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  4. <title>CSE 628 Introduction to Natural Language Processing Fall 2010</title>
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    7. 

  7. <h1><center>CSE 628 Introduction to Natural Language Processing</center></h1> 
    8. 

  8. <h2><center>Fall 2010</center></h2>
    9. 

  9. <h3><center>Mon <font color="red">11:40am</font> - 12:40pm, Wed <font 
    10. 

  10. color="red">11:10am</font> - 12:40pm at [CS-2129]</center></h3>
    11. 

  11. <br>
    12. 

  12. 

  13. <h4>Instructor:</h4> 
    14. 

  14. <ul type="circle">
    15. 

  15. <a href="http://www.cs.stonybrook.edu/~ychoi/">Yejin Choi</a>&nbsp;(email: ychoi@cs, 
    16. 

  16. office: 
    17. 

  17. CS-1422, <font color="blue"><b>Office Hours: Mon/Wed 2:30pm - 3:30pm</b></font>) <br>
    18. 

  18. </ul>
    19. 

  19. 

  20. <h4>Course Description:</h4>
    21. 

  21. 

  22. <ul type="circle">
    23. 

  23. <li>This course intends to provide a general introduction to Natural Language 
    24. 

  24. Processing (NLP), the study of computational systems to understand and/or
    25. 

  25. generate human language.
    26. 

  26. Approximately two thirds of the class will cover fundamental concepts and techniques in 
    27. 

  27. NLP, such as language models, statistical techniques for sequence tagging, parsing, 
    28. 

  28. information extraction, and information retrieval. The remaining one third of the class will introduce students to
    29. 

  29. some of the more recent development in NLP research, such as the use of constraint 
    30. 

  30. optimization techniques, and ideas for data acquisition without expert 
    31. 

  31. annotation. Throughout the class, students will be exposed to some of the 
    32. 

  32. recent research papers that connect the concepts learned from the textbook to 
    33. 

  33. exciting research questions that are practically motivated.
    34. 

  34. <br>
    35. 

  35. <b>Note:</b> The material covered in this class will not overlap with the companion class [CSE 507 Computational Linguistics] that 
    36. 

  36. will be offered in Spring 2011; this class concerns subjects that are more 
    37. 

  37. computationally-oriented, while CSE 507 will touch more on the linquistic 
    38. 

  38. theories and semantics.
    39. 

  39. <br><br>
    40. 

  40. <li><b>Textbook: </b>
    41. 

  41. Jurafsky and Martin, <a href="http://www.cs.colorado.edu/~martin/slp2.html"> SPEECH and LANGUAGE PROCESSING: An Introduction to 
    42. 

  42. Natural Language Processing, Computational Linguistics, and Speech Recognition
    43. 

  43. , Second Edition</a>, McGraw Hill, 2008. 
    44. 

  44. 

  45. <br><br>Note that some copies of the textbook should be available in the reserve 
    46. 

  46. shelf of the North Reading Room 
    47. 

  47. (NRR) at the library.
    48. 

  48. <br><br>
    49. 

  49. <li><b>Prerequisites: </b> 
    50. 

  50. Familiarity with either Artificial Intelligence or Machine 
    51. 

  51. Learning is strongly recommended, but not strictly necessary.
    52. 

  52. <br><br>
    53. 

  53. <li><b>Grading: </b>
    54. 

  54. Paper Presentation 10%,
    55. 

  55. Quiz (for paper presentations) 10%,
    56. 

  56. Homework 35%,
    57. 

  57. Final Project 35%,
    58. 

  58. Class Participation 10% 
    59. 

  59. <br><br>
    60. 

  60. <li> Late submission: Each student may adjust his/her homework deadline upto 7 days 
    61. 

  61. throughout the semester without a penalty. (not 7 days for each assignment, 
    62. 

  62. but 7 days cumulatively for the entire semester). After then, 10% of score will be 
    63. 

  63. subtracted each day. This policy is to encourage students to submit quality work, 
    64. 

  64. rather than poorly composed work in a hurry. For the purpose 
    65. 

  65. of counting late submission, factional values will be rounded up - for 
    66. 

  66. instance, late submission by 1 hour is counted as late by 1 day.
    67. 

  67. If there are situations where the application of this rule can be ambiguous, I have 
    68. 

  68. the right to apply the rule as I see appropriate. If you have a doubt, consult with me 
    69. 

