ROSeAnn: Reconciling Opinions of Semantic Annotators
Named entity extractors can be used to enrich both text and Web documents with semantic annotations. While originally focused on a few standard entity types, the ecosystem of annotators is becoming increasingly diverse, with recognition capabilities ranging from generic to specialised entity types....
| Main Authors: | , , , |
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| Format: | Conference item |
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2013
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| _version_ | 1826297702544048128 |
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| author | Chen, L Ortona, S Orsi, G Benedikt, M |
| author_facet | Chen, L Ortona, S Orsi, G Benedikt, M |
| author_sort | Chen, L |
| collection | OXFORD |
| description | Named entity extractors can be used to enrich both text and Web documents with semantic annotations. While originally focused on a few standard entity types, the ecosystem of annotators is becoming increasingly diverse, with recognition capabilities ranging from generic to specialised entity types. Both the overlap and the diversity in annotator vocabularies motivate the need for managing and integrating semantic annotations: allowing users to see the results of multiple annotations and to merge them into a unified solution. We demonstrate ROSEANN, a system for the management of semantic annotations. ROSEANN provides users with a unified view over the opinion of multiple independent annotators both on text and Web documents. It allows users to understand and reconcile conflicts between annotations via ontology-aware aggregation. ROSEANN incorporates both supervised aggregation, appropriate when representative training data is available, and an unsupervised method based on the notion of weighted-repair. |
| first_indexed | 2024-03-07T04:35:42Z |
| format | Conference item |
| id | oxford-uuid:cfd88fb4-267b-466c-9002-782727d75907 |
| institution | University of Oxford |
| last_indexed | 2024-03-07T04:35:42Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | oxford-uuid:cfd88fb4-267b-466c-9002-782727d759072022-03-27T07:45:39ZROSeAnn: Reconciling Opinions of Semantic AnnotatorsConference itemhttp://purl.org/coar/resource_type/c_5794uuid:cfd88fb4-267b-466c-9002-782727d75907Department of Computer Science2013Chen, LOrtona, SOrsi, GBenedikt, MNamed entity extractors can be used to enrich both text and Web documents with semantic annotations. While originally focused on a few standard entity types, the ecosystem of annotators is becoming increasingly diverse, with recognition capabilities ranging from generic to specialised entity types. Both the overlap and the diversity in annotator vocabularies motivate the need for managing and integrating semantic annotations: allowing users to see the results of multiple annotations and to merge them into a unified solution. We demonstrate ROSEANN, a system for the management of semantic annotations. ROSEANN provides users with a unified view over the opinion of multiple independent annotators both on text and Web documents. It allows users to understand and reconcile conflicts between annotations via ontology-aware aggregation. ROSEANN incorporates both supervised aggregation, appropriate when representative training data is available, and an unsupervised method based on the notion of weighted-repair. |
| spellingShingle | Chen, L Ortona, S Orsi, G Benedikt, M ROSeAnn: Reconciling Opinions of Semantic Annotators |
| title | ROSeAnn: Reconciling Opinions of Semantic Annotators |
| title_full | ROSeAnn: Reconciling Opinions of Semantic Annotators |
| title_fullStr | ROSeAnn: Reconciling Opinions of Semantic Annotators |
| title_full_unstemmed | ROSeAnn: Reconciling Opinions of Semantic Annotators |
| title_short | ROSeAnn: Reconciling Opinions of Semantic Annotators |
| title_sort | roseann reconciling opinions of semantic annotators |
| work_keys_str_mv | AT chenl roseannreconcilingopinionsofsemanticannotators AT ortonas roseannreconcilingopinionsofsemanticannotators AT orsig roseannreconcilingopinionsofsemanticannotators AT benediktm roseannreconcilingopinionsofsemanticannotators |