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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 Page: 1 2 3 Hits 1 – 20 of 59 1 Detecting Asks in SE attacks: Impact of Linguistic and Structural Knowledge ... Dorr, Bonnie J.; Bhatia, Archna; Dalton, Adam. - : arXiv, 2020 BASE Show details 2 Adaptation of a Lexical Organization for Social Engineering Detection and Response Generation ... Bhatia, Archna; Dalton, Adam; Mather, Brodie. - : arXiv, 2020 BASE Show details 3 Use of Modality and Negation in Semantically-Informed Syntactic MT ... Baker, Kathryn; Bloodgood, Michael; Dorr, Bonnie J.. - : arXiv, 2015 BASE Show details 4 A Modality Lexicon and its use in Automatic Tagging ... Baker, Kathryn; Bloodgood, Michael; Dorr, Bonnie J.. - : arXiv, 2014 BASE Show details 5 Semantically-Informed Syntactic Machine Translation: A Tree-Grafting Approach ... Baker, Kathryn; Bloodgood, Michael; Callison-Burch, Chris. - : arXiv, 2014 BASE Show details 6 Computing Lexical Contrast ... Mohammad, Saif M.; Dorr, Bonnie J.; Hirst, Graeme. - : arXiv, 2013 BASE Show details 7 Measuring Degrees of Semantic Opposition ... Mohammad, Saif M.; Dorr, Bonnie J.; Hirst, Graeme. - : National Research Council Canada, 2011 BASE Show details 8 Measuring Variability in Sentence Ordering for News Summarization Klavans, Judith L.; Madnani, Nitin; Passonneau, Rebecca. - : Proceeding ENLG '07 Proceedings of the Eleventh European Workshop on Natural Language Generation, 2007 BASE Show details 9 Multiple Alternative Sentene Compressions as a Tool for Automatic Summarization Tasks Zajic, David Michael. - 2007 Abstract: Automatic summarization is the distillation of important information from a source into an abridged form for a particular user or task. Many current systems summarize texts by selecting sentences with important content. The limitation of extraction at the sentence level is that highly relevant sentences may also contain non-relevant and redundant content. This thesis presents a novel framework for text summarization that addresses the limitations of sentence-level extraction. Under this framework text summarization is performed by generating Multiple Alternative Sentence Compressions (MASC) as candidate summary components and using weighted features of the candidates to construct summaries from them. Sentence compression is the rewriting of a sentence in a shorter form. This framework provides an environment in which hypotheses about summarization techniques can be tested. Three approaches to sentence compression were developed under this framework. The first approach, HMM Hedge, uses the Noisy Channel Model to calculate the most likely compressions of a sentence. The second approach, Trimmer, uses syntactic trimming rules that are linguistically motivated by Headlinese, a form of compressed English associated with newspaper headlines. The third approach, Topiary, is a combination of fluent text with topic terms. The MASC framework for automatic text summarization has been applied to the tasks of headline generation and multi-document summarization, and has been used for initial work in summarization of novel genres and applications, including broadcast news, email threads, cross-language, and structured queries. The framework supports combinations of component techniques, fostering collaboration between development teams. Three results will be demonstrated under the MASC framework. The first is that an extractive summarization system can produce better summaries by automatically selecting from a pool of compressed sentence candidates than by automatically selecting from unaltered source sentences. The second result is that sentence selectors can construct better summaries from pools of compressed candidates when they make use of larger candidate feature sets. The third result is that for the task of Headline Generation, a combination of topic terms and compressed sentences performs better then either approach alone. Experimental evidence supports all three results. Keyword: Automatic Summarization; Computer Science; Human Language Technology; Natural Language Processing; Sentence Compression URL: http://hdl.handle.net/1903/6729 BASE Hide details 10 Text Summarization Evaluation: Correlating Human Performance on an Extrinsic Task with Automatic Intrinsic Metrics President, Stacy F.; Dorr, Bonnie J. In: DTIC (2006) BASE Show details 11 Deriving verbal and compositional lexical aspect for NLP applications Dorr, Bonnie J.; Olsen, Mari B. In: The language of time (Oxford, 2005), p. 115-128 MPI für Psycholinguistik Show details 12 Use of Minimal Lexical Conceptual Structures for Single-Document Summarization Dorr, Bonnie J.; Habash, Nizar Y.; Monz, Christof... In: DTIC (2004) BASE Show details 13 Symbolic MT With Statistical NLP Components Dorr, Bonnie J.; Habash, Nizar Y.; Monz, Christof In: DTIC (2004) BASE Show details 14 Use of OCR for Rapid Construction of Bilingual Lexicons Karagol-Ayan, Burcu; Doermann, David; Dorr, Bonnie J. In: DTIC (2003) BASE Show details 15 A Similarity-Based Approach and Evaluation Methodology for Reduction of Drug Name Confusion Dorr, Bonnie J.; Kondrak, Grzegorz In: DTIC (2003) BASE Show details 16 Construction of a Chinese-English Verb Lexicon for Embedded Machine Translation in Cross-Language Information Retrieval Dorr, Bonnie J.; Lin, Dekang; Levow, Gina-Anne In: DTIC (2002) BASE Show details 17 Generating a Parsing Lexicon From Lexical-Conceptual Structure Ayan, Necip F.; Dorr, Bonnie J. In: DTIC (2002) BASE Show details 18 Improved Word-Level Alignment: Injecting Knowledge about MT Divergences Dorr, Bonnie J.; Pearl, Lisa; Hwa, Rebecca... In: DTIC (2002) BASE Show details 19 Constraints on the Generation of Tense, Aspect, and Connecting Words from Temporal Expressions Dorr, Bonnie J.; Gaasterland, Terry. - 2002 BASE Show details 20 Building a Chinese-English Mapping Between Verb Concepts for Multilingual Applications Dorr, Bonnie J.; Levow, Gina-Anne; Lin, Dekang In: DTIC (2001) BASE Show details Page: 1 2 3

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