Difference between revisions of "Blog/Boost document findability with tags in O365"
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− | Finding documents in Sharepoint online/Office 365 can be tedious. If you want to restrict your search to certain document types (like: reports, inquiries, CVs, sales orders, invoices) you either end up with too many irrelevant search hits (like: the search term "order" returns a lot of CVs) or relevant documents don't show up because the search term is not included (like "bill" instead of "invoice"). If you rely on Sharepoint's fulltext search capabilities then your users will be frustrated and spend too much time finding the right documents.</p> | + | Finding documents in Sharepoint online/Office 365 can be tedious. If you want to restrict your search to certain document types (like: reports, inquiries, CVs, sales orders, invoices) you either end up with too many irrelevant search hits (like: the search term "order" returns a lot of CVs) or relevant documents don't show up because the search term is not included (like "bill" instead of "invoice"). If you rely on Sharepoint's fulltext search capabilities then your users will be frustrated and spend too much time finding the right documents. |
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Revision as of 16:02, 28 September 2020
Main Page > Der DIQA Blog > Blog/Boost document findability with tags in O365
Blog
O365: Boost document findability with tags (September 1, 2020)
Finding documents in Sharepoint online/Office 365 can be tedious. If you want to restrict your search to certain document types (like: reports, inquiries, CVs, sales orders, invoices) you either end up with too many irrelevant search hits (like: the search term "order" returns a lot of CVs) or relevant documents don't show up because the search term is not included (like "bill" instead of "invoice"). If you rely on Sharepoint's fulltext search capabilities then your users will be frustrated and spend too much time finding the right documents.
Frustrating search experience without meaningful refiners:
Entering the search term "order" returns a lot of irrelevant documents (e.g. a CV) and even misses some sales order documents.
Video
contact
Dipl.-Wirtsch.-Inf.
Daniel Hansch
Machine Learning expert, software engineer, project manager
Tel.: +49-176 64078339
[email protected]