Hi,
I'm using lucene 4.8.1 an try to get the MLT to give certain fields a
bigger weight in the similarity calculation. Is this even possible? I
only saw that I can give a boost to the MLTQuery itself, but not to a
field. Has anybody any idea?
Regards,
Jürgen.
--
Jürgen Albert
Geschäftsfüh
> IndexReader reader = IndexReader.open(index);
> >
> > IndexSearcher searcher = new IndexSearcher(reader);
> >
> > // get similar doc
> > // Reader sReader = new StringReader();
> > MoreLikeThis mlt = new MoreLikeThis(reader);
> > // -
>double Score = hits[i].score
>
>
>
> }
>
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>
> On Fri, Jul 18, 2014 at 7:34 PM, Ian Lea wrote:
>
>> You need to supply more info. Tell us what version of lucene you are
>> using and
stead.
>
>
> --
> Ian.
>
>
> On Fri, Jul 18, 2014 at 11:50 AM, Rajendra Rao
> wrote:
> > Hello
> >
> >
> > I am using more like this query .But size of Score Docs i am getting is 0
> > I found that it
> > In Query Searchedquery = mlt.like
llo
>
>
> I am using more like this query .But size of Score Docs i am getting is 0
> I found that it
> In Query Searchedquery = mlt.like(reader1, "criteria");
>
> query object contain following value
> boost 1.0
> all clauses element data is null
>
>
&g
Hello
I am using more like this query .But size of Score Docs i am getting is 0
I found that it
In Query Searchedquery = mlt.like(reader1, "criteria");
query object contain following value
boost 1.0
all clauses element data is null
I used following code
MoreLikeThis mlt = new Mo
I have been looking over the more like this code. It looks like, in the
code, the more like this query simply does more like this based on the
first of the fields, and fails to consider the rest. Thus, if I have
title and body indexed for some document, it will do the more like this
based only
> For example, given terms "female", "John" and "London" - all 3 may
> have equal IDF but should a document representing a female in London
> be given equal weighting to a document representing the rarer example
> of a female who happens to be called "John"?
Not to mention multi-word phrase tokeni
adds extra complexity/cost but
might be an interesting avenue to explore for some apps when selecting
distinguishing characteristics or weighting query results.
Cheers
Mark
- Original Message
From: karl wettin <[EMAIL PROTECTED]>
To: java-user@lucene.apache.org
Sent: Friday, 9
I just woke up thinking it would be cool to attempt reducing the data
of all documents using PCA (or so) and store the output in a new
field per dimention introduced in order to find similair documents by
placing a simple proximity query. Did anyone attempt something like
this?
I did not
You're soo right! I'm totally new to lucene (and text analyses,
searching etc), but now that you showed me I "get it". Thank you so
much for your reply.
Chad
On Aug 8, 2006, at 12:45 AM, Chris Hostetter wrote:
I've never used MoreLikeThis myself, but based on how i know it works,
your
I've never used MoreLikeThis myself, but based on how i know it works,
your problem probably has more to do with the size of your test corpus and
th frequency of the words in your docs then by the size of the docs
themselves.
: There's still the issue of the queries from MoreLikeThis not
: return
Thank you Erick, that was what I anticipated would be necessary.
There's still the issue of the queries from MoreLikeThis not
returning results for terms I had expected ("bikes").
For example, I have these four very short documents:
"bikes are a handy tool for getting from diffrent locations
Well, I expect that defining "less common" is tricky and doesn't lend itself
to a canned answer . Would it work to create your own list of stop words
(possibly very large) to use for indexing and/or searching? This would
simply exclude the "less common" words (as you define them).
StandardAnalyzer
hi all,
I'm new to lucene but I'm loving it! I'm writing a prototype that
links documents together based upon similarities. Obviously the
first thing I did was use MoreLikeThis. However, it seems to be
finding matches based upon words that are too common, in this case
the words "from"
On 22 Oct 2005, at 20:20, [EMAIL PROTECTED] wrote:
Can someone point me to where I can find this class?
It exists in Lucene's Subversion repository under contrib/similarity.
Erik
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Hi All-
Can someone point me to where I can find this class?
Thanks!
-Joe
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