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Short text authorship attribution via sequence kernels, Markov chains and author unmasking: An investigation
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In: Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing ; http://acl.ldc.upenn.edu/W/W06/#W06-1600 (2015)
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Toward Determining the Comprehensibility of Machine Translations
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In: DTIC (2012)
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| 4 |
Novel Topic Impact on Authorship Attribution
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In: DTIC (2009)
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Syntactic Simplification for Improving Content Selection in Multi-Document Summarization
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In: DTIC (2004)
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Abstract:
In this paper, we explore the use of automatic syntactic simplification for improving content selection in multi-document summarization. In particular, we show how simplifying parentheticals by removing relative clauses and appositives results in improved sentence clustering, by forcing clustering based on central rather than background information. We argue that the inclusion of parenthetical information in a summary is a reference-generation task rather than a content-selection one, and implement a baseline reference rewriting module. We perform our evaluations on the test sets from the 2003 and 2004 Document Understanding Conference and report that simplifying parentheticals results in significant cant improvement on the automated evaluation metric Rouge. Syntactic simplification is an NLP task, the goal of which is to rewrite sentences to reduce their grammatical complexity while preserving their meaning and information content. Text simplification is a useful task for varied reasons. Chandrasekar et al. (1996) viewed text simplification as a preprocessing tool to improve the performance of their parser. The PSET project (Carroll et al., 1999), on the other hand, focused its research on simplifying newspaper text for aphasics, who have trouble with long sentences and complicated grammatical constructs. We have previously (Siddharthan, 2002; Siddharthan, 2003) developed a shallow and robust syntactic simplification system for news reports, that simplifies relative clauses, apposition and conjunction. In this paper, we explore the use of syntactic simplification in multi-document summarization.
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Keyword:
*LINGUISTICS; *NATURAL LANGUAGE; *SYNTAX; AUTOMATIC; BASE LINES; CLUSTERING; GRAMMARS; Linguistics; PARSERS; PREPROCESSING; SELECTION; SIMPLIFICATION; TEST SETS; TOOLS; WORDS(LANGUAGE)
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URL: http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA457833
http://www.dtic.mil/docs/citations/ADA457833
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| 6 |
Cross-Document Coreference on a Large Scale Corpus
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In: DTIC (2004)
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A Similarity-Based Approach and Evaluation Methodology for Reduction of Drug Name Confusion
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In: DTIC (2003)
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| 8 |
The Bible, Truth, and Multilingual OCR Evaluation
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In: DTIC (1998)
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| 9 |
Experiments in Spoken Document Retrieval at CMU
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In: DTIC (1997)
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| 10 |
Efficient Algorithms for Speech Recognition.
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In: DTIC AND NTIS (1996)
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| 11 |
Overview of Results of the MUC-6 Evaluation
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In: DTIC (1995)
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| 12 |
Phonological Parsing for Bi-directional Letter-to-Sound/Sound-to-Letter Generation
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In: DTIC (1994)
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| 13 |
Signal Processing for Robust Speech Recognition
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In: DTIC (1994)
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| 14 |
Adaptive Natural Language Processing
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In: DTIC AND NTIS (1991)
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| 15 |
Global Optimization of Digital Circuits.
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In: DTIC AND NTIS (1991)
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| 16 |
Integrating Syntax, Semantics,and Discourse DARPA (Defense Advanced Research Projects Agency) Natural Language Understanding Program
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In: DTIC AND NTIS (1989)
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| 17 |
Integration of Speech and Natural Language
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In: DTIC AND NTIS (1989)
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PROGRAMMING LANGUAGE FOR AUTOMATIC CHECKOUT EQUIPMENT. VOLUME II. ADAPTED PLACE FOR THE BENDIX AN/GJQ-9.
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In: DTIC AND NTIS (1963)
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