  69. first before making your own assumption.
    70. 

  70. <br><br>
    71. 

  71. <li> Assignments are posted to <a href="https://blackboard.stonybrook.edu/bin/common/course.pl?course_id=_321486_1">
    72. 

  72. Blackboard </a> 
    73. 

  73. 

  74. </ul>
    75. 

  75. 

  76. 

  77. <h4><font color="black">Announcements:</font></h4>
    78. 

  78. <ol>
    79. 

  79. <li> First class will be on Wednesday Sep 1.
    80. 

  80. <li> This class is open to <i>both</i> Ph.D. and masters students. 
    81. 

  81. <li> The class location has moved to CS 2129. Due 
    82. 

  82. to the availability of the room, the Monday classes will begin at 11:40am and end 
    83. 

  83. at 12:40pm. The Wednesday classes are 11:10am - 12:40pm.
    84. 

  84. <li> <font color="black"> Homework-1 (paper reading assignment) will be due Sep 19th 
    85. 

  85. 6pm. (See <a href="https://blackboard.stonybrook.edu/bin/common/course.pl?course_id=_321486_1">
    86. 

  86. Blackboard </a> for details) </font> 
    87. 

  87. <li> <font color="black"> Homework-2 (paper reading assignment) will be due Sep 
    88. 

  88. 28th (TUE) 11:59pm. (See <a href="https://blackboard.stonybrook.edu/bin/common/course.pl?course_id=_321486_1">
    89. 

  89. Blackboard </a> for details) </font>
    90. 

  90. <li> <font color="black"> Homework-3 (project plan) will be due Oct 12th (TUE) 11:59pm. (See <a href="https://blackboard.stonybrook.edu/bin/common/course.pl?course_id=_321486_1">
    91. 

  91. Blackboard </a> for details) </font> 
    92. 

  92. <li> <font color="black"> Homework-4 (baseline implementation/data collection) will be due Oct 
    93. 

  93. 26th (TUE) 11:59pm. (See <a href="https://blackboard.stonybrook.edu/bin/common/course.pl?course_id=_321486_1">
    94. 

  94. Blackboard </a> for details) </font>
    95. 

  95. <li> <font color="black"> Notice that your late submission credit has been 
    96. 

  96. increased by 2 days!  </font>
    97. 

  97. <li> <font color="black"> Homework-5 submission (substantial implementation of your 
    98. 

  98. project and in-depth analysis and evaluation) will be due Nov 
    99. 

  99. 23th (TUE) 11:59pm. (See <a href="https://blackboard.stonybrook.edu/bin/common/course.pl?course_id=_321486_1">
    100. 

  100. Blackboard </a> for details) </font> 
    101. 

  101. <li> <b> <font color="red"> Homework-6 submission (Final Project Submission) will be due 
    102. 

  102. Dev 19th (SUN) 11:59pm. Submission guideline is similar to that of the previous 
    103. 

  103. submission. </font> </b>
    104. 

  104. 

  105. </ol>
    106. 

  106. 

  107. <h4>Syllabus: (<i><small>subject to change depending on the students' backgrounds and 
    108. 

  108. interests</i></small>)</h4>
    109. 

  109. <table style="text-align: left; width: 100%;" border="1" cellpadding="2" style="border-collapse: collapse"
    110. 

  110. bordercolor="#808080" 
    111. 

  111.  cellspacing="2">
    112. 

  112.   <tbody>
    113. 

  113.     <tr bgcolor="black"> 
    114. 

  114.       <td width="30"></td>
    115. 

  115.       <td width="80"><font size=4 color="white"><b>Date</b></font></td>
    116. 

  116.       <td><font size=4 color="white"><b>Topics</b></font></td>
    117. 

  117.       <td><font size=4 color="white"><b>References</b></font></td>
    118. 

  118.     </tr>
    119. 

  119.     
    120. 

  120.     <tr bgcolor="lightcyan"><td>01</td>    
    121. 

  121.       <td>Wed 09/01</td>
    122. 

  122.       <td>Introduction <a href="./lecture/01-intro.pdf">[slides]</a></td>
    123. 

  123.       <td><ul type="circle">
    124. 

  124.       <li>J&M Chapter 1	
    125. 

  125.       <li><a href="http://www.cs.cornell.edu/home/llee/papers/cstb.pdf">[pdf]</a>
    126. 

