Very fast index updates: No need for re-builting the whole index
on every submission to the indexer.
Proximity: Ranking results with respect to how close the keywords were found in
a document. So if you have a document which includes the phrase "full
text search" and another document which includes the words "full",
"text", "search", the first one will be ranked higher.
Weighting scheme: Configurable weights for words in title and body.
By default, words in title weight more than words in the body of the document.
So, documents that contain the search query in the title are ranked higher than
those that contain it in the body..
Stemming: It allows to find same words with different endings. For
example, if words "testing" or "tests" are found in a document, the word
"test" will be stored by indexer instead. Search will also try to find
the word "test" if "testing" or "tests" is given in search query. Note
that this scheme lacks exact search possibility, but usually reduces
database size and makes search faster.
Stopwords: Ignores common words and characters (known as stopwords)
as they tend to slow down searches without improving the quality of the
results. Terms such as "where" and "how", as well as certain single
digits and single letters, are not included in searches.
Modular architecture: Makes it easy to add parsers and dictionaries.
Multilingual support: Latin and Cyrillic are available. Other can be added.
Search terms in context: Displays excerpt from the documents,
which shows how your search terms are used in context on that document.
Your search terms are bolded so you can tell at a glance whether
the result is a document you want to view.
