On Jul 13, 2005, at 8:18 AM, Rahul D Thakare wrote:
We are using doc.add(Field.Text("keywords",keywords)); to add the
keywords to the document, where keywords is comma separated
keywords string.
If the text is already comma separated and that is the level at which
you things tokenized, then simply do something like this (untested
pseudo-code):
String[] values = keywords.split(",");
for (int i=0; i < values.length; i++)
doc.add(Field.Keyword("keywords", values[i]));
Lucene seems to tokenize the keywords with multiple words like(MAIN
BOARD) as different keywords(ie as MAIN and BOARD). Tokenization is
based on comma and space...So if we search for "MAIN BOARD",
documents having keywords like "MAIN LOGIC", "MAIN PARTS", etc also
show up
If one searches for "MAIN BOARD", we want get only the documents
have "MAIN BOARD". How to do this ?
The question back to you is do you want searches for simply "MAIN" to
find both "MAIN LOGIC" and "MAIN PARTS"? Or should it return no
documents since its not an exact match?
Using the above code, "MAIN" would find neither of those and the
query would have to be exact. I see below you've clarified this
requirement...
To achieve this we used doc.add(Field.Keyword("keywords",
keywords)); and while searching
we cannot use standard analyzer, while searching, as divides the
keywords if we search keywords having space... so we wrote an
KeywordAnalyser(KeywordAnalyzer is basically returns only one
single token) as given below.
There is a KeywordAnalyzer now in the contrib/analyzers codebase, and
it will ship with the next version of Lucene (or you could build it
yourself and use it). There is also a couple of variants of the
KeywordAnalyzer in the Lucene in Action code (www.lucenebook.com).
Which solve the above said problem, but we are not able to the wild
card searchs like MAIN*, etc.
We need both the functionality ie.
1. if user searches for MAIN BOARD, should get only documents that
contain MAIN BOARD and not MAIN LOGIC, MAIN, MAIN PART etc.
2. User should be able to do the wild card search like MAIN*, etc
and get the desired documents.
Please let us know, how we should do the indexing ? and which
analyzer to use to do the search ?
There are many ways to go about this sort of thing, and I apologize
for being short on time and not able to explain them all fully. One
option is to keep the tokenization using a traditional analyzer so
that it separates by whitespace, but when a user queries it turns
into a PhraseQuery. If you really mean for wildcards to be single
words in the field (in other words, users don't need to query on MA*)
then the space separated tokenization would work fine here as well.
It is important to think through the analysis process as well as the
search interface issues (the interface must be given thorough
consideration and treated as a first class citizen when discussing
implementations), especially when wildcard and range queries come
up. It has been a hot topic recently on how to deal with wildcards
and ranges efficiently. In your example, if by "MAIN*" you intend
for the word MAIN to be a unique token and the user would choose a
full word to search upon and merely wants to find it within a larger
field then wildcards are not necessary.
Erik
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