Semantic Search Components
This event took place on Wednesday 08 November 2006 at 11:30
Dr. Victoria Uren KMi, The Open University, UK
Formulating complex queries is hard, especially in heterogeneous information environments, where users do not understand all the data structures of multiple complex knowledge bases. We see a gap between semantic search tools that are user friendly, but have restricted functionality, and powerful, formal query languages, which are unsuitable for end users. We explore the complexity of semantic queries through an example. Building on this example, we propose a solution using a component based approach. We propose a layered architecture, with components taking an intermediary role between the end user interface and formal query languages. The kinds of components that would be needed for such a system are outlined, and challenges for the system are discussed, in particular, how to combine semantic searches. This paper was presented at EKAW 2006.
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This event took place on Wednesday 08 November 2006 at 11:30
Dr. Victoria Uren KMi, The Open University, UK
Formulating complex queries is hard, especially in heterogeneous information environments, where users do not understand all the data structures of multiple complex knowledge bases. We see a gap between semantic search tools that are user friendly, but have restricted functionality, and powerful, formal query languages, which are unsuitable for end users. We explore the complexity of semantic queries through an example. Building on this example, we propose a solution using a component based approach. We propose a layered architecture, with components taking an intermediary role between the end user interface and formal query languages. The kinds of components that would be needed for such a system are outlined, and challenges for the system are discussed, in particular, how to combine semantic searches. This paper was presented at EKAW 2006.
Download presentation slides
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KnowledgeManagementMultimedia &
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HypermediaNew Media SystemsSemantic Web &
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We focus on content-based information retrieval over a wide range of data spanning form unstructured text and unlabelled images over spoken documents and music to videos. This encompasses the modelling of human perception of relevance and similarity, the learning from user actions and the up-to-date presentation of information. Currently we are building a research version of an integrated multimedia information retrieval system MIR to be used as a research prototype. We aim for a system that understands the user's information need and successfully links it to the appropriate information sources, be it a report or a TV news clip. This work is guided by the vision that an automated knowledge extraction system ultimately empowers people making efficient use of information sources without the burden of filing data into specialised databases.
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