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Relevance Feedback based on Constrained Clustering: FDU at TREC 09
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In: DTIC (2009)
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| 2 |
A Journey in Entity Related Retrieval for TREC 2009
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In: DTIC (2009)
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| 3 |
Lucene for n-grams using the ClueWeb Collection
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In: DTIC (2009)
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| 4 |
BIT at TREC 2009 Faceted Blog Distillation Task
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In: DTIC (2009)
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| 5 |
IRRA at TREC 2009: Index Term Weighting based on Divergence From Independence Model
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In: DTIC (2009)
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| 6 |
POSTECH at TREC 2009 Blog Track: Top Stories Identification
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In: DTIC (2009)
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| 7 |
PRIS at 2009 Relevance Feedback track: Experiments in Language Model for Relevance Feedback
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In: DTIC (2009)
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| 8 |
Experiments on Related Entity Finding Track at TREC 2009
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In: DTIC (2009)
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| 9 |
Facet Classification of Blogs: Know-Center at the TREC 2009 Blog Distillation Task
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In: DTIC (2009)
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| 10 |
Comparing Evaluation Metrics for Sentence Boundary Detection
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In: DTIC (2007)
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| 12 |
Measuring Translation Quality by Testing English Speakers with a New Defense Language Proficiency Test for Arabic
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In: DTIC (2005)
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| 13 |
Measuring Human Readability of Machine Generated Text: Three Case Studies in Speech Recognition and Machine Translation
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In: DTIC (2005)
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| 14 |
Uses of the Diagnostic Rhyme Test (English Version) for Predicting the Effects of Communicators' Linguistic Backgrounds on Voice Communications in English: An Exploratory Study
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In: DTIC (2000)
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| 15 |
The Bible, Truth, and Multilingual OCR Evaluation
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In: DTIC (1998)
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Abstract:
Multilingual OCR has emerged as an important information technology, thanks to the increasing need for cross-language information access. While many research groups and companies have developed OCR algorithms for various languages, it is difficult to compare the performance of these OCR algorithms across languages. This difficulty arises because most evaluation methodologies rely on the use of a document image dataset in each of the languages and it is difficult to find document datasets in different languages that are similar in content and layout. In this paper we propose to use the Bible as a dataset for comparing OCR accuracy across languages. Besides being available in a wide range of languages, Bible translation are closely parallel in content, carefully translated, surprisingly relevant with respect to modern-day language, and quite inexpensive. A project at the University of Maryland is currently implementing this idea. We have created a scanned image dataset with groundtruth from an Arabic Bible. We have also used image degradation models to create synthetically degraded images of a French Bible. We hope to generate similar Bible datasets for other languages, and we are exploring alternative corpora such as the Koran and the Bhagavad Gita that have similar properties. Quantitative OCR evaluation based on the Arabic Bible dataset is currently in progress. ; Sponsored in part by DARPA and Army Research Lab. Report no. CS-TR-3967. Presented at the SPIE Conference on Document Recognition and Retrieval VI held in San Jose, CA on 27-28 Jan 1999. Published in the Proceedings of the SPIE Conference on Document Recognition and Retrieval VI, Proceedings of SPIE, v3651, 1999.
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Keyword:
*BIBLE; *CORPUS; *DATASETS; *GROUNDTRUTH; *OPTICAL CHARACTER RECOGNITION; *TEST SETS; *TRANSLATIONS; ACCURACY; ALGORITHMS; Cybernetics; DOCUMENT IMAGES; DOCUMENTS; IMAGES; Information Science; LANGUAGE; Linguistics; MULTILINGUAL OCR(OPTICAL CHARACTER RECOGNITION); SYMPOSIA; TEST AND EVALUATION
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URL: http://www.dtic.mil/docs/citations/ADA458666
http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA458666
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| 17 |
Tipster Shogun System (Joint GE-CMU): MUC-4 Test Results and Analysis
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In: DTIC (1992)
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| 18 |
GE-CMU: Description of the Tipster/Shogun System as Used for MUC-4
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In: DTIC (1992)
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| 20 |
Overview of the Fourth Message Understanding Evaluation and Conference
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In: DTIC AND NTIS (1992)
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