  126.       Lillian Lee, 2001. <i>I'm
    127. 

  127.       sorry Dave, I'm afraid I can't do that: Linguistics, Statistics,
    128. 

  128.       and Natural Language Processing circa 2001.</i>  The National
    129. 

  129.       Academies' study on the Fundamentals of Computer Science
    130. 

  130.       </ul></td>
    131. 

  131.     </tr>
    132. 

  132.     
    133. 

  133.     <tr bgcolor="lightcyan"><td>02</td>
    134. 

  134.       <td>Mon 09/06</td>
    135. 

  135.       <td>No Class (Labor Day)</td>
    136. 

  136.       <td></td>
    137. 

  137.     </tr>
    138. 

  138.     
    139. 

  139.     <tr bgcolor="lightcyan"><td>03</td>
    140. 

  140.       <td>Wed 09/08</td>
    141. 

  141.       <td>Language Models <a href="./lecture/02-ngram.pdf">[slides]</a></td>
    142. 

  142.       <td>
    143. 

  143.       <ul type="circle"><li>J&M Chapter 4</ul>
    144. 

  144.       </td>
    145. 

  145.     </tr>
    146. 

  146.     
    147. 

  147.     <tr bgcolor="lightcyan"><td>04</td>
    148. 

  148.       <td>Mon 09/13</td>
    149. 

  149.       <td>Language Models & Information Theory <a href="./lecture/03-ngram.pdf">[slides]</a></td>
    150. 

  150.       <td>
    151. 

  151.       <ul type="circle"><li>J&M Chapter 4      
    152. 

  152.       <li>
    153. 

  153.       <a href="http://www.aclweb.org/anthology/P/P05/P05-1065.pdf">[pdf]</a>
    154. 

  154.       Sarah E. Schwarm and Mari Ostendorf, 2005.
    155. 

  155.       <i>Reading level assessment using support vector machines and statistical 
    156. 

  156. language models.</i> ACL
    157. 

  157. 	  <li>
    158. 

  158. 	  <a href="http://research.microsoft.com/en-us/um/people/kevynct/pubs/hlt04_readability.
    159. 

  159. pdf">[pdf]</a>
    160. 

  160. 	  Kevyn Collins-Thompson and Jamie Callan, 2004. <i> A language modeling approach to predicting 
    161. 

  161. reading difficulty.</i> NAACL 
    162. 

  162.       <li>
    163. 

  163.       <a href="http://www.ldc.upenn.edu/acl/A/A00/A00-2032.pdf">[pdf]</a>
    164. 

  164.       Rie Kubota Ando and Lillian Lee, 2000.
    165. 

  165.       <i>Mostly-Unsupervised Statistical Segmentation of Japanese: Applications to 
    166. 

  166. Kanji.</i> NAACL
    167. 

  167.       </td>
    168. 

  168.     </tr>
    169. 

  169.     
    170. 

  170.     <tr bgcolor="lightcyan"><td>05</td>
    171. 

  171.       <td>Wed 09/15</td>
    172. 

  172.       <td>Machine Learning Basics <a href="./lecture/04h.pdf">[slides]</a></td>
    173. 

  173.       <td><ul type="circle">      
    174. 

  174.       </ul></td> 
    175. 

  175.     </tr>
    176. 

  176.     
    177. 

  177.     <tr bgcolor="lightcyan"><td>06</td>
    178. 

  178.       <td>Mon 09/20</td>
    179. 

  179.       <td>Part-of-Speech Tagging & Sequence Tagging <a href="./lecture/05h.pdf">[slides]</a></td>
    180. 

  180.       <td>
    181. 

  181.       <ul type="circle"><li>J&M Chapter 5</ul>
    182. 

  182.       </td>
    183. 

  183.     </tr>
    184. 

  184.     
    185. 

  185.     <tr bgcolor="lightcyan"><td>07</td>
    186. 

  186.       <td>Wed 09/22</td>
    187. 

  187.       <td>Part-of-Speech Tagging & Sequence Tagging <a href="./lecture/05h.pdf">[slides]</a></td>
    188. 

  188.       <td>
    189. 

  189.       <ul type="circle"><li>J&M Chapter 5</ul>
    190. 

  190.       </td>
    191. 

  191.     </tr>
    192. 

