<META HTTP-EQUIV="Content-Type" CONTENT="text/html; charset=gb2312">
<html xmlns:v="urn:schemas-microsoft-com:vml" xmlns:o="urn:schemas-microsoft-com:office:office" xmlns:w="urn:schemas-microsoft-com:office:word" xmlns:m="http://schemas.microsoft.com/office/2004/12/omml" xmlns="http://www.w3.org/TR/REC-html40"><head><meta name=Generator content="Microsoft Word 14 (filtered medium)"><style><!--
/* Font Definitions */
@font-face
{font-family:SimSun;
panose-1:2 1 6 0 3 1 1 1 1 1;}
@font-face
{font-family:SimSun;
panose-1:2 1 6 0 3 1 1 1 1 1;}
@font-face
{font-family:Calibri;
panose-1:2 15 5 2 2 2 4 3 2 4;}
@font-face
{font-family:Tahoma;
panose-1:2 11 6 4 3 5 4 4 2 4;}
@font-face
{font-family:SimSun;
panose-1:2 1 6 0 3 1 1 1 1 1;}
@font-face
{font-family:"Arial Narrow";
panose-1:2 11 6 6 2 2 2 3 2 4;}
@font-face
{font-family:Verdana;
panose-1:2 11 6 4 3 5 4 4 2 4;}
/* Style Definitions */
p.MsoNormal, li.MsoNormal, div.MsoNormal
{margin:0cm;
margin-bottom:.0001pt;
font-size:12.0pt;
font-family:"Times New Roman","serif";}
a:link, span.MsoHyperlink
{mso-style-priority:99;
color:blue;
text-decoration:underline;}
a:visited, span.MsoHyperlinkFollowed
{mso-style-priority:99;
color:purple;
text-decoration:underline;}
span.EmailStyle17
{mso-style-type:personal-reply;
font-family:"Calibri","sans-serif";
color:#1F497D;}
.MsoChpDefault
{mso-style-type:export-only;
font-size:11.0pt;
font-family:"Calibri","sans-serif";}
@page WordSection1
{size:612.0pt 792.0pt;
margin:72.0pt 90.0pt 72.0pt 90.0pt;}
div.WordSection1
{page:WordSection1;}
--></style><!--[if gte mso 9]><xml>
<o:shapedefaults v:ext="edit" spidmax="1026" />
</xml><![endif]--><!--[if gte mso 9]><xml>
<o:shapelayout v:ext="edit">
<o:idmap v:ext="edit" data="1" />
</o:shapelayout></xml><![endif]--></head><body lang=ZH-CN link=blue vlink=purple><div class=WordSection1><p class=MsoNormal><span lang=EN-US style='font-size:10.5pt;font-family:"Calibri","sans-serif";color:#1F497D'>Hi guys, <o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-size:10.5pt;font-family:"Calibri","sans-serif";color:#1F497D'><o:p> </o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-size:10.5pt;font-family:"Calibri","sans-serif";color:#1F497D'>Next time when you make the announcement, please also include the venue and time in case some one forget. For today, the location is SEIEE-03-528, time is 4 PM.<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-size:10.5pt;font-family:"Calibri","sans-serif";color:#1F497D'><o:p> </o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-size:10.5pt;font-family:"Calibri","sans-serif";color:#1F497D'>Kenny<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-size:10.5pt;font-family:"Calibri","sans-serif";color:#1F497D'><o:p> </o:p></span></p><p class=MsoNormal><b><span lang=EN-US style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'>From:</span></b><span lang=EN-US style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'> adapt-bounces@cs.sjtu.edu.cn [mailto:adapt-bounces@cs.sjtu.edu.cn] <b>On Behalf Of </b>Luo Kangqi<br><b>Sent:</b> 2013</span><span style='font-size:10.0pt;font-family:SimSun'>Äê</span><span lang=EN-US style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'>9</span><span style='font-size:10.0pt;font-family:SimSun'>ÔÂ</span><span lang=EN-US style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'>25</span><span style='font-size:10.0pt;font-family:SimSun'>ÈÕ</span><span lang=EN-US style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'> 9:48<br><b>To:</b> Adapt<br><b>Subject:</b> [Adapt] [Adapt Seminar] Semantic Text Similarity<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US><o:p> </o:p></span></p><div><p class=MsoNormal><span lang=EN-US>Hi all,<o:p></o:p></span></p></div><div><p class=MsoNormal><span lang=EN-US><o:p> </o:p></span></p></div><div><p class=MsoNormal><span lang=EN-US>In today's seminar, I'll talk about Semantic Text Similarity.<o:p></o:p></span></p></div><div><p class=MsoNormal><span lang=EN-US><o:p> </o:p></span></p></div><div><p class=MsoNormal><span lang=EN-US>Semantic similarity is a core technique for many topics in natural language processing, such as question answering, semantic searching, and computer-assisted assessment. The task is to compute a similarity score given two natural language texts. Due to the different aspects of understanding for semantic similarity, various methods has been proposed to solve this task. I will present some typical framework to model natural texts, the algorithms to compute the similarity score, and how we evaluate those semantic similarity methods.<o:p></o:p></span></p></div><div><p class=MsoNormal><span lang=EN-US><o:p> </o:p></span></p></div><div><p class=MsoNormal><span lang=EN-US>Cheers,<o:p></o:p></span></p></div><div><p class=MsoNormal><span lang=EN-US>Kangqi<o:p></o:p></span></p></div><div><div><p class=MsoNormal><span lang=EN-US style='font-size:9.0pt;font-family:"Arial Narrow","sans-serif";color:#909090'>------------------<o:p></o:p></span></p></div><div><div><p class=MsoNormal><span lang=EN-US style='font-size:10.5pt;font-family:"Verdana","sans-serif";color:gray'>Luo Kangqi<o:p></o:p></span></p></div><div><p class=MsoNormal><span lang=EN-US style='font-size:10.5pt;font-family:"Verdana","sans-serif";color:gray'>ADAPT Lab, SEIEE 3-341<o:p></o:p></span></p></div><div><p class=MsoNormal><span lang=EN-US style='font-size:10.5pt;font-family:"Verdana","sans-serif";color:gray'>Shanghai Jiao Tong University<o:p></o:p></span></p></div></div></div><div><p class=MsoNormal><span lang=EN-US> <o:p></o:p></span></p></div></div></body></html>