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 Full
Text
Search
Sarah
Allen

@ultrasaurus
class Article < ActiveRecord::Base
  acts_as_solr
end
3
Tokyo
Dystopia
Language
Relevance
Accuracy
 Speed
Text as Language
stemming
   synonyms
  stop
words
word
boundaries
SELECT text FROM phrases WHERE text like '%run%';

 Can you run this to the post office for me?
 I'm going for a run, want to come along?
 Cross country running
 I'm too drunk to drive.
 I am running out of battery power.
 Work is not like wolf - it won't run away.
SELECT text FROM phrases WHERE
            vectors @@ 'run'::tsquery;

 Can you run this to the post office for me?
 Sorry I am running really late.
 I'm going for a run, want to come along?
 Cross country running
 I am running out of battery power.
 Work is not like wolf - it won't run away.
Tokenization and Stemming
Google App Engine /JRuby / Lucene

http://full-text-search.appspot.com

http://

github.com/
ultrasaurus/
full-text-search-appengine
hAp://full‐text‐search.appspot.com/




                                      16
hAp://full‐text‐search.appspot.com/




                                      17
hAp://full‐text‐search.appspot.com/




                                      18
hAp://localhost:8080/_ah/admin/datastore?kind=Notes




                                                      19
./script/generate scaffold note
   content:string index:List -f --skip-migration

./script/generate dd_model note content:string index:List -f
class Note
 include DataMapper::Resource

 property :id,   Serial
 property :content, String,      :required => true, :length => 500
 property :index, List,       :required => true
 timestamps :at

end
java_import org.apache.lucene.analysis.snowball.SnowballAnalyzer
java_import java.io.StringReader
before :valid?, :update_index

def update_index
 analyzer = SnowballAnalyzer.new("English")
 s = StringReader.new(content)
 token_stream = analyzer.tokenStream(nil, s)

 terms = []
 while (token = token_stream.next) do
   terms << token.term
 end
 self.index = terms
end
before :valid?, :update_index

def update_index
 analyzer = SnowballAnalyzer.new("English")
 s = StringReader.new(content)
 token_stream = analyzer.tokenStream(nil, s)

 terms = []
 while (token = token_stream.next) do
   terms << token.term
 end
 self.index = terms
end
hAp://full‐text‐search.appspot.com/




                                      25
a about above after again against all am an and any are
    aren't as at be because been before being below between
   both but by can't cannot could couldn't did didn't do does
doesn't doing don't down during each few for from further had
   hadn't has hasn't have haven't having he he'd he'll he's her
 here here's hers herself him himself his how how's i i'd i'll i'm
i've if in into is isn't it it's its itself let's me more most mustn't
  my myself no nor not of off on once only or other ought our
    ours ourselves out over own same shan't she she'd she'll
 she's should shouldn't so some such than that that's the their
    theirs them themselves then there there's these they they'd
  they'll they're they've this those through to too under until up
 very was wasn't we we'd we'll we're we've were weren't what
   what's when when's where where's which while who who's
  whom why why's with won't would wouldn't you you'd you'll
             you're you've your yours yourself yourselves

           http://www.ranks.nl/resources/stopwords.html
Word Boundaries












        
















        
          





        
     








        
















        
          





        
     





        
   
 I
love
horses 




        
















        
             





        
        





        
   
 I
love
horses 




        
















        
             





        
        





        
   
 I
love
horses 




        

Horses
are
beauSful














        
             





        
        





        
   
 I
love
horses 




        

Horses
are
beauSful














        
             





        
        





           
   
 I
love
horses 




           

Horses
are
beauSful

                               







   deer
in
the
forest




           
             





           
        





           
   
 I
love
horses 




           

Horses
are
beauSful

                               







   deer
in
the
forest




           
             





           
        





           
   
 I
love
horses 




           

Horses
are
beauSful

                              







   deer
in
the
forest




           
             








deer
live
in
the
woods


           
        





           
   
 I
love
horses 




           

Horses
are
beauSful

                              







   deer
in
the
forest




           
             








deer
live
in
the
woods





           
        





           
   
 I
love
horses 




           

Horses
are
beauSful

                              







   deer
in
the
forest




           
             








deer
live
in
the
woods





           
        





           
   
 I
love
horses




           

Horses
are
beauSful

                              







   deer
in
the
forest




           
            








deer
live
in
the
woods





           
        








You
are
an
idiot.


