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TITLE:
Intelligent Filtering for Graph Visualization
KEYWORDS:
Interactive Visualization, Information Filtering, Statistical Learning
ABOUT SAP:
The SAP Research Business Intelligence (BI) Practice is part of the global
technology research unit of SAP and works on next-generation data access and information delivery tools. Our mission is to bring breakthrough innovation and research, and contribute to the success of SAP's in user-centric BI and analytics technologies.
As the world's leading provider of business software, SAP delivers products and services that help accelerate business innovation for our customers. We believe that doing so will unleash growth and create significant new value -- for our customers, SAP, and ultimately, entire industries and the economy at large. Today, more than 47,800 customers in more than 120 countries run SAP applications -- from distinct solutions addressing the needs of small businesses and midsize companies to suite offerings for global organizations.
TOPIC DESCRIPTION:
In order to contribute to the Information Visualization research agenda, the BI Practice proposes a PhD position in its Sophia-Antipolis offices (Nice, France).
Recent trends in information and knowledge modeling are increasingly oriented towards graph based models that capture the relational structure between diverse types of entities. However, for large, strongly connected graphs it is difficult to visualize all information at once, as well as to decide how to zoom-into and explore the data without losing a general overview of the context. Filtering and aggregating information is an important line of research to overcome these drawbacks: efficient information visualization is just as much about knowing what to show than knowing what not to show. A first important research point is to test whether existing approaches for graph filtering / aggregation are suited to the knowledge structures that arise in intelligent business applications -- and whether their implementation allows for real-time interaction for visual analysis purposes. Second, it is worth exploring to what extent the success of these techniques is problem specific and!
how to develop more general and robust approaches. Finally, it is of interest to investigate entirely new approaches that build upon graphs as "models" for the filtering process. Such an approach, inspired by recent work in graph matching and graph querying, would make it possible to
take into account both the structure and the content of the knowledge bases, as well as to incorporate context and user information to customize the visual analysis experience.
CANDIDATE PROFILE:
- Last year student of M.Sc. or Engineering degree in Computer Science, Applied Mathematics or similar fields. Students with a strong academic record are favored.
- Interest for applied research and development. The candidate should be comfortable with theoretical / abstract work as well.
- Knowledge in Data Mining, Operations Research, Graph Theory and related fields. Ideal candidate has knowledge of algorithms for graph analysis and visualization, both theoretical and practical.
- Experience with programming languages (Java)
- Fluency in English (working language), other EU languages considered an advantage (in particular French)
- Excellent oral and written communication skills
TO APPLY:
Visit http://www.careersatsap.com/CareerCenter.aspx and enter the reference
FR-54454741-EN-11-002 in the search field.
Deadline is September 01, 2011.
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