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<div>An alternate interface for the Google Books n-grams is at:</div>
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<div><a href="http://googlebooks.byu.edu/" target="_blank">http://googlebooks.byu.edu/</a></div>
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<div>This interface allows you to search by part of speech, lemma, synonyms, collocates, and to compare results across different portions of the n-grams datasets. For a comparison of this interface and the standard Google Books n-grams interface, see:</div>
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<div><a href="http://googlebooks.byu.edu/compare-googleBooks.asp" target="_blank" title="http://googlebooks.byu.edu/compare-googleBooks.asp
Cmd+Click to follow link" style="font-size: 12pt;">http://googlebooks.byu.edu/compare-googleBooks.asp</a> </div>
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<div>Also, just a few quick links to show what type of displays one can get from the data:</div>
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<div><a href="http://googlebooks.byu.edu/?c=us&q=26566890" target="_blank">http://googlebooks.byu.edu/?c=us&q=26566890</a></div>
<div>All matching strings, by decade</div>
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<div><a href="http://googlebooks.byu.edu/?c=us&q=26566893" target="_blank">http://googlebooks.byu.edu/?c=us&q=26566893</a></div>
<div>Overall frequency of all matching strings, by decade</div>
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<div><a href="http://googlebooks.byu.edu/?c=us&q=26566903" target="_blank">http://googlebooks.byu.edu/?c=us&q=26566903</a></div>
<div>Matching strings for just one part of the corpus (here, 199os-2000)</div>
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<div>Best,</div>
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<div>Mark Davies</div>
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<p>============================================<br>
Mark Davies<br>
Professor of Linguistics / Brigham Young University<br>
<a tabindex="0" href="http://davies-linguistics.byu.edu/">http://davies-linguistics.byu.edu/</a></p>
<p>** Corpus design and use // Linguistic databases **<br>
** Historical linguistics // Language variation **<br>
** English, Spanish, and Portuguese **<br>
============================================<br>
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<div id="divRpF592988" style="direction: ltr;"><font face="Tahoma" size="2" color="#000000"><b>From:</b> corpora-bounces@uib.no [corpora-bounces@uib.no] on behalf of tg [beijixingboy@hotmail.com]<br>
<b>Sent:</b> Wednesday, November 13, 2013 1:44 AM<br>
<b>To:</b> corpora@uib.no<br>
<b>Subject:</b> [Corpora-List] Questions for Google syntactic N-grams corpus<br>
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<p class="MsoNormal"><font size="3"><a name="OLE_LINK63"></a><a name="OLE_LINK58"></a><a name="OLE_LINK57"><span lang="EN-US" style="background-color:white">Hi, dear all,</span></a></font></p>
<p class="MsoNormal"><font size="3"><a name="OLE_LINK57"><span lang="EN-US" style="background-color:white"><br>
</span></a></font></p>
<p class="MsoNormal" align="left"><font size="3"><a name="OLE_LINK59"><span lang="EN-US">I am extremely interested in the new edition of Google N-grams corpus.My research topic is using the sentence dependence parsing skill to mining the web scale textual corpus
for semantics understanding.</span></a></font></p>
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<p class="MsoNormal" align="left"><font size="3"><span lang="EN-US" style="color:rgb(68,68,68)">And I want to ask two questions as following,</span><span lang="EN-US"></span></font></p>
<p class="MsoNormal" align="left"><font size="3"><span lang="EN-US" style="color:rgb(68,68,68)"><br>
</span></font></p>
<p class="MsoNormal" align="left"><font size="3"><span lang="EN-US" style="color:rgb(68,68,68)">Q1: how to use this large scale data? Is there any existing tools, e.g. indexing and search tools like lucene (maybe not available for this big data)? Any other
index tools?</span></font></p>
<p class="MsoNormal" align="left"><font size="3"><span lang="EN-US" style="color:rgb(68,68,68)"><br>
</span></font></p>
<span lang="EN-US" style="color:rgb(68,68,68)"><font size="3">Q2: I want to extract the typical triplets dependent relations (S-V-O, e.g. "lion - chase - zebra"), could you help me for how to do this efficiently?</font></span><br>
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<p style="line-height:21.81818199157715px; color:rgb(68,68,68); font-family:'Microsoft YaHei UI','Microsoft YaHei',宋体,Calibri,sans-serif; font-size:15.454545021057129px">
Gang Tian | Phd Student</p>
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School of Information Technologies | Faculty of Engineering & IT</p>
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THE UNIVERSITY OF SYDNEY</p>
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