Exploring Semantic Hits
This event took place on Wednesday 06 May 2009 at 11:30
Thomas Ullmann KMi, The Open University
SemSearchXplorer is a toolkit for the exploration of semantic data. The goal is to lower barriers to access information in semantic data
repositories. Therefore SemSearchXplorer supports the user in three respects: (1) It supports querying of the semantic data with a keyword based approach, so the users do not need to learn a semantic query language, (2) it helps users finding relevant results on the one hand by semantic enriched information about the results and on the other hand with semantic filter options to narrow down the set of results, and (3) it provides information exploration capabilities through semantic visualizations recommended by the system. Filtering of semantic search results helps to narrow down the result set to a more manageable amount of information. SemSearchXplorer uses a class filter and a filter based on the key concepts of an ontology to support filtering of information. Besides the searching for relevant information, facilities for the exploration of the results help users to gain insight in the context of results. With several semantic visualizations, we try to help users making sense of the raw data. Based on the assumption that there is no single visualization that fit all exploration needs, SemSearchXplorer recommends visualizations based on the selected information of users.
This event took place on Wednesday 06 May 2009 at 11:30
SemSearchXplorer is a toolkit for the exploration of semantic data. The goal is to lower barriers to access information in semantic data
repositories. Therefore SemSearchXplorer supports the user in three respects: (1) It supports querying of the semantic data with a keyword based approach, so the users do not need to learn a semantic query language, (2) it helps users finding relevant results on the one hand by semantic enriched information about the results and on the other hand with semantic filter options to narrow down the set of results, and (3) it provides information exploration capabilities through semantic visualizations recommended by the system. Filtering of semantic search results helps to narrow down the result set to a more manageable amount of information. SemSearchXplorer uses a class filter and a filter based on the key concepts of an ontology to support filtering of information. Besides the searching for relevant information, facilities for the exploration of the results help users to gain insight in the context of results. With several semantic visualizations, we try to help users making sense of the raw data. Based on the assumption that there is no single visualization that fit all exploration needs, SemSearchXplorer recommends visualizations based on the selected information of users.
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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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