P266 - BTW2017 - Datenbanksysteme für Business, Technologie und Web - Workshopband
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- KonferenzbeitragApplication and Testing of Business Processes in the Energy Domain(Datenbanksysteme für Business, Technologie und Web (BTW 2017) - Workshopband, 2017) Böhmer, Kristof; Stertz, Florian; Hildebrandt, Tobias; Rinderle-Ma, Stefanie; Eibl, Günther; Ferner, Cornelia; Burkhart, Sebastian; Engel, DominikThe energy domain currently struggles with radical legal and technological changes, such as, smart meters. This results in new use cases which can be implemented based on business process technology. Understanding and automating business processes requires to model and test them. However, existing process testing approaches frequently struggle with the testing of process resources, such as ERP systems, and negative testing. Hence, this work presents a toolchain which tackles that limitations. The approach uses an open source process engine to generate event logs and applies process mining techniques in a novel way.
- Konferenzbeitragasprin: Answer Set Programming with Preferences(Datenbanksysteme für Business, Technologie und Web (BTW 2017) - Workshopband, 2017) Romero, JavierAnswer Set Programming (ASP) is a well established approach to declarative problem solving, combining a rich yet simple modeling language with high-performance solving capacities. In this talk we present asprin, a general, flexible and extensible framework for preferences in ASP. asprin is general and captures many of the existing approaches to preferences. It is flexible, because it allows for the combination of different types of preferences. It is also extensible, allowing for an easy implementation of new approaches to preferences. Since it is straightforward to capture propositional theories and constraint satisfaction problems in ASP, the framework is also relevant to optimization in Satisfiability Testing and Constraint Processing.
- KonferenzbeitragBTW 2017 Data Science Challenge (SDSC17)(Datenbanksysteme für Business, Technologie und Web (BTW 2017) - Workshopband, 2017) Waizenegger, Tim
- KonferenzbeitragThe Case For Change Notifications in Pull-Based Databases(Datenbanksysteme für Business, Technologie und Web (BTW 2017) - Workshopband, 2017) Wingerath, Wolfram; Gessert, Felix; Friedrich, Steffen; Witt, Erik; Ritter, NorbertModern web applications often require application servers to deliver updates proactively to the client. These push-based architectures, however, are notoriously hard to implement on top of existing infrastructure, because today’s databases typically only support pull-based access to data. In this paper, we first illustrate the usefulness of query change notifications and the complexity of providing them. We then describe use cases and discuss state-of-the-art systems that do provide them, before we finally propose a system architecture that offers query change notifications as an opt-in feature for existing pull-based databases. As our proposed architecture distributes computational work across a cluster of machines, we also compare scalable stream processing frameworks that could be used to implement the proposed system design.
- KonferenzbeitragComparative Evaluation for Recommender Systems for Book Recommendations(Datenbanksysteme für Business, Technologie und Web (BTW 2017) - Workshopband, 2017) Tashkandi, Araek; Wiese, Lena; Baum, MarcusRecommender System (RS) technology is often used to overcome information overload. Recently, several open-source platforms have been available for the development of RSs. Thus, there is a need to estimate the predictive accuracy of such platforms to select a suitable framework. In this paper we perform an offline comparative evaluation of commonly used recommendation algorithms of collaborative filtering. They are implemented by three popular RS platforms (LensKit, Mahout, and MyMediaLite) using the BookCrossing data set containing 1,149,780 user ratings on books. Our main goal is to find out which of these RSs is the most applicable and has high performance and accuracy on these data. We consider performing a fair objective comparison by benchmarking the evaluation dimensions such as the data set and the evaluation metric. Our evaluation shows the disparity of evaluation results between the RS frameworks. This points to the need of standardizing evaluation methodologies for recommendation algorithms.