  192.     
    193. 

  193.     <tr bgcolor="lightcyan"><td>08</td>
    194. 

  194.       <td>Mon 09/27</td>
    195. 

  195.       <td>Hidden Markov Models <a href="./lecture/06h.pdf">[slides]</a></td>
    196. 

  196.       <td>
    197. 

  197.       <ul type="circle"><li>J&M Chapter 6</ul>
    198. 

  198.       </td>
    199. 

  199.     </tr>
    200. 

  200.     
    201. 

  201.     <tr bgcolor="lightcyan"><td>09</td>
    202. 

  202.       <td>Wed 09/29</td>
    203. 

  203.       <td>Hidden Markov Models <a href="./lecture/06h.pdf">[slides]</a></td>
    204. 

  204.       <td>
    205. 

  205.       <ul type="circle"><li>J&M Chapter 6</ul>
    206. 

  206.       </td>
    207. 

  207.     </tr>
    208. 

  208.     
    209. 

  209.     <tr bgcolor="lightcyan"><td>10</td>
    210. 

  210.       <td>Mon 10/04</td>
    211. 

  211.       <td>2nd Assignment & Project Discussion</td>
    212. 

  212.       <td>      
    213. 

  213.       <ul type="circle"><li>
    214. 

  214.       See blackboards for slides
    215. 

  215.       </ul>
    216. 

  216.       </td>
    217. 

  217.     </tr>
    218. 

  218.     
    219. 

  219.     <tr bgcolor="lightcyan"><td>11</td>
    220. 

  220.       <td>Wed 10/06</td>
    221. 

  221.       <td>Project Meeting</td>
    222. 

  222.       <td></td>
    223. 

  223.     </tr>
    224. 

  224.     
    225. 

  225.     <tr bgcolor="lightcyan"><td>12</td>
    226. 

  226.       <td>Mon 10/11</td>
    227. 

  227.       <td>Recruiting Event</td>
    228. 

  228.       <td>
    229. 

  229.       </td>
    230. 

  230.     </tr>
    231. 

  231.     
    232. 

  232.     <tr bgcolor="lightcyan"><td>13</td>
    233. 

  233.       <td>Wed 10/13</td>
    234. 

  234.       <td>Maximum Entropy Models & Conditional Random Fields <a href="./lecture/07h.pdf">[slides]</a></td>
    235. 

  235.       <td>
    236. 

  236.       <ul type="circle">
    237. 

  237.       <li>J&M Chapter 6
    238. 

  238.       </ul>
    239. 

  239.       </td>
    240. 

  240.     </tr>
    241. 

  241.     
    242. 

  242.     <tr bgcolor="lightcyan"><td>14</td>
    243. 

  243.       <td>Mon 10/18</td>
    244. 

  244.       <td>Information Extraction <a href="./lecture/08h.pdf">[slides]</a></td>
    245. 

  245.       <td><ul type="circle">
    246. 

  246.       <li>J&M Chapter 22
    247. 

  247.       </ul>      
    248. 

  248.       </td>
    249. 

  249.     </tr>
    250. 

  250.     
    251. 

  251.     <tr bgcolor="lightcyan"><td>15</td>
    252. 

  252.       <td>Wed 10/20</td>
    253. 

  253.       <td>Paper Presentations</td>
    254. 

  254.       <td>
    255. 

  255.       <ul type="circle">
    256. 

  256.       <li>Balanagireddy Mudiam to present [<i>Large-Scale Named Entity Disambiguation Based on 
    257. 

  257.       Wikipedia Data </i> by Silviu Cucerzan] 
    258. 

  258.       <a href="http://acl.ldc.upenn.edu/D/D07/D07-1074.pdf">[pdf]</a>
    259. 

  259.       <a href="./students/bala.pdf">[slides]</a>
    260. 

  260.       <li>Ruchita Sarawgi, Kailash GVS, Praveen V S to present 
    261. 

  261.       [<i>Automatically profiling the Author of an Anonymous 
    262. 

  262.       Text</i> by Shlomo Argamon, Moshe Koppel, James W. Pennebaker, and Jonathan Schler]
    263. 

  263.       <a href="http://www.cs.biu.ac.il/~koppel/papers/AuthorshipProfiling-cacm-final.pdf">[pdf]</a>
    264. 

