Filtering CHOs by Learning Sample Clauses

Filtering CHOs by Learning. A major concern for any creative/topical application of Europeana CHOs is how to distinguish useful from "useless" objects. For example, the two objects below are not likely to be of interest to anyone but an archaeologist: • jar fragment60 from the Xxxxxx Museum of Egyptian Archaeology (UCL) • cup fragment61 from the Fitzwilliam Museum, Cambridge, UK 60 xxxx://xxxxxxxxx.xx/portal/record/2022347/8BA4652040C28D97167F10C8A07FB03747BCB5B8 61 xxxx://xxxxxxxxx.xx/portal/record/2022304/1CDFAE9C1AC3F86DE38CAB40B6764324A1CF634F This is not nit-picking, since about half the objects with the keyword "jar" are fragments or shards. Since Europeana does not enforce object quality criteria, nor has notability criteria (like Wikipedia), all kinds of objects that hold only specialist interest have made their way into Europeana. We can use machine learning approaches to acquire "blacklists" in a dynamic way.
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Related to Filtering CHOs by Learning

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