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The Pennsylvania State University CiteSeerX Archives (40)
Judith L. Klavans (39)
Eleazar Eskin (9)
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Kathleen R. Mckeown (6)
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1
08-0117-08 is gratefully acknowledged. Taming Social Tags: Computational Linguistic Analysis of Tags for Images in Museums
Judith L. Klavans
;
Raul Guerra
;
Rebecca Laplante
...
In: http://lampsrv02.umiacs.umd.edu/pubs/TechReports/LAMP_155/LAMP_155.pdf (2011)
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2
Similarity-based Multilingual Multi-Document Summarization
David Kirk Evans
;
Kathleen Mckeown
;
Judith L. Klavans
In: http://www.cs.columbia.edu/nlp/papers/2005/evans_al_05.pdf (2005)
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3
Inducing constraint-based grammars from a small semantic treebank
Smaranda Muresan
;
Tudor Muresan
;
Judith L. Klavans
In: http://www.aaai.org/Papers/Symposia/Spring/2004/SS-04-05/SS04-05-009.pdf (2004)
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4
Inducing constraint-based grammars from a small semantic treebank
Smaranda Muresan
;
Tudor Muresan
;
Judith L. Klavans
In: http://www.cs.columbia.edu/nlp/papers/2004/muresan_al_04.pdf (2004)
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5
Columbia newsblaster: multilingual news summarization on the web
David Kirk Evans
;
Judith L. Klavans
In: http://www.cs.columbia.edu/%7Edevans/papers/mlNewsblaster.pdf (2004)
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6
A Platform for Multilingual News Summarization Paper ID: Multilingual-Summarization-CU
David Kirk Evans
;
Judith L. Klavans
In: http://www.cs.columbia.edu/techreports/cucs-014-03.pdf (2003)
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7
A Platform for Multilingual . . .
David Kirk Evans
;
Judith L. Klavans
In: http://www.cs.columbia.edu/~library/TR-repository/reports/reports-2003/cucs-014-03.ps.gz (2003)
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8
Methods for precise named entity matching in digital collections
Peter T. Davis
;
David K. Elson
;
Judith L. Klavans
In: http://www.cs.columbia.edu/nlp/papers/2003/davis_al_03.pdf (2003)
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9
Methods for precise named entity matching in digital collections
Peter T. Davis
;
David K. Elson
;
Judith L. Klavans
In: http://www.cs.columbia.edu/~delson/pubs/jcdl03.pdf (2003)
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10
B.: Tackling the internet glossary glut: Automatic extraction and evaluation of genus phrases
Judith L. Klavans
In: http://www.cs.columbia.edu/nlp/papers/2003/klavans_al_03.pdf (2003)
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11
Combining Linguistic and Machine Learning Techniques for Email
Smaranda Muresan
;
Evelyne Tzoukermann
;
Judith L. Klavans
In: http://cnts.uia.ac.be/conll2001/ps/15259mur.ps (2001)
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12
Document Processing with LinkIT
David K. Evans
;
Judith L. Klavans
;
Nina Wacholder
In: http://133.23.229.11/~ysuzuki/Proceedingsall/RIAO2000/Friday/110DP1.pdf (2000)
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13
Document Processing with LinkIT
David Evans Judith
;
David K. Evans
;
Judith L. Klavans
...
In: http://www.columbia.edu/cu/cria/Publications/riao2000.ps (2000)
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14
Evaluation of computational linguistic techniques for identifying significant topics for browsing applications
Judith L. Klavans
;
Nina Wacholder
;
David K. Evans
In: http://www.lrec-conf.org/proceedings/lrec2000/pdf/355.pdf (2000)
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15
The Eurospider Retrieval System and the TREC-8 Cross-Language Track
Martin Braschler
;
Min-yen Kan
;
Peter Schäuble
...
In: http://www.cs.columbia.edu/~min/papers/eit_t8f.pdf (1999)
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16
The Eurospider Retrieval System and the TREC-8 Cross-Language Track
Martin Braschler
;
Min-yen Kan
;
Peter Schäuble
...
In: http://trec.nist.gov/pubs/trec8/papers/eit_t8f.pdf (1999)
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17
Towards Multidocument Summarization by Reformulation: Progress and Prospects
Kathleen R. McKeown
;
Judith L. Klavans
;
Vasileios Hatzivassiloglou
...
In: http://www.cs.columbia.edu/nlp/newsblaster/papers/stim2.pdf (1999)
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18
Towards multidocument summarization by reformulation: Progress and prospects
Kathleen R. Mckeown
;
Judith L. Klavans
;
Vasileios Hatzivassiloglou
...
In: http://www.cs.columbia.edu/~vh/Papers/1999/Summarization-AAAI.pdf (1999)
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19
Detecting text similarity over short passages: exploring linguistic feature combinations via machine learning
Vasileios Hatzivassiloglou
;
Judith L. Klavans
;
Eleazar Eskin
In: http://www.cs.columbia.edu/~vh/Papers/1999/SimFinder-EMNLP.pdf (1999)
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20
Toward Multi-document summarization by Reformulation: progress
Kathleen R. Mckeown
;
Judith L. Klavans
;
Vasileios Hatzivassiloglou
;
Regina Barzilay
;
Eleazar Eskin
In: https://www.aaai.org/Papers/AAAI/1999/AAAI99-065.pdf (1999)
Abstract:
By synthesizing information common to retrieved docu-ments, multi-document summarization can help users of in-formation retrieval systems to find relevant documents with a minimal amount of reading. We are developing a multi-document summarization system to automatically generate a concise summary by identifying and synthesizing similarities across a set of related documents. Our approach is unique in its integration of machine learning and statistical techniques to identify similar paragraphs, intersection of similar phrases within paragraphs, and language generation to reformulate the wording of the summary. Our evaluation of system com-ponents shows that learning over multiple extracted linguis-tic features is more effective than information retrieval ap-proaches at identifying similar text units for summarization and that it is possible to generate a fluent summary that con-veys similarities among documents even when full semantic interpretations of the input text are not available.
URL:
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.570.1068
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