  264.       <a href="./students/ruch.ppt">[slides]</a>
    265. 

  265.       </ul>
    266. 

  266.       </td>
    267. 

  267.     </tr>
    268. 

  268.     
    269. 

  269.     <tr bgcolor="lightcyan"><td>16</td>
    270. 

  270.       <td>Mon 10/25</td>
    271. 

  271.       <td>Context Free Grammars <a href="./lecture/09h.pdf">[slides]</a></td>
    272. 

  272.       <td>
    273. 

  273.       <ul type="circle"><li>J&M Chapter 12      
    274. 

  274.       </ul>
    275. 

  275.       </td>
    276. 

  276.     </tr>
    277. 

  277.     
    278. 

  278.     <tr bgcolor="lightcyan"><td>17</td>
    279. 

  279.       <td>Wed 10/27</td>
    280. 

  280.       <td>Paper Presentations</td>
    281. 

  281.       <td>
    282. 

  282.       <ul type="circle">     
    283. 

  283.       <li> Ritwik Banerjee to present [<i>A Non-negative Matrix Tri-factorization Approach to Sentiment Classification 
    284. 

  284. with Lexical Prior Knowledge</i> by Tao Li, Yi Zhang, and Vikas Sindhwani] 
    285. 

  285. <a href="http://www.aclweb.org/anthology/P/P09/P09-1028.pdf"> [pdf]</a>
    286. 

  286. <a href="./students/ritw.pdf">[slides]</a>
    287. 

  287.       <li>Thomas J Condus to present [<i>A Hierarchical Approach to Encoding Medical Concepts for Clinical 
    288. 

  288.       Notes</i> by Yitao Zhang] <a href="http://www.aclweb.org/anthology/P/P08/P08-3012.pdf">[pdf]</a>
    289. 

  289.       <a href="./students/thom.ppt">[slides]</a>
    290. 

  290.       </ul>
    291. 

  291.       </td>
    292. 

  292.     </tr>
    293. 

  293. 

  294.     <tr bgcolor="lightcyan"><td>18</td>
    295. 

  295.       <td>Mon 11/01</td>
    296. 

  296.       <td>Parsing <a href="./lecture/10h.pdf">[slides]</a></td>
    297. 

  297.       <td>  
    298. 

  298.       <ul type="circle"><li>J&M Chapter 13
    299. 

  299.       </ul>
    300. 

  300.       </td>
    301. 

  301.     </tr>
    302. 

  302.     
    303. 

  303.     <tr bgcolor="lightcyan"><td>19</td>
    304. 

  304.       <td>Wed 11/03</td>
    305. 

  305.       <td>Paper Presentations</td>
    306. 

  306.       <td>
    307. 

  307.       <ul type="circle">
    308. 

  308.       <li>
    309. 

  309.       Deepika Srinivasan, Annapurneshwari Kulkarni to present
    310. 

  310.       [<i>Annotating Named Entities in Twitter Data with Crowdsourcing</i> by   	
    311. 

  311. Tim Finin, Will Murnane, Anand Karandikar, Nicholas Keller, Justin Martineau, and Mark Dredze]
    312. 

  312.       <a href="http://www.cs.jhu.edu/~mdredze/publications/amt_ner.pdf">[pdf]</a>  
    313. 

  313.       <a href="./students/deep.ppt">[slides]</a>
    314. 

  314.       <li>Ishani Garg, Sumati Priya to present [<i>Robust Sentiment Detection on Twitter from Biased and Noisy 
    315. 

  315.       Data</i> by Luciano Barbosa, and Junlan Feng]
    316. 

  316.       <a 
    317. 

  317.       href="http://www2.research.att.com/~lbarbosa/publications/coling_2010.pdf">[pdf]</a>
    318. 

  318.       <a href="./students/isha.pdf">[slides]</a>
    319. 

  319.       <li>Mandeep Singh Grang, Sudheer Jetty to present 
    320. 

  320.       [<i>NLP (Natural Language Processing) for NLP (Natural Language 
    321. 

  321.       Programming)</i> by Rada Mihalcea, Hugo Liu, and Henry Lieberman] <a 
    322. 

  322.       href="http://www.cse.unt.edu/~rada/papers/mihalcea.cicling06a.pdf">[pdf]</a>          
    323. 

  323.       <a href="./students/mand.pdf">[slides]</a>
    324. 

