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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 19 of 19 1 An Information-extraction system for Urdu—a resource-poor language Smruthi Mukund; Rohini Srihari; Erik Peterson In: http://www.cedar.buffalo.edu/~rohini/Papers/ACM-TALIP.pdf (2010) BASE Show details 2 Automatic Scoring of Short Handwritten Essays in Reading Comprehension Tests Sargur Srihari; Jim Collins; Rohini Srihari... In: http://www.cedar.buffalo.edu/~srihari/papers/TR-01-07.pdf (2007) BASE Show details 3 Information extraction for multi-participant, task-oriented, synchronous, computer-mediated communication: A corpus study of chat data Cassandre Creswell; Nicholas Schwartzmyer; Rohini Srihari In: http://research.ihost.com/and2007/cd/Proceedings_files/p131.pdf (2007) BASE Show details 4 datasets for Using Verbs and Adjectives to Automatically Classify Blog Sentiment Chesley, Paula; Xu, Li; Rohini, Srihari. - : dataset self-published online, 2006 BASE Show details 5 An Expert Lexicon Approach to Identifying English Phrasal Verbs Wei Li; Wei Li Xiuhong; Cheng Niu... In: http://acl.ldc.upenn.edu/acl2003/main/pdfs/Li.pdf (2003) BASE Show details 6 An Expert Lexicon Approach to Identifying English Phrasal Verbs Wei Li; Wei Li Xiuhong; Cheng Niu... In: http://acl.ldc.upenn.edu/P/P03/P03-1065.pdf (2003) BASE Show details 7 Use of Multimedia Input in Automated Image Annotation and Content-Based Retrieval Rohini Srihari In: http://www.cedar.buffalo.edu/Staff/Rohini/Postscript/spie95.ps.Z (1995) BASE Show details 8 An On-Line Cursive Word Recognition System Giovanni Seni; Nasser Nasrabadi; Rohini Srihari In: http://www.cedar.buffalo.edu/Linguistics/papers/ieee.ps (1994) BASE Show details 9 Visual Semantics: Extracting Visual Information from Text Accompanying Pictures Rohini Srihari; Debra T. Burhans In: http://www.cedar.buffalo.edu/Piction/papers/vis_sem.ps (1994) BASE Show details 10 Document Understanding: Research Directions Sargur Srihari; Stephen Lam; Venu Govindaraju... In: http://www.cedar.buffalo.edu/Publications/Postscript/Survey.ps (1992) BASE Show details 11 TREC 2008 at the University at Buffalo: Legal and Blog Track Jianqiang Wang; Ying Sun; Omar Mukhtar... In: http://trec.nist.gov/pubs/trec17/papers/suny-buffalo.legal.blog.rev.pdf BASE Show details 12 An On-Line Cursive Word Recognition System Giovanni Seni Y; Nasser Nasrabadi Z; Rohini Srihari Y In: http://www.cedar.buffalo.edu/handwriting/papers/ieee.pdf BASE Show details 13 Automated Scoring of Handwritten Essays based on Latent Semantic Analysis Sargur Srihari; Jim Collins; Rohini Srihari... In: http://www.cedar.buffalo.edu/~srihari/papers/DAS-2006.pdf BASE Show details 14 Proceedings of the ACL 2003 Workshop on Multilingual Summarization and Question Answering, pp. 84-93. Question Answering on a Case Insensitive Corpus Wei Li; Rohini Srihari; Cheng Niu... In: http://acl.ldc.upenn.edu/acl2003/mlsum/pdfs/Li.pdf BASE Show details 15 Learning to Summarize using Coherence Pradipto Das; Rohini Srihari In: http://www.cedar.buffalo.edu/%7Erohini/Papers/pdasNIPS09Wkshp.pdf BASE Show details 16 Utterance Topic Model for Generating Coherent Summaries Pradipto Das; Rohini Srihari In: http://www.cedar.buffalo.edu/%7Erohini/Papers/UBSummarizer-TAC2009.pdf BASE Show details 17 Utterance Topic Model for Generating Coherent Summaries Pradipto Das; Rohini Srihari In: http://www.nist.gov/tac/publications/2009/participant.papers/UBSummarizer.proceedings.pdf Abstract: Generating short multi-document summaries has received a lot of focus recently and is useful in many respects including summarizing answers to a question in an online scenario like Yahoo! Answers. The focus of this paper is to attempt to define a new probabilistic topic model that includes the semantic roles of the words in the document generation process. Words always carry syntactic and semantic information and often such information, for e.g., the grammatical and semantic role (henceforth GSR) of a word like Subject, Verb, Object, Adjective qualifiers, WordNet and VerbNet role assignments etc. is carried across adjacent sentences to enhance local coherence in different parts of a document. A statistical topic model like LDA[5] usually models topics as distributions over the word count vocabulary only. We posit that a document could first be topic modeled over a vocabulary of GSR transitions and then corresponding to each transition, words and and hence sentences can be sampled to best describe the transition. Thus the topics in the proposed model also lend themselves to be distributions over the GSR transitions implicitly. We also later show how this basic model can be extended to a model for query focused summarization where for a particular query, sentences can be ranked by a product of thematical salience and coherence through GSR transitions. We empirically show that the new topic model had lower test set perplexity than LDA and we also analyze the performance of our summarization model using the ROUGE[13] on DUC2005 dataset 1 and PYRA-MID[17] on the TAC2008 2 and TAC2009 3 datasets. Keyword: Centering theory; Coherence; Multi-document summarization; Topic Models URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.232.4803 http://www.nist.gov/tac/publications/2009/participant.papers/UBSummarizer.proceedings.pdf BASE Hide details 18 A Question Answering System Supported by Information Extraction Rohini Srihari; Wel Li BASE Show details 19 A Hybrid Approach for Named Entity and Sub-Type Tagging Rohini Srihari BASE Show details

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