Relevance
Accuracy
Speed
Write
                   Hosted
Database
                   Search



           Rails
Read
                   Hosted
Database
                   Search



           Rails
Target                                     Target     Source
Text                                       Language   Language

We’re
running
out
of
daylight              en         ja

Could
you
run
this?                        en         ja

Cross‐country
running                      en         ja

I’m
going
for
a
run,
want
to
come
along?   en         ja
I’m
going
for
a
run,
want
to
come
along?   en   ja
I’m
going
for
a
run,
want
to
come
along?   en   ja




                                

I’m
going
for
a
run,
want
to
come
along?    en   ja




                                       

ha
shi
ri
ni
iku
ke
do
iAtsho
ni
ki
ma
su
ka?
I’m
going
for
a
run,
want
to
come
along?    en   ja




                                       

ha
shi
ri
ni
iku
ke
do
iAtsho
ni
ki
ma
su
ka?
Ikuko
Kobayashi
I’m
going
for
a
run,
want
to
come
along?    en   ja




                                       

ha
shi
ri
ni
iku
ke
do
iAtsho
ni
ki
ma
su
ka?
Ikuko
Kobayashi
2009‐11‐29
20:36:47
UTC
I’m
going
for
a
run,
want
to
come
along?    en   ja




                                       

ha
shi
ri
ni
iku
ke
do
iAtsho
ni
ki
ma
su
ka?
Ikuko
Kobayashi
2009‐11‐29
20:36:47
UTC
hAp://….16ec695a‐8fce‐4277‐bdd4.flv
I’m
going
for
a
run,
want
to
come
along?    en   ja




                                       

ha
shi
ri
ni
iku
ke
do
iAtsho
ni
ki
ma
su
ka?
Ikuko
Kobayashi
2009‐11‐29
20:36:47
UTC
hAp://….16ec695a‐8fce‐4277‐bdd4.flv
hAp://….Japanese_ikuko_kobayashi.jpg
62
class Page < ActiveRecord::Base
  acts_as_tsearch :fields => [ ... ]
end
Page.send :acts_as_tsearch, :fields => [:title]
PagePart.send :acts_as_tsearch, :fields =>
  [:content]
ProgramPropertyList.send :acts_as_tsearch,
  :fields
  =>[:instructor, :program_desc,
  :program_detail, :resource]
@pages
=
Page.find_by_tsearch(@query)
66
69
70
71
class Phrase < ActiveRecord::Base
  acts_as_tsearch :fields => [:text]
end
Phrase.find_by_tsearch(term,
  :conditions => {:language_id =>
                   target_language.id})
When you think about
     search...
Questions?