  324.       </ul>      
    325. 

  325.       </td>      
    326. 

  326.     </tr>    
    327. 

  327.         
    328. 

  328.     <tr bgcolor="lightcyan"><td>20</td>
    329. 

  329.       <td>Mon 11/08</td>
    330. 

  330.       <td>Paper Presentations</td>
    331. 

  331.       <td>
    332. 

  332.       <ul type="circle">
    333. 

  333.       <li>Rohith Menon, Goutham Bhat and Shruthi D to present 
    334. 

  334.       [<i>Authorship Attribution Using Probabilistic Context-Free Grammars</i> by Sindhu Raghavan, Adriana Kovashka, and Raymond Mooney]
    335. 

  335.       <a href="http://www.aclweb.org/anthology/P/P10/P10-2008.pdf">[pdf]</a>
    336. 

  336.       </ul>
    337. 

  337.       </td>   
    338. 

  338.     </tr>
    339. 

  339.     
    340. 

  340.     <tr bgcolor="lightcyan"><td>21</td>
    341. 

  341.       <td>Wed 11/10</td>
    342. 

  342.       <td>Paper Presentations</td>
    343. 

  343.       <td>
    344. 

  344.       <ul type="circle">
    345. 

  345.       <li>
    346. 

  346.       Manoj Harpalani, Sandesh Singh to present
    347. 

  347.       [<i>Learning within sentence semantic coherence</i> by Elena Eneva, Rose 
    348. 

  348.       Hoberman, and Lucian Lita]
    349. 

  349.       <a href="http://www.aclweb.org/anthology/W/W01/W01-0503.pdf">[pdf]</a>
    350. 

  350.       <li>Chandrakanth Reddy B, Anand sagar Kothapalli to present 
    351. 

  351.       [<i>An Approach for Combining Content-based and Collaborative Filters</i> by   	
    352. 

  352. Qing Li, and Byeong Man Kim]
    353. 

  353.       <li>Harit Himanshu to present [<i>Thumbs up? Sentiment Classification using Machine Learning 
    354. 

  354.       Techniques</i> by Bo Pang, and Lillian Lee]
    355. 

  355.       <a href="http://www.cs.cornell.edu/home/llee/papers/sentiment.pdf">[pdf]</a>
    356. 

  356.       </ul>
    357. 

  357.       </td>   
    358. 

  358.     </tr>
    359. 

  359.     
    360. 

  360.     <tr bgcolor="lightcyan"><td>22</td>
    361. 

  361.       <td>Mon 11/15</td>
    362. 

  362.       <td>Paper Presentations <br> & <br> Statistical Parsing <a href="./lecture/11h.pdf">[slides]</a></td>
    363. 

  363.       <td>      
    364. 

  364.       <ul type="circle">      
    365. 

  365.       <li>Parag Kadu & Aneesh Ali to present [<i>Sentence Boundary Detection and the Problem with the 
    366. 

  366.       U.S.</i> by Dan Gillick] <a 
    367. 

  367.       href="http://www.aclweb.org/anthology/N/N09/N09-2061.pdf">[pdf]</a>      
    368. 

  368.       <li>J&M Chapter 14
    369. 

  369.       </ul>
    370. 

  370.       </td>   
    371. 

  371.     </tr>
    372. 

  372.     
    373. 

  373.     <tr bgcolor="lightcyan"><td>23</td>
    374. 

  374.       <td>Wed 11/17</td>
    375. 

  375.       <td>Paper Presentations</td>
    376. 

  376.       <td>
    377. 

  377.       <ul type="circle">
    378. 

  378.       <li>Vaibhav Shrivastava & Girish SK to present 
    379. 

  379.       [<i>Hierarchical Document Categorization with Support Vector 
    380. 

  380.       Machines</i> by Lijuan Cai and Thomas Hofmann.]
    381. 

  381.       <a href="http://sca2002.cs.brown.edu/people/th/papers/CaiHof-CIKM2004.pdf">[pdf]</a>
    382. 

  382. 	  <li>Amitha Cheluvagopal & Sharath Ravindran & Avinash Gupta Konda to 
    383. 

  383. 	  present [<i>An Effective Two-Stage Model for Exploiting Non-Local Dependencies in Named 
    384. 

