Corporate Semantic Search
An effective knowledge management of corporate information resources is a cornerstone for a long-lasting competitive advantage. Semantic Web Technologies offer new possibilities for enhanced integration of heterogeneous business data, information discovery as well as advanced automation of sophisticated tasks. The foundation of the Semantic Web is build upon ontologies which formally and unambiguously describe concepts of an application domain as well as relationships among them, thus making data machine interpretable. Utilizing them in corporate portals, as means for representing business objects, could substantially improve both content navigation as well as search results.
As a business oriented research group concentrating on the Semantic Web applied within corporate structures, the Corporate Semantic Web (CSW) project covers a wide spectrum of innovative scientific and application oriented solutions for research problems in a corporate context. One of the pillars of CSW research is represented by Corporate Semantic Search which unites standard search methods with semantic technologies. The systematic integration of business information allows the semantic analysis of the available data and information sources making semantic search an enhancement to the classical search solutions. Corporate Semantic Search, in this context, refers to the different forms of semantic search in corporate and business applications.
Search in Non-semantic Data
The key objective of this research area is the development of a semantic based learning method for trend recognition in hybrid information systems, i.e. systems consisting of both qualitative and quantitative data. Using the financial domain as an example of hybrid information systems and having regard to the multimodal financial data, an adequate trend recognition method will be developed for the recognition of temporal changing patterns in textual information sources relevant to the financial market domain. The focus of this research will be put on developing a solution relevant to the trend mining problem which combines a Data Mining approach with adequate Semantic Web technologies.
Search Personalization
Searching for business objects like products, projects, employee profiles, etc. is a
nontrivial and often occurring task. For complex objects having multiple
properties a perfect match is rarely found. Therefore, the user is, in most
cases, also interested in a ranking of objects by their semantic similarity
values with respect to the personalized query. The focus of this work package
lies on utilizing Semantic Web technologies in order to enhance the query capabilities
of corporate portals. The research in this area ranges from adaptive and
adaptable representation of search profiles, over evaluation of semantically
represented business objects with respect to user preferences based on semantic
similarity of concepts, to providing the user with requirement based,
personalized views on corporate data.
Multimedia Search
Start: 2011-02
Search Contextualiztion
Start: 2011-02