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Full text search adventures

  • 1. Adventures
 in
 Full
Text
Search Sarah
Allen

@ultrasaurus
  • 2. class Article < ActiveRecord::Base acts_as_solr end
  • 3. 3
  • 4.
  • 5.
  • 6.
  • 7.
  • 11. stemming synonyms stop
words word
boundaries
  • 12. SELECT text FROM phrases WHERE text like '%run%';  Can you run this to the post office for me? I'm going for a run, want to come along?  Cross country running  I'm too drunk to drive.  I am running out of battery power.  Work is not like wolf - it won't run away.
  • 13. SELECT text FROM phrases WHERE vectors @@ 'run'::tsquery;  Can you run this to the post office for me?  Sorry I am running really late. I'm going for a run, want to come along?  Cross country running  I am running out of battery power.  Work is not like wolf - it won't run away.
  • 14.
  • 15. Tokenization and Stemming Google App Engine /JRuby / Lucene http://full-text-search.appspot.com http:// github.com/ ultrasaurus/ full-text-search-appengine
  • 20. ./script/generate scaffold note content:string index:List -f --skip-migration ./script/generate dd_model note content:string index:List -f
  • 21. class Note include DataMapper::Resource property :id, Serial property :content, String, :required => true, :length => 500 property :index, List, :required => true timestamps :at end
  • 23. before :valid?, :update_index def update_index analyzer = SnowballAnalyzer.new("English") s = StringReader.new(content) token_stream = analyzer.tokenStream(nil, s) terms = [] while (token = token_stream.next) do terms << token.term end self.index = terms end
  • 24. before :valid?, :update_index def update_index analyzer = SnowballAnalyzer.new("English") s = StringReader.new(content) token_stream = analyzer.tokenStream(nil, s) terms = [] while (token = token_stream.next) do terms << token.term end self.index = terms end
  • 26. a about above after again against all am an and any are aren't as at be because been before being below between both but by can't cannot could couldn't did didn't do does doesn't doing don't down during each few for from further had hadn't has hasn't have haven't having he he'd he'll he's her here here's hers herself him himself his how how's i i'd i'll i'm i've if in into is isn't it it's its itself let's me more most mustn't my myself no nor not of off on once only or other ought our ours ourselves out over own same shan't she she'd she'll she's should shouldn't so some such than that that's the their theirs them themselves then there there's these they they'd they'll they're they've this those through to too under until up very was wasn't we we'd we'll we're we've were weren't what what's when when's where where's which while who who's whom why why's with won't would wouldn't you you'd you'll you're you've your yours yourself yourselves http://www.ranks.nl/resources/stopwords.html
  • 30. 


 

 








 
 


 
 


  • 31. 


 

 








 
 


 
 


  • 32. 

 
 
 I
love
horses 

 

 








 
 


 
 


  • 33. 

 
 
 I
love
horses 

 

 








 
 


 
 


  • 34. 

 
 
 I
love
horses 

 

Horses
are
beauSful 








 
 


 
 


  • 35. 

 
 
 I
love
horses 

 

Horses
are
beauSful 








 
 


 
 


  • 36. 

 
 
 I
love
horses 

 

Horses
are
beauSful 
 





 deer
in
the
forest 
 


 
 


  • 37. 

 
 
 I
love
horses 

 

Horses
are
beauSful 
 





 deer
in
the
forest 
 


 
 


  • 38. 

 
 
 I
love
horses 

 

Horses
are
beauSful 
 





 deer
in
the
forest 
 








deer
live
in
the
woods 
 


  • 39. 

 
 
 I
love
horses 

 

Horses
are
beauSful 
 





 deer
in
the
forest 
 








deer
live
in
the
woods


 
 


  • 40. 

 
 
 I
love
horses 

 

Horses
are
beauSful 
 





 deer
in
the
forest 
 








deer
live
in
the
woods


 
 


  • 41. 

 
 
 I
love
horses

 

Horses
are
beauSful 
 





 deer
in
the
forest 
 








deer
live
in
the
woods


 
 








You
are
an
idiot.


