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This section includes information about the new Fuse search. If you are currently using Fuse's legacy search, see Legacy search. |
This section covers the languages that are supported in Fuse search. The languages recognised by Fuse when you enter a search query, and those supported and recognised , including those recognised by Knowledge Intelligence are different.
This section includes:
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Searching for content
Fuse only returns searches across content in the language selected in your profile. When you search for content in Fuse, the search engine automatically recognises the language of the entered query and returns content in this language, based on what you have searched for. If applicable, Fuse automatically applies filters to the search results, using query snapping.
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| For examples of query snapping, see [DRAFT] Knowledge intelligence. |
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authored in all supported languages and returns results that best match your query.
Knowledge intelligence
Knowledge intelligence means that when content is added to Fuse, it is scanned using various technologies to better understand the content. When the content is processed, additional metadata is added, which takes the form of extracted entities, such as locations, people, amounts , skills, dates and so onand dates. Keywords (also known as noun phrases) are also extracted.
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For more information on how Knowledge Intelligence works, see [DRAFT] Knowledge intelligenceIntelligence. |
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 typea person, date, organisation, location and so on, which Fuse can transform into metadata. This metadata is then used to help users find this content quickly in searches. This metadata also allows Fuse to perform query snapping, in which Fuse automatically applies filters and facets to search results.
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Example: If you search for 'fire safety articles by Edward Francis', Fuse might intuitively apply the following facets to search results:
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The following languages are supported when extracting entities:
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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 to make it easier to find in searches:
- 2020 (DateTime)
- John Smith (Person)
- ACME Corp (Organisation)
Below you can find a list of entities that Fuse's Knowledge Intelligence engine recognises, along with the supported languages for each entity:
| Entity | Description | Supported languages | ||
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| Person | The name of a person. For example, John Smith. |
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| PersonType | A person's job or role. For example, Admin. |
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| Location | Landmarks, structures, geographical features, and geopolitical entities. This might be a city, town or region. For example, London. |
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| Organisation | Companies, political organisations, music groups, sports clubs, government and public organisations. For example, ACME Ltd. |
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| Event | Cultural events, public holidays and sporting events. |
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| Product | This might be a product that a company produces, such as software or computing products. |
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| Address | The street address of a physical location, such as a house or office building. For example, 123 Carlton Avenue. |
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| Phone number | A phone number. |
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An email address. For example, john.smith@acmecorp.com.
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| IPAddress | A network IP address. |
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| URL | A web address. For example, www.bbc.co.uk. |
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| DateTime | Dates and times. This includes calendar dates, date and time ranges, times of day, durations. |
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| Quantity | This can be units of measurement and amounts. This includes percentages, ages, currency, temperatures, and dimensions. |
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Extracting keywords
If an item of content has been created in one of the following languages, Fuse is able to process the text within the content and extract keywords.
For example, when you search for "'electric vehicle"', Fuse scans existing content items to find the term "term 'electric vehicle" ' as well as the respective terms "electric" and "vehicle"'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:
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