Forgive me if this is brief in detail, but as is often the case, I have inherited a project I know very little about.
My organization is in the process of moving a help system for an enterprise level proprietary computer system from RoboHelp Classic to RoboHelp 2019.
The content and structure of the help topics is virtually identical in both systems. However searching is producing markedly different results.
In the old system (RoboHelp Classic), I can search for a help entry by title and it is the first item returned. When I perform the exact same search in RoboHelp 2019, the results are wildly different, and not at all helpful, and almost never contain the entry that I searched for.
Can anyone point me in the right direction? Is this an indexing issue? Or are there search settings in RH 2019 that I need to tweak? Any assistance would be appreciated as I am stumbling around in the dark at the moment.
I have flagged this thread with Adobe and they will be responding.
See www.grainge.org for free Authoring and RoboHelp Information
The results of the search are sorted using a score which is computed using BM25 algorithm along with other factors such as boost, proximity of keywords etc. In summary according to BM25 algorithm, the more a search term occurs in a single topic, the more that term will increase that topic’s score, but the more a search term occurs in the overall collection of topics, the less that term will increase a topic’s score.
For example, if a term occurs in several topics but in one topic it occurs very frequently then that topic will have higher score and will be displayed before other topics in the search result. But the frequency is not the only thing that is used to compute the topic’s score. Search term’s location also contributes the score of the topic. Following list is list of location in descending order of there boost value. Location with higher boost value adds more to the topic’s score.
In case search query has multiple terms then number of terms present in the document and there closeness also improves the score of the topic. For example of if you search for “Health and Safety” then any document which has both the keywords present will be ranked higher than the documents which have only one keyword present.
Closeness of the keywords plays a major role in the scoring. Any document which has all the keywords (within a window threshold of 50 characters) will always be ranked higher with all other documents which don’t have all the keywords, even if they are present in the body of the document and other documents have keyword in title or headings.
These are the main factors which decide the rank of the document in the search results. Hope this clears your doubts.
Please let us know if you any more queries.