Consider this sample use case involving accessing agricultural and food data. Today users often cannot grasp the content in their native language. Search is possible only in the language of the indexed documents. There is low quality of translations, and terminology is not correctly translated. Content metadata is of low quality and incomplete, prohibiting good discovery services, and content is not connected to external data sources.
FREME will improve this situation in several ways: e-Translation will allow users to access content in their own language. e-Entity will be used to detect and search relevant entities in user queries; in combination with e-Translation, this will allow users to discover content across language barriers and explore structured data with their native language. e-Terminology will help to create high quality terminology efficiently. e-Link will make it possible to connect the terminology with external data sources. e-Publishing and e-Internationalisation will provide standardised representation of content including enrichment information. This will be the basis for further content re-use.
“Since FREME objectives span a wide range of business and research communities, we have discussed FREME at many events, ranging from cutting edge research conferences or industry specific events to EU networking, related to the communities of data, language technology and public sector information,” says project coordinator, Professor Felix Sasaki from DFKI, one of the largest non-profit contract research institutes in the field of innovative software technology based on Artificial Intelligence (AI) methods.
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