoulos, A. and Rendle, S. and Schmidt-Thieme, L. and Stumme, G. and Symeonidis, P.}, interhash = {0bb7f0588cd690d67cc73e219a3a24fa}, intrahash = {87d6883ebd98e8810be45d7e7e4ade96}, isbn = {978-1-4614-1893-1}, month = feb, publisher = {Springer}, series = {SpringerBriefs in Electrical and Computer Engineering}, title = {Recommender Systems for Social Tagging Systems}, url = {http://www.springer.com/computer/database+management+%26+information+retrieval/book/978-1-4614-1893-1}, year = 2012 } @book{balbymarinho2012recommender, abstract = {Social Tagging Systems are web applications in which users upload resources (e.g., bookmarks, videos, photos, etc.) and annotate it with a list of freely chosen keywords called tags. This is a grassroots approach to organize a site and help users to find the resources they are interested in. Social tagging systems are open and inherently social; features that have been proven to encourage participation. However, with the large popularity of these systems and the increasing amount of user-contributed content, information overload rapidly becomes an issue. Recommender Systems are well known applications for increasing the level of relevant content over the “noise” that continuously grows as more and more content becomes available online. In social tagging systems, however, we face new challenges. While in classic recommender systems the mode of recommendation is basically the resource, in social tagging systems there are three possible modes of recommendation: users, resources, or tags. Therefore suitable methods that properly exploit the different dimensions of social tagging systems data are needed. In this book, we survey the most recent and state-of-the-art work about a whole new generation of recommender systems built to serve social tagging systems. The book is divided into self-contained chapters covering the background material on social tagging systems and recommender systems to the more advanced techniques like the ones based on tensor factorization and graph-based models.}, author = {Balby Marinho, L. and Hotho, A. and Jäschke, R. and Nanopoulos, A. and Rendle, S. and Schmidt-Thieme, L. and Stumme, G. and Symeonidis, P.}, doi = {10.1007/978-1-4614-1894-8}, interhash = {0bb7f0588cd690d67cc73e219a3a24fa}, intrahash = {87d6883ebd98e8810be45d7e7e4ade96}, isbn = {978-1-4614-1893-1}, month = feb, publisher = {Springer}, series = {SpringerBriefs in Electrical and Computer Engineering}, title = {Recommender Systems for Social Tagging Systems}, url = {http://link.springer.com/book/10.1007/978-1-4614-1894-8}, year = 2012 } @inproceedings{Domhardt.2009, abstract = {Neuartige Spielesteuerungen, die auf dem Prinzip eines Brain-Computer Interface basieren, können möglicherweise auch für andere Computeranwendungen sinnvoll genutzt werden. Der Beitrag stellt ein solches Eingabegerät und die Ergebnisse eines ersten Usabilitytests vor.}, address = {Dortmund}, author = {Domhardt, M. and Schmidt, L.}, booktitle = {Arbeit, Beschäftigungsfähigkeit und Produktivität im 21. Jahrhundert}, editor = {{Gesellschaft für Arbeitswissenschaft e. V.}}, interhash = {fa106689a2aa47f0409868cbe93f8a55}, intrahash = {f9bbb40f03198bfcdcd5213a643e01ca}, isbn = {9783936804079}, pages = {105-108}, publisher = {GfA-Press}, title = {Brain-Computer-Interface: Von der Spielesteuerung zur Mensch-Computer-Interaktion?}, year = 2009 } @inproceedings{Hoberg.2010, abstract = {In diesem Beitrag wird die Evaluation der Gebrauchstauglichkeit und Vernetzungswirkung der prototypisch umgesetzten mobilen sozialen Software Social Link mittels einer adaptierten Heuristischen Evaluation beschrieben. Social Link unterstützt seine Anwender dabei, Informationen über sich, den eigenen Standpunkt und das vorherrschende Wetter an Mitglieder einer Peer Group zu verschicken. Für die Evaluation wurden Nielsens Web-Heuristiken für die Anwendung auf mobile soziale Applikationen angepasst. Die Software wurde von sechs Evaluatoren bewertet und Optimierungsvorschläge für die Weiterentwicklung von Social Link generiert.}, address = {Düsseldorf}, author = {Hoberg, S. and Kniewel, R. and Behrenbruch, K. and Schmidt, L. and Pirali, A. and David, K.}, booktitle = {Useware 2010}, editor = {{VDI/VDE-Gesellschaft Mess- und Automatisierungstechnik}}, interhash = {8d6192b685855ea4af3e4fcfb4d9c4a8}, intrahash = {316cd63c877ae24ef26b2cd6dc4406ab}, isbn = {9783180920993}, pages = {129-138}, publisher = {VDI}, series = {VDI-Berichte}, title = {Adaptierte Heuristische Evaluation einer neuartigen sozialen Software}, volume = 2099, year = 2010 } @incollection{Schmidt.2008c, abstract = {In der Abteilung Ergonomie und Führungssysteme des FGAN Forschungsinstituts für Kommunikation, Informationsverarbeitung und Ergonomie werden Konzepte, Methoden und Werkzeuge zur benutzerzentrierten Gestaltung von Führungs- und Führungsinformationssystemen erforscht, entwickelt und angewandt. Ziel ist die Bereitstellung der erforderlichen wissenschaftlichen und technologischen Basis für ergonomisch zweckmäßige Ausrüstungsentscheidungen im Verfahren der Bedarfsermittlung und Bedarfsdeckung. Aufbauend auf ergonomischen Anforderungsanalysen werden innovative Mensch-Maschine-Schnittstellen konzipiert, in Form von Prototypen realisiert und hinsichtlich ihrer nutzergerechten Gestaltung in Feld- und Laborstudien evaluiert. Diese methodische Herangehensweise und die verschiedenen, thematisch abgegrenzten Forschungsfelder der Abteilung werden im Folgenden im Überblick dargestellt.}, address = {Berlin}, author = {Schmidt, L.}, booktitle = {Ergonomie und Mensch-Maschine-Systeme}, editor = {Schmidt, L. and Schlick, C. M. and Grosche, J.}, interhash = {bb2b76e58d281d0ebb59826bd047e453}, intrahash = {6a9965eef9c6ba186eba354a0005b058}, isbn = {9783540783305}, pages = {67-78}, publisher = {Springer}, title = {Ergonomie und Führungssysteme}, year = 2008 }