  384. Entity Recognition</i> by Vijay Krishnan and Christopher Manning]
    385. 

  385. <a href="http://www.aclweb.org/anthology/P/P06/P06-1141.pdf">[pdf]</a>	
    386. 

  386.       </ul>
    387. 

  387.       </td>   
    388. 

  388.     </tr>
    389. 

  389.     
    390. 

  390.     <tr bgcolor="lightcyan"><td>24</td>
    391. 

  391.       <td>Mon 11/22</td>
    392. 

  392.       <td>Paper Presentations</td>
    393. 

  393.       <td>
    394. 

  394.       <ul type="circle"><li>Siming Li & Girish Kulkarni to present [<i>A Linear Programming Formulation for Global Inference
    395. 

  395. in Natural Language Tasks</i> by Dan Roth, and Wen-tau Yih]
    396. 

  396.       <a href="http://l2r.cs.uiuc.edu/~danr/Papers/RothYi04a.pdf">[pdf]</a>
    397. 

  397.       <li>Longfei Xing & Supriya Vasudevan to present
    398. 

  398.       [<i>Graph-based Ranking Algorithms for Sentence Extraction,
    399. 

  399. Applied to Text Summarization</i> by Rada Mihalcea]
    400. 

  400. <a href="http://acl.ldc.upenn.edu/P/P04/P04-3020.pdf">[pdf]</a>
    401. 

  401. 	  </ul>
    402. 

  402.       </td>   
    403. 

  403.     </tr>
    404. 

  404.     
    405. 

  405.     <tr bgcolor="lightcyan"><td>25</td>
    406. 

  406.       <td>Wed 11/24</td>
    407. 

  407.       <td>Correction Day - Follows a FRIDAY schedule </td>
    408. 

  408.       <td></td>
    409. 

  409.     </tr>
    410. 

  410.     
    411. 

  411.     <tr bgcolor="lightcyan"><td>26</td>
    412. 

  412.       <td>Mon 11/29</td>
    413. 

  413.       <td>Statistical Parsing <a href="./lecture/11h.pdf">[slides]</a></td>
    414. 

  414.       <td><ul type="circle">      
    415. 

  415.       <li>J&M Chapter 14
    416. 

  416.       </ul>      
    417. 

  417.       </td>
    418. 

  418.     </tr>
    419. 

  419.     
    420. 

  420.     <tr bgcolor="lightcyan"><td>27</td>
    421. 

  421.       <td>Wed 12/01</td>
    422. 

  422.       <td>Paper Presentations <br> & <br> Machine Translation <a 
    423. 

  423.       href="./lecture/12h.pdf">[slides]</a></td>
    424. 

  424.       <td><ul type="circle">
    425. 

  425.       <li>Khusboo Agarwal & Piyush Kumat to present 
    426. 

  426.       [<i>NaLIX: an Interactive Natural Language Interface for Querying XML</i> by 
    427. 

  427.       Yunyao Li, Huahai Yang, and H. V. Jagadish]
    428. 

  428.       <a href="http://www-personal.umich.edu/~yunyaol/publication/130NaLIX.pdf">[pdf]</a>
    429. 

  429.       <li>J&M Chapter 25</ul>      
    430. 

  430.       </td>
    431. 

  431.     </tr>
    432. 

  432.     
    433. 

  433.     <tr bgcolor="lightcyan"><td>28</td>
    434. 

  434.       <td>Mon 12/06</td>
    435. 

  435.       <td>Machine Translation <a href="./lecture/12h.pdf">[slides]</a></td>
    436. 

  436.       <td><ul type="circle">
    437. 

  437.       <li>J&M Chapter 25</ul>      
    438. 

  438.       </td>
    439. 

  439.     </tr>
    440. 

  440.     
    441. 

  441.     <tr bgcolor="lightcyan"><td>29</td>
    442. 

  442.       <td>Wed 12/08</td>
    443. 

  443.       <td>Expectation Maximization <br> & <br> How to be successful in your 
    444. 

  444.       future career</td>
    445. 

  445.       <td></td>
    446. 

  446.     </tr>
    447. 

  447.    
    448. 

  448.   </tbody>
    449. 

  449. </table>
    450. 

  450. <br>
    451. 

  451. <br>
    452. 

  452. 

  453. <br>
    454. 

  454. <br>
    455. 

  455. <br>
    456. 

  456. </body>
    457. 

  457. </html>
    458. 

  458.