TY - JOUR A1 - Meinel, Christoph A1 - Klotz, Volker T1 - The first 10 years of the ECCC digital library Y1 - 2006 UR - http://portal.acm.org/cacm U6 - https://doi.org/10.1145/1107458.1107484 ER - TY - JOUR A1 - Meinel, Christoph A1 - Wang, Long T1 - Building content clusters based on modelling page pairs N2 - We give a new view on building content clusters from page pair models. We measure the heuristic importance within every two pages by computing the distance of their accessed positions in usage sessions. We also compare our page pair models with the classical pair models used in information theories and natural language processing, and give different evaluation methods to build the reasonable content communities. And we finally interpret the advantages and disadvantages of our models from detailed experiment results Y1 - 2006 UR - http://www.springerlink.com/content/105633/ U6 - https://doi.org/10.1007/11610113_85 ER - TY - JOUR A1 - Lindberg, Tilmann A1 - Meinel, Christoph A1 - Wagner, Ralf T1 - Design thinking : a fruitful concept for IT development? Y1 - 2011 SN - 978-3-642-13756-3 ER - TY - JOUR A1 - Meinel, Christoph A1 - Leifer, Larry T1 - Design thinking research Y1 - 2011 SN - 978-3-642-13756-3 ER - TY - JOUR A1 - Gumienny, Raja A1 - Meinel, Christoph A1 - Gericke, Lutz A1 - Quasthoff, Matthias A1 - LoBue, Peter A1 - Willems, Christian T1 - Tele-board : enabling efficient collaboration in digital design spaces across time and distance Y1 - 2011 SN - 978-3-642-13756-3 ER - TY - JOUR A1 - Thienen, Julia von A1 - Noweski, Christine A1 - Meinel, Christoph A1 - Rauth, Ingo T1 - The co-evolution of theory and practice in design thinking - or - "Mind the oddness trap!" Y1 - 2011 SN - 978-3-642-13756-3 ER - TY - JOUR A1 - Yeung, Ching-man Au A1 - Noll, Michael G. A1 - Gibbins, Nicholas A1 - Meinel, Christoph A1 - Shadbolt, Nigel T1 - Spear spamming-resistant expertise analysis and ranking incollaborative tagging systems JF - Computational intelligence N2 - In this article, we discuss the notions of experts and expertise in resource discovery in the context of collaborative tagging systems. We propose that the level of expertise of a user with respect to a particular topic is mainly determined by two factors. First, an expert should possess a high-quality collection of resources, while the quality of a Web resource in turn depends on the expertise of the users who have assigned tags to it, forming a mutual reinforcement relationship. Second, an expert should be one who tends to identify interesting or useful resources before other users discover them, thus bringing these resources to the attention of the community of users. We propose a graph-based algorithm, SPEAR (spamming-resistant expertise analysis and ranking), which implements the above ideas for ranking users in a folksonomy. Our experiments show that our assumptions on expertise in resource discovery, and SPEAR as an implementation of these ideas, allow us to promote experts and demote spammers at the same time, with performance significantly better than the original hypertext-induced topic search algorithm and simple statistical measures currently used in most collaborative tagging systems. KW - collaborative tagging KW - expertise KW - folksonomy KW - HITS KW - ranking KW - spamming Y1 - 2011 U6 - https://doi.org/10.1111/j.1467-8640.2011.00384.x SN - 0824-7935 SN - 1467-8640 VL - 27 IS - 3 SP - 458 EP - 488 PB - Wiley-Blackwell CY - Hoboken ER - TY - JOUR A1 - Thienen, Julia von A1 - Noweski, Christine A1 - Meinel, Christoph A1 - Lang, Sabine A1 - Nicolai, Claudia A1 - Bartz, Andreas T1 - What can design thinking learn from behavior group theraphy? Y1 - 2012 SN - 978-3-642-31990-7 ER - TY - JOUR A1 - Roschke, Sebastian A1 - Cheng, Feng A1 - Meinel, Christoph T1 - An alert correlation platform for memory-supported techniques JF - Concurrency and computation : practice & experience N2 - Intrusion Detection Systems (IDS) have been widely deployed in practice for detecting malicious behavior on network communication and hosts. False-positive alerts are a popular problem for most IDS approaches. The solution to address this problem is to enhance the detection process by correlation and clustering of alerts. To meet the practical requirements, this process needs to be finished fast, which is a challenging task as the amount of alerts in large-scale IDS deployments is significantly high. We identifytextitdata storage and processing algorithms to be the most important factors influencing the performance of clustering and correlation. We propose and implement a highly efficient alert correlation platform. For storage, a column-based database, an In-Memory alert storage, and memory-based index tables lead to significant improvements of the performance. For processing, algorithms are designed and implemented which are optimized for In-Memory databases, e.g. an attack graph-based correlation algorithm. The platform can be distributed over multiple processing units to share memory and processing power. A standardized interface is designed to provide a unified view of result reports for end users. The efficiency of the platform is tested by practical experiments with several alert storage approaches, multiple algorithms, as well as a local and a distributed deployment. KW - memory-based correlation KW - memory-based clustering KW - memory-based databases KW - IDS management Y1 - 2012 U6 - https://doi.org/10.1002/cpe.1750 SN - 1532-0626 VL - 24 IS - 10 SP - 1123 EP - 1136 PB - Wiley-Blackwell CY - Hoboken ER - TY - JOUR A1 - Jobst, Birgit A1 - Köppen, Eva A1 - Lindberg, Tilmann A1 - Moritz, Josephine A1 - Rhinow, Holger A1 - Meinel, Christoph T1 - The faith-factor in design thinking : creative confidence through education at the design thinking schools Potsdam and Standford? Y1 - 2012 SN - 978-3-642-31990-7 ER -