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30.07.2010

Life Sciences:
- Search and creation standardized information about genes, such as gene Ontology (http://www.geneontology.org/). The information used in the study human genome, disease and genetics in general.
- Search and obtaining information from millions of documents, which are used in research and discovery of new drugs
- Normalisation, integration and analysis of patient data with the aim of early detection, prediction and prevention of disease
- Query the ordinary, everyday language with the aim of search millions of documents related to medical and bio research, and for information on drugs, procedures and indications.

Government:
- Intelligence, text analysis, early warning from social networks,forums, comments, normalization entities through multilingual website
- Integration of public data through a semantic grouping of the government agency websites
- Integration of data related to criminal justice, normalization and merging of search results data through different court jurisdictions
- Merge the search results data through local governments and their autocategorization by topics
- Automatic notification of users on various topics and conditions, for example on tenders and public procurement.

Publishing:
- Isolation and analysis of concepts in order to improve indexing and search results are obtained by user relevance
- Auto-categorization and classification of the various topics and areas to facilitate easier to find the desired publication and the publisher better sales and new markets
- Auto suggesting book titles that may interest the customer, based on the creation of concepts in real time
- Query the ordinary, everyday language by the user

Software:
- Automatic checks of the fit into the designed standards and quality
- Semantic data search and Auto-categorization data is embedded in many of the tools of today's software industry
- Integration of code from various sources
- For large a software firm that link multiple projects simultaneously, have built a unique search solutions to different storage
- Ontological driven project management with a large number of development code.

Financial:
- Public opinion polls in real time, using the news that can affect trading and stock performance
- Finding and normalization of data on transactions undertaken with a variety of systems that belong to the banks in the merged operations
- Semantic processing of data with the aim of integrating a number of different systems for complex banking events (eg wire transfer)

Legal:
- Language analysis, eliminating irrelevant and categorization of relevant content and materials for the preparation of cases
- Separation of the entities and conceptual analysis aimed at normalization of subject indexing of documents, memos and e-mail
- Mergers and normalization of legal and other documents in order to prepare case

Manufactoring:
- Data mining and auto-categorizing catalogs of multiple parts, equipment, and materials manufacturers
- Automatic topical tagging and annotation of documentation for complex, large-scale manufacturing
- Ontology of aircraft geometric and structural components to maintain impact awareness of changes

Electronics:
- Entity extraction and normalization to integrate geographical physical information with mobile search
- Natural language processing support for customer self-service on mobile devices

Energy:
- Mining and normalizing basin data results from disparate sources to federate results for analysis
- News feed monitoring to discover trends and new entities for competitive intelligence
- Federating content across global operations for strategic business analysis and improvement

Education:
- Concept discovery and topical categorization of large domains for scholarly research support
- Federation of public content search results with academic resources
- Ontology use for unifying educational resources across collaborating campuses or institution

Tourism:
- Improving search and navigation and knowledge base of various materials, as well as increased sales arrangements that may be related.