Mit der zunehmenden Menge textueller Daten im Web 2.0 wächst auch die Notwendigkeit der maschinellen Auswertung dieser Daten, beispielsweise um in Texten geäußerte Meinungen aufzuspüren (Opinion Mining). Im vorliegenden Beitrag wird das Aspect-based Opinion Mining – ein Verfahren mit sehr hohem Detaillierungsgrad – für deutschsprachige Texte anhand eines Projekts für die Versicherungswirtschaft vorgestellt. Es wird gezeigt, dass in Bewertungsplattformen geäußerte Meinungen zu Produkten und Services von Versicherungen mit einer Genauigkeit von etwa 90% und einer Vollständigkeit von ca. 80% für positive und ca. 60% für negative Meinungen erkannt werden können.

Value stream mapping (VSM) is a widely proven method to optimize a production. The practical approach, the manageable effort and the target-oriented procedure are the factors of success of this method. However, the method is of limited use when applied to make-to-order (MTO) environments. This paper aims to describe the shortcomings of VSM with respect to an application in a MTO production. The paper concentrates on the different logistic targets VSM impacts, as well as the manufacturing control tasks VSM applies. To set the basis for an application of VSM in MTO companies, requirements are described both for the logistic targets of VSM and the related manufacturing control tasks.

Keramische Werkstoffe werden aufgrund ihrer hervorragenden Verschleißresistenz und Biokompatibilität zunehmend in der Implanattechnik verwendet. Bisher jedoch konnten Keramiken für vollkeramische Knieimplantate nicht erfolgreich eingesetzt werden. Grund hierfür sind zunächst fehlende Anforderungskriterien an das Design und die geometrischen sowie topografischen Gegebenheiten eines vollkeramischen Knieimplantats. Darüber hinaus stellen die in der Implantattechnik eingesetzten Implantate hohe Anforderungen an die automatische Schleif- und Polierbearbeitung, welche erforderlich ist, um ein vollkeramisches Knieimplantat wirtschaftlich zu fertigen. Im Rahmen dieser Arbeit werden nachgiebige Diamantwerkzeuge eingesetzt, um verschleißgerechte Oberflächen auf keramischen Implantaten zu erzielen. Hierfür wird zunächst das Prozessverständnis für nachgiebige Werkzeuge geschaffen, um auf Basis der aktiven Kornanzahl und der Polierkraft keramische Oberflächen gezielt zu polieren. Abschließende Verschleißmessungen keramischer Implantatprüflinge zeigen auf, dass die Anzahl der Mikrokontakte der Implantatflächen anstelle der Rauheit maßgeblich für die Verschleißrate ist. 

In this paper, we report about benchmark experiments and results from optimizing database connectivity for querying social networking data from Apache Shindig in a Neo4j database. We built on our experiments from [1] and tried to improve performance of the current RESTful http connection in comparison to JDBC in order to fully utilize performance benefits of the graph database compared to relational database management systems. We implemented a database driver based on WebSockets. We found that BSON is a better data transfer format than JSON and compression increases performance in some settings while decreasing it in others. Multiple WebSocket connections are needed to scale to a high number of client requests and fully utilize database performance. Multi-threading is another key factor for scalability. Implementing a kind of stored procedure, we were able to further increase throughput and decrease response times.

Hybrid index structures support access to heterogeneous data types in multiple columns. Several experiments confirm the improved efficiency of these hybrid access structures. Yet, very little is known about the worst case time and space complexity of them. This paper aims to close this gap by introducing a theoretical framework supporting the analysis of hybrid index structures. This framework then is used to derive the constraints for an access structure which is both time and space efficient. An access structure based on a B+-Tree augmented with bit lists representing sets of terms from texts is the outcome of the analysis which is then validated experimentally together with a hybrid R-Tree variant to show a logarithmic search time complexity.

Knowledge management represents a key issue for both information systems’ academics and practitioners, including those who have become disillusioned by actual results that fail to deliver on exaggerated promises and idealistic visions. Social software, a tremendous global success story, has prompted similarly high expectations regarding the ways in which organizations can improve their knowledge handling. But can these expectations be met, whether in academic research or the real world? This article seeks to identify current research trends and gaps, with a focus on social knowledge environments. The proposed research agenda features four focal challenges: semi-permeable organizations, social software in professional work settings, crowd knowledge, and cross-border knowledge management. Three solutions emerge as likely methods to address these challenges: design-oriented solutions, analytical solutions, and interdisciplinary dialogue.

In this work, we present a system called PoliTwi, which was designed to detect emerging political topics (Top Topics) in Twitter sooner than other standard information channels. The recognized Top Topics are shared via different channels with the wider public. For the analysis, we have collected about 4,000,000 tweets before and during the parliamentary election 2013 in Germany, from April until September 2013. It is shown, that new topics appearing in Twitter can be detected right after their occurrence. Moreover, we have compared our results to Google Trends. We observed that the topics emerged earlier in Twitter than in Google Trends.

Finally, we show how these topics can be used to extend existing knowledge bases (web ontologies or semantic networks) which are required for concept-level sentiment analysis. For this, we utilized special Twitter hashtags, called sentiment hashtags, used by the German community during the parliamentary election.