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| For examples of query snapping, see **[DRAFT] Knowledge intelligence**. |
The following languages are supported for this:
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For more information on how Knowledge Intelligence works, see **[DRAFT] Knowledge intelligence**. |
Extracting entities
If an item of content has been created in one of the languages listed below, Fuse is able to process the text within the content and extract entities. An entity is a piece of information that is present somewhere in the content body that matches predefined categories, such as Person, Date, Company or File type, which Fuse can transform into a tag. These tags are metadata. This metadata is then used to help users find this content quickly in searches. These also allow Fuse to do query snapping, in which Fuse automatically applies filters and facets to search results.
For example, a Word document might contain the following sentence: "John Smith's company, ACME Corp, successfully designed and produced their first electric car in 2020". Fuse might scan this sentence within the Word document and add the following tags metadata to make it easier to find:
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For example, when you search for "electric vehicle", Fuse scans content to find the term "electric vehicle" as well as the respective terms "electric" and "vehicle". If these terms are present in the body of any items of content, Fuse ranks these in the search results. In this case, any content that contains "electric vehicle" will be listed first and those containing the respective terms "electric" and/or "vehicle" will appear afterwards.
The following languages are supported when extracting keywords:
- British English
- European Portuguese
- Peninsular Spanish
- American English
- French
- German
- Italian
- Danish
- Dutch
- Finnish
- Norwegian
- Russian
- Swedish
- Japanese
- Korean
- Polish