Individual user responsibility: working data, derived data Data must be backed up using a tested/automated process: working data, derived data; published data resource data Not available to the public: working data; derived data Made available to the public as described below: Published data and Resource dataThe Authoring Tools for Multimedia Content (AToMiC) Track aims to build reliable benchmarks for multimedia search systems. The focus of this track is to develop and evaluate IR techniques for text-to-image and image-to-text search problems.
About this Dataset
Title | Authoring Tools for Multimedia Content (AToMiC) Track 2023 |
---|---|
Description | Individual user responsibility: working data, derived data Data must be backed up using a tested/automated process: working data, derived data; published data resource data Not available to the public: working data; derived data Made available to the public as described below: Published data and Resource dataThe Authoring Tools for Multimedia Content (AToMiC) Track aims to build reliable benchmarks for multimedia search systems. The focus of this track is to develop and evaluate IR techniques for text-to-image and image-to-text search problems. |
Modified | 2024-04-18 00:00:00 |
Publisher Name | National Institute of Standards and Technology |
Contact | mailto:[email protected] |
Keywords | TREC text retrieval conference |
{ "identifier": "ark:\/88434\/mds2-3243", "accessLevel": "public", "contactPoint": { "hasEmail": "mailto:[email protected]", "fn": "Ian Soboroff" }, "programCode": [ "006:045" ], "landingPage": "https:\/\/data.nist.gov\/od\/id\/mds2-3243", "title": "Authoring Tools for Multimedia Content (AToMiC) Track 2023", "description": "Individual user responsibility: working data, derived data Data must be backed up using a tested\/automated process: working data, derived data; published data resource data Not available to the public: working data; derived data Made available to the public as described below: Published data and Resource dataThe Authoring Tools for Multimedia Content (AToMiC) Track aims to build reliable benchmarks for multimedia search systems. The focus of this track is to develop and evaluate IR techniques for text-to-image and image-to-text search problems.", "language": [ "en" ], "distribution": [ { "accessURL": "https:\/\/pages.nist.gov\/trec-browser\/trec32\/atomic\/overview\/", "title": "Authoring Tools for Multimedia Content (AToMiC) Track" }, { "downloadURL": "https:\/\/huggingface.co\/TREC-AToMiC", "mediaType": "application\/octet-stream", "title": "TREC 2023 CORPUS DATASET" } ], "bureauCode": [ "006:55" ], "modified": "2024-04-18 00:00:00", "publisher": { "@type": "org:Organization", "name": "National Institute of Standards and Technology" }, "theme": [ "Information Technology:Computational science", "Information Technology:Data and informatics" ], "keyword": [ "TREC text retrieval conference" ] }