Filtern
Erscheinungsjahr
- 2011 (27) (entfernen)
Dokumenttyp
- Ausgabe (Heft) zu einer Zeitschrift (27) (entfernen)
Schlagworte
- computer clusters (4)
- parallel algorithms (3)
- artifcial neural networks (2)
- artificial neural networks (2)
- Authentifizierung (1)
- Cloud Computing (1)
- Datensicherheit (1)
- E-government (1)
- E-services (1)
- Enterprise Systems (1)
- Healthcare institution (1)
- IT Outsourcing (1)
- IT Services (1)
- Internet (1)
- Neuronales Netz (1)
- Onlinewahl (1)
- Personalausweis (1)
- Quality assessment system (1)
- Search engine (1)
- Website (1)
- Wechselkursänderung (1)
- activation functions of neurons (1)
- adaptive resonance theory (1)
- artiffficial neural networks (1)
- artififfcial neural networks (1)
- blood analysis (1)
- business process management (1)
- classification (1)
- core ontologies (1)
- currency exchange rates (1)
- estimation of algorithm efficiency (1)
- gradient method of training weight coefficients (1)
- image processing (1)
- information system (1)
- knowledge work (1)
- mathematical model (1)
- mobile application (1)
- mobile facets (1)
- mobile phone (1)
- ontology (1)
- parallel calculations (1)
- scene analysis (1)
- social media (1)
- social object (1)
- social simulation (1)
- time series (1)
- tracking (1)
Institut
- Fachbereich 4 (27) (entfernen)
We present the user-centered, iterative design of Mobile Facets, a mobile application for the faceted search and exploration of a large, multi-dimensional data set of social media on a touchscreen mobile phone. Mobile Facets provides retrieval of resources such as places, persons, organizations, and events from an integration of different open social media sources and professional content sources, namely Wikipedia, Eventful, Upcoming, geo-located Flickr photos, and GeoNames. The data is queried live from the data sources. Thus, in contrast to other approaches we do not know in advance the number and type of facets and data items the Mobile Facets application receives in a specific contextual situation. While developingrnMobile Facets, we have continuously evaluated it with a small group of fifive users. We have conducted a task-based, formative evaluation of the fifinal prototype with 12 subjects to show the applicability and usability of our approach for faceted search and exploration on a touchscreen mobile phone.
An estimation of the number of multiplication and addition operations for training artififfcial neural networks by means of consecutive and parallel algorithms on a computer cluster is carried out. The evaluation of the efficiency of these algorithms is developed. The multilayer perceptron, the Volterra network and the cascade-correlation network are used as structures of artififfcial neural networks. Different methods of non-linear programming such as gradient and non-gradient methods are used for the calculation of the weight coefficients.