  • 43.
  • 44.
  • 45.
  • 46.
  • 48. Speed
  • 49.
  • 50.
  • 51. Write Hosted Database Search Rails
  • 52. Read Hosted Database Search Rails
  • 53.
  • 54. Target Target Source Text Language Language We’re
running
out
of
daylight en ja Could
you
run
this? en ja Cross‐country
running en ja I’m
going
for
a
run,
want
to
come
along? en ja
  • 57. I’m
going
for
a
run,
want
to
come
along? en ja 
 ha
shi
ri
ni
iku
ke
do
iAtsho
ni
ki
ma
su
ka?
  • 58. I’m
going
for
a
run,
want
to
come
along? en ja 
 ha
shi
ri
ni
iku
ke
do
iAtsho
ni
ki
ma
su
ka? Ikuko
Kobayashi
  • 59. I’m
going
for
a
run,
want
to
come
along? en ja 
 ha
shi
ri
ni
iku
ke
do
iAtsho
ni
ki
ma
su
ka? Ikuko
Kobayashi 2009‐11‐29
20:36:47
UTC
  • 60. I’m
going
for
a
run,
want
to
come
along? en ja 
 ha
shi
ri
ni
iku
ke
do
iAtsho
ni
ki
ma
su
ka? Ikuko
Kobayashi 2009‐11‐29
20:36:47
UTC hAp://….16ec695a‐8fce‐4277‐bdd4.flv
  • 61. I’m
going
for
a
run,
want
to
come
along? en ja 
 ha
shi
ri
ni
iku
ke
do
iAtsho
ni
ki
ma
su
ka? Ikuko
Kobayashi 2009‐11‐29
20:36:47
UTC hAp://….16ec695a‐8fce‐4277‐bdd4.flv hAp://….Japanese_ikuko_kobayashi.jpg
  • 62. 62
  • 63. class Page < ActiveRecord::Base acts_as_tsearch :fields => [ ... ] end
  • 64. Page.send :acts_as_tsearch, :fields => [:title] PagePart.send :acts_as_tsearch, :fields => [:content] ProgramPropertyList.send :acts_as_tsearch, :fields =>[:instructor, :program_desc, :program_detail, :resource]
  • 66. 66
  • 67.
  • 68.
  • 69. 69
  • 70. 70
  • 71. 71
  • 72. class Phrase < ActiveRecord::Base acts_as_tsearch :fields => [:text] end
  • 73. Phrase.find_by_tsearch(term, :conditions => {:language_id => target_language.id})
  • 74.
  • 75. When you think about search...
  • 76.

Notas del editor

  1. Photo source: http://www.flickr.com/photos/9mohamed0/4268238013/sizes/o/\n
  2. \n
  3. \n
  4. Photo source: http://www.flickr.com/photos/zehfernando/3457455680/\n
  5. Photo source: http://www.flickr.com/photos/bevvell/4649795989/in/pool-97958286@N00\n
  6. Photo source: http://www.flickr.com/photos/caveman_92223/2763166886/\n
  7. Photo source: http://www.flickr.com/photos/lochaven/2588186224/\n
  8. Postgres: In database &amp;#x201C;tsvector&amp;#x201D; , partial indexes, acts_as_tsearch\n\nMySql FULLTEXT indices are fully indexed fields which support stopwords, boolean searches, and relevancy ratings: http://onlamp.com/pub/a/onlamp/2003/06/26/fulltext.html\nNote: MySql FULLTEXT requires MyISAM storage engine\nComparison of MySql vs. PostgresQL: http://www.wikivs.com/wiki/MySQL_vs_PostgreSQL\n\nSolr/Lucene: Separate Index, Language Features: Faceted Search, Similar Documents (you may also like&amp;#x2026;)\nSphinx typically installed on the same machine, directly accessed your database\n
  9. \n
  10. \n
  11. Word boundaries understood by context in: Chinese, Japanese, Korean, Thai\nCJK word boundaries not handled in MySql 5: http://blogs.sun.com/soapbox/entry/fulltext_and_asian_languages_with\n
  12. \n
  13. \n
  14. Rethinking Full-Text Search for Multilingual DatabasesJeffrey Sorensen and Salim Roukos IBM T. J. Watson Research Center Yorktown Heights, New York &lt;sorenj|roukos&gt;@us.ibm.com\n
  15. \n
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  18. \n
  19. \n
  20. \n
  21. \n
  22. \n
  23. \n
  24. \n
  25. \n
  26. Stop words can cause problems when using a search engine to search for phrases that include them, particularly in names such as &apos;The Who&apos;, &apos;The The&apos;, or &apos;Take That&apos;\nhttp://en.wikipedia.org/wiki/Stop_words\n
  27. \n
  28. \n
  29. \n
  30. \n
  31. \n
  32. \n
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  34. \n
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  36. \n
  37. \n
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  39. \n
  40. \n
  41. \n
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  43. \n
  44. \n
  45. \n
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  48. Photo source: http://www.flickr.com/photos/thatguyfromcchs08/2300190277/\n
  49. Photo source: http://www.flickr.com/photos/stuckincustoms/4443168109/sizes/l/\n
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  76. think of a blank canvas... don&amp;#x2019;t think about Solr or Sphinx, first think about what people are trying to find and what will help them most. \nMaybe browse is more im\n
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