We are trying to group phrases together in order to improve results.
For instance, if the user asks a question like "When do I have to change the filter of my air conditioning?" with a domain specific phrase such as “air conditioning”, R&R returns some answers containing the term “air” and no “conditioning” or it returns answers containing other terms like air bag or air filter.
This can be accomplish using a raw Solr instance and set the phrase between quotes. So, the Solr query would look like the following:
...
"debug": {
"rawquerystring": "When do I have to change the filter of my \"air conditioning\" ?",
"querystring": "When do I have to change the filter of my \"air conditioning\" ?",
"parsedquery": "text:when text:do text:i text:have text:to text:change text:the text:filter text:of text:my PhraseQuery(text:\"air conditioning\") text:?",
"parsedquery_toString": "text:when text:do text:i text:have text:to text:change text:the text:filter text:of text:my text:\"air conditioning\" text:?",
...
However, the R&R guide states:
The syntax is different from standard Solr syntax as follows:
You can search for a single term, or a phrase. You do not need to surround the phrase with double quotation marks as with Solr, but you can include phrases in the query and they are accounted for by the ranker models.
We could not find more details regarding the above statement.
But, as we understand, the ranker is supposed to identify phrases. If that is the case, we were wondering if there is a way where we can set a dictionary of phrases in order to tune the ranker? Or, could we set our own model of legal phrases? What are the options to accomplish this goal?
Thanks