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Hits 101 – 120 of 287

101
Pyconcordancer ...
Rahimi, Adel. - : Zenodo, 2015
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102
Kurmanji Stemmer ...
Rahimi, Adel. - : Zenodo, 2015
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103
Corpkit: Corpkit User Interface ...
McDonald, D.. - : Zenodo, 2015
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104
Kurmanji-Stemmer: The Second Release ...
Rahimi, Adel. - : Zenodo, 2015
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105
Advanced natural language processing and temporal mining for clinical discovery ...
Mehrabi, Saeed. - : IUPUI University Library, 2015
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106
Condition-specific differential subnetwork analysis for biological systems ...
Jhamb, Deepali. - : IUPUI University Library, 2015
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107
Tree-adjoining machine translation ...
DeNeefe, Steve. - : University of Southern California Digital Library (USC.DL), 2015
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108
Weighted tree automata and transducers for syntactic natural language processing ...
May, Jonathan David Louis. - : University of Southern California Digital Library (USC.DL), 2015
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109
Advanced natural language processing and temporal mining for clinical discovery
Mehrabi, Saeed. - 2015
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110
Condition-specific differential subnetwork analysis for biological systems
Jhamb, Deepali. - 2015
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111
Semantically-enriched parsing for natural language understanding ...
Tratz, Stephen Charles. - : University of Southern California Digital Library (USC.DL), 2015
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112
Data from: A Convolution Kernel Approach to Identifying Comparisons in Text ...
TKACHENKO Hady W. LAUW Maksim. - : SMU Research Data Repository (RDR), 2015
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113
Data from: A Convolution Kernel Approach to Identifying Comparisons in Text ...
TKACHENKO Hady W. LAUW Maksim. - : SMU Research Data Repository (RDR), 2015
Abstract: This record contains the underlying research data for the publication "A Convolution Kernel Approach to Identifying Comparisons in Text" and the full-text is available from: https://ink.library.smu.edu.sg/sis_research/2891Comparisons in text, such as in online reviews, serve as useful decision aids. In this paper, we focus on the task of identifying whether a comparison exists between a specific pair of entity mentions in a sentence. This formulation is transformative, as previous work only seeks to determine whether a sentence is comparative, which is presumptuous in the event the sentence mentions multiple entities and is comparing only some, not all, of them. Our approach leverages not only lexical features such as salient words, but also structural features expressing the relationships among words and entity mentions. To model these features seamlessly, we rely on a dependency tree representation, and investigate the applicability of a series of tree kernels. This leads to the development of a new ...
Keyword: 200402 Computational Linguistics; 80107 Natural Language Processing; FOS Computer and information sciences; FOS Languages and literature
URL: https://dx.doi.org/10.25440/smu.12062850.v1
https://researchdata.smu.edu.sg/articles/dataset/Data_from_A_Convolution_Kernel_Approach_to_Identifying_Comparisons_in_Text/12062850/1
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114
Quantity and Quality: Not a Zero-Sum Game ... : Quantität und Qualität: kein Nullsummenspiel ...
Alday, Phillip Marshel. - : Philipps-Universität Marburg, 2015
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115
Emotional Facial Expressions in Synthesised Sign Language Avatars: a Manual Evaluation.
In: Other Resources (2015)
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116
Providing Objective Metrics of Team Communication Skills via Interpersonal coordination Mechanisms
In: Conference Papers (2015)
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117
Dependency Tree Annotation Software
In: DTIC (2015)
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118
Structural Complexity in Linguistic Systems Research Topic 3: Mathematical Sciences
In: DTIC (2015)
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119
A Study on the Efficacy of Sentiment Analysis in Author Attribution
In: Electronic Theses and Dissertations (2015)
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120
SIMPLIFICATION OF VOCAL TRACT SHAPES WITH DIFFERENT LEVELS OF DETAIL
Arnela, Marc; Engwall, Olov; Dabbaghchian, Saeed. - : KTH, Tal-kommunikation, 2015. : University of Glasgow, 2015
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