- KonferenzbeitragComparing Relevance Feedback Techniques on German News Articles(Datenbanksysteme für Business, Technologie und Web (BTW 2017) - Workshopband, 2017) Romberg, JuliaWe draw a comparison on the behavior of several relevance feedback techniques on a corpus of German news articles. In contrast to the standard application of relevance feedback, no explicit user query is given and the main goal is to recognize a user’s preferences and interests in the examined data collection. The compared techniques are based on vector space models and probabilistic models. The results show that the performance is category-dependent on our data and that overall the vector space approach Ide performs best.
- KonferenzbeitragComputational Social Choice in the Clouds(Datenbanksysteme für Business, Technologie und Web (BTW 2017) - Workshopband, 2017) Csar, Theresa; Lackner, Martin; Pichler, Reinhard; Sallinger, EmanuelIn the era of big data we are concerned with solving computational problems on huge datasets. To handle huge datasets in cloud systems dedicated programming frameworks are used, among which MapReduce is the most widely employed. It is an important issue in many application areas to design parallel algorithms which can be executed efficiently on cloud systems and can cope with big data. In computational social choice we are concerned with computational questions of joint decision making based on preference data. The question of how to handle huge preference datasets has not yet received much attention. In this report we summarize our recent work on designing and evaluating algorithms for winner determination in huge elections using the MapReduce framework.
- KonferenzbeitragCoordinated Omission in NoSQL Database Benchmarking(Datenbanksysteme für Business, Technologie und Web (BTW 2017) - Workshopband, 2017) Friedrich, Steffen; Wingerath, Wolfram; Ritter, NorbertDatabase system benchmark frameworks like the Yahoo! Cloud Serving Benchmark (YCSB) play a crucial role in the process of developing and tuning data management systems. YCSB has become the de facto standard for performance evaluation of scalable NoSQL database systems. However, its initial design is prone to skipping important latency measurements. This phenomenon is known as the coordinated omission problem and occurs in almost all load generators and monitoring tools. A recent revision of the YCSB code base addresses this particular problem, but does not actually solve it. In this paper we present the latency measurement scheme of NoSQLMark, our own YCSB-based scalable benchmark framework that completely avoids coordinated omission and show that NoSQLMark produces more accurate results using our validation tool SickStore and the distributed data store Cassandra.
- KonferenzbeitragCustomer Service in Social Media: An Empirical Study of the Airline Industry(Datenbanksysteme für Business, Technologie und Web (BTW 2017) - Workshopband, 2017) Carnein, Matthias; Homann, Leschek; Trautmann, Heike; Vossen, Gottfried; Kraume, KarstenUntil recently, customer service was exclusively provided over traditional channels. Cus- tomers could write an email or call a service center if they had questions or problems with a product or service. In recent times, this has changed dramatically as companies explore new channels to offer customer service. With the increasing popularity of social media, more companies thrive to provide customer service also over Facebook and Twitter. Companies aim to provide a better customer ex- perience by offering more convenient channels to contact a company. In addition, this unburdens traditional channels which are costly to maintain. This paper empirically evaluates the performance of customer service in social media by analysing a multitude of companies in the airline industry. We have collected several million customer service requests from Twitter and Facebook and auto- matically analyzed how efficient the service strategies of the respective companies are in terms of response rate and time.
- KonferenzbeitragA Data Center Infrastructure Monitoring Platform Based on Storm and Trident(Datenbanksysteme für Business, Technologie und Web (BTW 2017) - Workshopband, 2017) Dreissig, Felix; Pollner, NikoSensor data of a modern data center’s cooling and power infrastructure fulfil the character- istics of data streams and are therefore suitable for stream processing. We present a stream-based monitoring platform for data center infrastructure. It is based on multiple independent collectors, which query measurements from sensors and forward them to an Apache Kafka queue. At the platform’s core is a processing cluster based on Apache Storm and its high-level Trident API. From there, results get forwarded to one or multiple data sinks. Using our system, analytical queries can be developed using a collection of universal, generic stream operators including CORRELATE, a novel operator which combines elements from multiple streams with unique semantics. Besides the platform’s general concept, the characteristics and pitfalls of our real-world implementation are also discussed in this work.