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1
Domain-specific coreference resolution with lexicalized features
Gilbert, Nathan; Riloff, Ellen M.. - : Association for Computational Linguistics, 2014
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2
Conundrums in noun phrase coreference resolution: making sense of the state-of-the-art
Riloff, Ellen M.; Stoyanov, Veselin; Gilbert, Nathan; Cardie, Claire. - : Association for Computational Linguistics, 2009
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3
Toward completeness in concept extraction and classification
Riloff, Ellen M.; Hovy, Eduard; Kozareva, Zornitsa. - : Association for Computational Linguistics, 2009
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4
Corpus-based semantic lexicon induction with web-based corroboration
Igo, Sean P.; Riloff, Ellen M.. - : Association for Computational Linguistics, 2009
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5
Unified model of phrasal and sentential evidence for information extraction
Riloff, Ellen M.; Patwardhan, Siddharth. - : Association for Computational Linguistics, 2009
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6
Semantic class learning from the web with hyponym pattern linkage graphs
Riloff, Ellen M.; Kozareva, Zornitsa; Hovy, Eduard. - : Association for Computational Linguistics, 2008
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7
Effective information extraction with semantic affinity patterns and relevant regions
Riloff, Ellen M.; Patwardhan, Siddharth. - : Association for Computational Linguistics, 2007
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8
Exploiting role-identifying nouns and expressions for information extraction
Riloff, Ellen M.; Phillips, William. - : Recent Advances in Natural Language Processing, 2007
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9
Feature subsumption for opinion analysis
Riloff, Ellen M.; Patwardhan, Siddharth; Wiebe, Janyce. - : Association for Computational Linguistics, 2006
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10
Learning domain-specific information extraction patterns from the web
Riloff, Ellen M.; Patwardhan, Siddharth. - : Association for Computational Linguistics, 2006
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11
OpinionFinder: a system for subjectivity analysis
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12
Identifying sources of opinions with conditional random fields and extraction patterns
Riloff, Ellen M.; Choi, Yejin; Cardie, Claire; Patwardhan, Siddharth. - : Association for Computational Linguistics, 2005
Abstract: Journal Article ; Recent systems have been developed for sentiment classification, opinion recognition, and opinion analysis (e.g., detecting polarity and strength). We pursue another aspect of opinion analysis: identifying the sources of opinions, emotions, and sentiments. We view this problem as an information extraction task and adopt a hybrid approach that combines Conditional Random Fields (Lafferty et al., 2001) and a variation of AutoSlog (Riloff, 1996a). While CRFs model source identification as a sequence tagging task, AutoSlog learns extraction patterns. Our results show that the combination of these two methods performs better than either one alone. The resulting system identifies opinion sources with 79:3% precision and 59:5% recall using a head noun matching measure, and 81:2% precision and 60:6% recall using an overlap measure.
Keyword: AutoSlog; Conditional random fields; Information retrieval; Opinion analysis; Opinion recognition; Sentiment classification; Sources of opinions
URL: https://collections.lib.utah.edu/ark:/87278/s6v12p0n
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13
Unsupervised learning of contextual role knowledge for coreference resolution
Riloff, Ellen M.; Bean, David. - : Association for Computational Linguistics, 2004
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14
Learning subjective nouns using extraction pattern bootstrapping
Wiebe, Janyce; Wilson, Theresa; Riloff, Ellen M.. - : Association for Computational Linguistics, 2003
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15
Learning extraction patterns for subjective expressions
Riloff, Ellen M.; Wiebe, Janyce. - : Association for Computational Linguistics, 2003
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16
Exploiting strong syntactic heuristics and co-training to learn semantic lexicons
Phillips, William; Riloff, Ellen M.. - : Association for Computational Linguistics, 2002
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17
Bootstrapping method for learning semantic lexicons using extraction pattern contexts
Riloff, Ellen M.; Thelen, Michael. - : Association for Computational Linguistics, 2002
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18
Inducing information extraction systems for new languages via cross-language projection
Riloff, Ellen M.; Schafer, Charles; Yarowsky, David. - : Association for Computational Linguistics, 2002
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19
Looking under the hood: tools for diagnosing your question answering engine
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20
Rule-based question answering system for reading comprehension tests
Thelen, Michael; Riloff, Ellen M.. - : Association for Computational Linguistics, 2000
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