Bug #71944 Outdated URL on internals/fulltext
Submitted: 5 Mar 2014 18:08 Modified: 14 Mar 2014 18:03
Reporter: Daniël van Eeden (OCA) Email Updates:
Status: Closed Impact on me:
Category:MySQL Server: Documentation Severity:S3 (Non-critical)
Version: OS:Any
Assigned to: Stefan Hinz CPU Architecture:Any

[5 Mar 2014 18:08] Daniël van Eeden
Page: http://dev.mysql.com/doc/internals/en/full-text-search.html
Referenced page: http://www.miislita.com/term-vector/term-vector-1.html

The referenced page results in a 404.

How to repeat:
Visit referenced page.
[5 Mar 2014 18:12] MySQL Verification Team
Thank you for the bug report.
[11 Mar 2014 10:12] Hartmut Holzgraefe
https://en.wikipedia.org/wiki/Vector_space_model might be a replacement candidate for the broken link?
[14 Mar 2014 18:03] Stefan Hinz
Thank you for your bug report. This issue has been addressed in the documentation. The updated documentation will appear on our website shortly.
Replaced broken link with appropriate Wikipedia page.
Thanks for the suggestion, Hartmut!
[28 May 2016 3:45] E Garcia
Since 2014 http://www.miislita.com is a search engine site. The resource cited above (http://www.miislita.com/term-vector/term-vector-1.html) was moved to its sister site and is now available at 


with its content updated and improved. The old link now redirects permanently to the new one.

The MySQL implementation of the vector space model described in MySQL Internals Manual Section 10.7 is systematically explained in the updated version of the tutorial series at 


On other matters, we would like to mention of the following broken link in the MySQL Internal Manuals, Section 10.7: 


As an alternative, any of the following can be used instead as they all deal with pivoted normalization:

[28 May 2016 13:07] E Garcia
Scratch "pivoted" from the line that reads

"As an alternative, any of the following can be used instead as they all deal with pivoted normalization:"

True that the last three links provided discuss document length normalization, but only the first one is about pivoted normalization. My fault.