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| = About character encoding = | #acl All:read |
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| In general we use UTF-8 as default character encoding. | = CompleteSearch = |
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| The AC->settings->encoding is 'utf-8' unless overriden in autocomplete_config.php The text.php is saved as UTF-8 The css file uses '@charset "utf-8";' |
[[MpiiWiki|Old Wiki from the MPII]] (lots of detailed / internal information) |
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| We have to support other encodings like iso-8859-1 because some collections are not utf-8 encoded. | == Quick Intro == |
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| Follow these steps to checkout the !CompleteSearch code from our SVN, build it, build an index, run a server on that index, and ask queries to that server via HTTP. Don't be afraid, it's easy. If you have questions, send an email to Hannah Bast <bast@informatik.uni-freiburg.de>. | |
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== UTF-8 lowercase in PHP (23May07 Markus) == Requires extension mbstring (for functions like mb_strtolower). Following line required in php.ini |
=== 0. Get source code === |
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| In windows: extension=php_mbstring.dll or in linux: extension=php_mbstring.so |
svn checkout http://vulcano.informatik.uni-freiburg.de/svn/completesearch/codebase Username: [ask us] Password: [ask us] |
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| (On geek, the mb_... functions were available by default, on Markus's laptop the line above had to be added.) | === 1. Compile === |
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| {{{ make all }}} |
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| == Texts in text.php are now UTF-8 encoded (23May07 Markus) == | This will build three binaries: * buildIndex * buildDocsDB * startCompletionServer If you call any of these binaries without parameters you will get usage info with all the available options. === 2. Input (to be produced by a suitable parser) === Ínput 1: a file ''<base-name>.words'', with lines of the form {{{ <word><TAB><doc id><TAB><score><TAB><position> }}} This file must be sorted such that ''sort -c -k1,1 -k2,2n -k4,4n'' does not complain. Input 2: a file ''<base-name>.docs'', with lines of the form <doc id><TAB>u:<url of document><TAB>t:<title of document><TAB>H:<raw text of document> This file must be sorted so that ''sort -c -k1,1n'' does not complain. You find a very simple example under http://www.mpi-inf.mpg.de/~bast/topsecret/example.tgz === 3. Build the word index === {{{ buildIndex HYB <base-name>.words }}} This produces the (binary) index file ''<base-name>.hybrid''. It enables fast processing of the powerful query language offered by CompleteSearch (including full-text search, prefix search and completion, synonym search, error-tolerant search, etc.). ''buildIndex'' also produces the file ''<base-name>.vocabulary'' that provides the mapping from word ids to words. This is an ASCII file, you can just look at it. Note that by default, the HYB index is built with block of fixed sizes. It is more efficient though to pass it an explicit list of block boundaries (-B option). TODO: say something about this here, it's actually quite easy. === 4. Build the doc index === {{{ buildDocsDB <name>.docs }}} This produces the (binar) file ''<base-name>.docs.DB'' which provides an efficient mapping from doc ids to documents. This is needed if you want to show excerpts / snippets from documents matching the query (which is almost always the case). === 5. Start server === startCompletionServer -Z <name>.hybrid This starts the server. If you run it without argument, it prints usage information. The -Z argument lets the server run in the foreground, and output everything to the console, which is convenient for testing. 6. Queries The server listens on the port you specified in step 6 (8888 by default), and speaks HTTP. For example: curl "http://localhost:8888/?q=die*&h=1&c=3" This will return the result as an XML, which should be self-explanatory. Here is the list of parameters which you may pass along with the query (q=...) h : number of hits c : number of completions (of last query word, if you put a * behind it) f : send hits starting from this one (default: 0) en : number of excerpts per hit er : size of excerpt rd : how to rank the documents (0 = by score, 1 = by doc id, 2 = by word id, append a or d for ascending or descending) rw : how to rank the words (0 = by score, 1 = by doc count, 2 = by occurrence count, 3 = by word id, 4 = by doc id, append a or d as above) s : how to aggregate scores (expert option, ignore for the moment) Jede Menge Doku auf http://search.mpi-inf.mpg.de/wiki/CompleteSearch |
CompleteSearch
Old Wiki from the MPII (lots of detailed / internal information)
Quick Intro
Follow these steps to checkout the CompleteSearch code from our SVN, build it, build an index, run a server on that index, and ask queries to that server via HTTP. Don't be afraid, it's easy. If you have questions, send an email to Hannah Bast <bast@informatik.uni-freiburg.de>.
0. Get source code
svn checkout http://vulcano.informatik.uni-freiburg.de/svn/completesearch/codebase Username: [ask us] Password: [ask us]
1. Compile
make all
This will build three binaries:
- buildIndex
- buildDocsDB
- startCompletionServer
If you call any of these binaries without parameters you will get usage info with all the available options.
2. Input (to be produced by a suitable parser)
Ínput 1: a file <base-name>.words, with lines of the form
<word><TAB><doc id><TAB><score><TAB><position>
This file must be sorted such that sort -c -k1,1 -k2,2n -k4,4n does not complain.
Input 2: a file <base-name>.docs, with lines of the form
<doc id><TAB>u:<url of document><TAB>t:<title of document><TAB>H:<raw text of document>
This file must be sorted so that sort -c -k1,1n does not complain.
You find a very simple example under http://www.mpi-inf.mpg.de/~bast/topsecret/example.tgz
3. Build the word index
buildIndex HYB <base-name>.words
This produces the (binary) index file <base-name>.hybrid. It enables fast processing of the powerful query language offered by CompleteSearch (including full-text search, prefix search and completion, synonym search, error-tolerant search, etc.).
buildIndex also produces the file <base-name>.vocabulary that provides the mapping from word ids to words. This is an ASCII file, you can just look at it.
Note that by default, the HYB index is built with block of fixed sizes. It is more efficient though to pass it an explicit list of block boundaries (-B option). TODO: say something about this here, it's actually quite easy.
4. Build the doc index
buildDocsDB <name>.docs
This produces the (binar) file <base-name>.docs.DB which provides an efficient mapping from doc ids to documents. This is needed if you want to show excerpts / snippets from documents matching the query (which is almost always the case).
5. Start server
startCompletionServer -Z <name>.hybrid
This starts the server. If you run it without argument, it prints usage information. The -Z argument lets the server run in the foreground, and output everything to the console, which is convenient for testing.
6. Queries
The server listens on the port you specified in step 6 (8888 by default), and speaks HTTP. For example:
curl "http://localhost:8888/?q=die*&h=1&c=3"
This will return the result as an XML, which should be self-explanatory.
Here is the list of parameters which you may pass along with the query (q=...)
h : number of hits c : number of completions (of last query word, if you put a * behind it) f : send hits starting from this one (default: 0) en : number of excerpts per hit er : size of excerpt rd : how to rank the documents (0 = by score, 1 = by doc id, 2 = by word id, append a or d for ascending or descending) rw : how to rank the words (0 = by score, 1 = by doc count, 2 = by occurrence count, 3 = by word id, 4 = by doc id, append a or d as above) s : how to aggregate scores (expert option, ignore for the moment)
Jede Menge Doku auf http://search.mpi-inf.mpg.de/wiki/CompleteSearch