Features — Relevancy-Ranking
can sort and instantly re-sort searches
by relevancy with respect to number of
hits, file name, file date, etc.
provide automatic term weighting, following
a "plain English" or unstructured
indexed search request.
term weighting is
based on the frequency and density
of hits in your files.
example, in the search request get
me Sam's memo on the 1999 CorpX takeover,
if 1999 appeared in 3,000
files, and Sam appeared
in only two files, then Sam would
get a much higher relevancy rating,
taking you straight to the most "relevant" files.
- A positional
scoring option works
with dtSearch's natural language relevancy
ranking to rank documents more highly
when hits are near the top of a file,
or otherwise clustered in a file.
- Variable term weighting can also apply to natural language and other queries.
term weighting can place extra emphasis
on one or more words: soup:8
term weighting can assign negative
emphasis to one or more words: red
or green or yellow:-7
term weighting can also apply to
contains (apple and pear)) or (author:2
- Developers, for more API-driven sorting and relevancy-ranking options, see the Databases and Field Searching topic in Selected Articles by Subject.
See Also: Faceted Search and Metadata