similar to: Setting the boost field after indexing

I''ve been trying to implement acts_as_ferret in my latest project and ran into a snag. If I do a search for ''auditor state'' then the search works perfectly. If I include a stop word, as in ''auditor of state'', then I get no results. I''d prefer not to set stop words to nil and index everything. The solution, that I have yet to attempt, is to use

Hi, I''m confused about managing field boosting ... I have set the :boost for the :name field in my docs to 10, via :boost => 10 Then I performed a search for ''keith'' over all fields via with *:(keith*), expecting a doc with Keith in the :name field to come out on top. But another doc with Keith mentioned in other fields (:comments, :address) scored higher. I

Hi, I have a model which has properties, these are your standard name/value pairs, but also have attributes that affect how I want to store them in ferret. I was using 0.9.5 with 0.2 of aaf, which seemed fine, I just copied and pasted (yes, I know, ick) the to_doc method and added code to iterate though the properties that that model had, and add relavent fields to the document. It seems

I''m making a simple business directory search and I want to boost the relevance of the ''name'' field over the ''address'' field - both stored in the same document in the same index. Here is some console code to demonstrate what I am actually doing >> include Ferret::Document => Object >> doc = Document.new => Document { } >> doc

I am wondering whether one could boost certain fields (e.g., title and keywords) to make them ''weigh'' more against searches across all fields. I know that Document::Field has a boost attribute and that it accepts a boost argument in the constructor (although I''ve had not much luck with it, I am just getting back exceptions upon init w/ boost), but I was wondering

Lucene, and perhaps most search engines, are biased towards small fields with little content (where thus the term frequency is higher). Lucene has the option to define a custom (Similarity) class to calculate the similarity between two fields (custom calculation of lengthNorm and tf) in different documents. But how do I do this in ferret? (I know to boost a field, but this is not what I

I have this model: class Post < ActiveRecord::Base acts_as_ferret :fields => { :title => {:boost => 2}, :description => {}, :url => {}, :rank_sort => {:index => :untokenized_omit_norms, :term_vector => :no},

Sorry if this is a repost- I wasn''t sure if the www.ruby-forum.com list works for postings. I''ve been having trouble with indexing a large amount of documents(2.4M). Essentially, I have one process that is following the tutorial dumping documents to an index stored on the file system. If I open the index with another process, and run the size() method it is stuck at a number

Hi! I thought I understood Ferret''s query scoring and how to tweak results using boost values. What I currently experience however, leaves me completely baffled. Perhaps someone can shed some light on the scoring algorithm, because asking Ferret to "explain" the score for a particular document isn''t as informative as I thought. Actually, it confuses me even

Is it possible to query the index for a TermEnum for all fields in the index instead of just ? Thanks, John

Hi I am using boosting for a classification and prediction problem. For some reason it is giving me an outcome that doesn't fall between 0 and 1 for the predictions. I have tried type="response" but it made no difference. Can anyone see what I am doing wrong? Screen output shown below: > boost.model <- gbm(as.factor(train$simNuance) ~ ., # formula +

Hello, does any one know how to interpret this output in R? > Classification with logitboost > fit <- logitboost(xlearn, ylearn, xtest, presel=50, mfinal=20) > summarize(fit, ytest) Minimal mcr: 0 achieved after 6 boosting step(s) Fixed mcr: 0 achieved after 20 boosting step(s) What is "mcr" mean? Thanks [[alternative HTML version deleted]]

I''m using acts_as_ferret to index one of my rails models. Right after I start the app the first request that orders by some ferret field will take very long. Subsequent ones seem to be fast. I guess some caching is going on. Any tips on solving this? Pedro.

Last week we noticed that the default scheduler isn't being set properly in CentOS 7. I haven't checked this for CentOS 6, but it might be worth exploring. The TL;DR is unless you're running CentOS 7 on a laptop or as a virtual guest, you should probably run 'tuned-adm profile throughput-performance' I wrote up the full details here ->

There was errors when I tried to start the script recommended by Andrew to boost bandwidth for voip http://www.mixdown.ca/~andrew/dump/rc.tc. This is the output I get : ./rc.tc start RTNETLINK answers: File exists RTNETLINK answers: File exists RTNETLINK answers: File exists RTNETLINK answers: File exists RTNETLINK answers: File exists RTNETLINK answers: File exists RTNETLINK answers: File

The BGL (Boost Graph Library) defines tie(), which is exactly what the tie() defined in STLExtras.h. The header files of GBL use boost::tie(), and other boost libraries use boost::tie() too. How to resolve the ambiguity for compiler? -- Tzu-Chien Chiu, 3D Graphics Hardware Architect <URL:http://www.csie.nctu.edu.tw/~jwchiu>

On Thu, 22 Sep 2005, Tzu-Chien Chiu wrote: > On 22/09/05, Bill Wendling <isanbard at gmail.com> wrote: >> Couldn't you state the explicit namespaces. So not using "using >> namespace llvm" and instead prefix all calls with "llvm::"? > > The header files in boost do not use fully-qualified tie(). I probably > should not modify them. But my .cpp

On 22/09/05, Bill Wendling <isanbard at gmail.com> wrote: > Couldn't you state the explicit namespaces. So not using "using > namespace llvm" and instead prefix all calls with "llvm::"? The header files in boost do not use fully-qualified tie(). I probably should not modify them. But my .cpp file #include them. I hope I could "using namespace" boost

Hi all, first off, it''s 2AM and I''m not thinking properly, so please forgive me if this one''s easy, but I just need to get this going. First problem, using 0.9.6 on all of our development machines, works great, then we move it to a server running x86_64 linux and it segfaults as soon as it tries to create an Index. I''ve tried rebuilding with different

Just a quick note for future reference - at least for me, ferret won''t work on Ruby 1.8.4. gem install ferret Successfully installed ferret-0.11.4-mswin32 ruby -v ruby 1.8.4 (2005-12-24) [i386-mswin32] irb irb(main):001:0> require ''ferret'' A windows error message box appears - ruby.exe - Entry Point Not Found The procedure entry point rb_w32_write could not be