[PDF] Top 20 A Study of Machine Learning Algorithms for Recognizing Textual Entailment
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A Study of Machine Learning Algorithms for Recognizing Textual Entailment
... a machine learning approach we tested with different classifiers in order to classify RTE-4 test pairs in three classes: entailment, contradiction or ... See full document
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Recognizing Textual Entailment using Dependency Analysis and Machine Learning
... As the results indicate, our dependency-based heu- ristics and lexical features have resulted in signifi- cant improvement in accuracy of RTE1, RTE2 and RTE3 datasets. DT outperforms other classifiers with only 8 ... See full document
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Types of Common Sense Knowledge Needed for Recognizing Textual Entailment
... ical study of a natural language understanding task in order to help answer these ...the Recognizing Textual Entailment (RTE) task (Dagan et ... See full document
6
A Machine Learning Approach for Recognizing Textual Entailment in Spanish
... Future work is oriented to experiment with ad- ditional lexical and semantic similarities features and to test the improvements they may yield. Also, we must explore how to decrease the computation- al cost of the ... See full document
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Recognizing Partial Textual Entailment
... partial textual entail- ...for recognizing (complete) textual entailment can be successfully adapted to this ...for recognizing complete entailment in a semi-automatic setting, ... See full document
5
Labeled Alignment for Recognizing Textual Entailment
... statistical machine translation: Parameter esti- ...2007. Learning align- ments and leveraging natural ...on Textual Entail- ment and Paraphrasing, pages ... See full document
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Controlling the effect of crowd noisy annotations in NLP Tasks
... Chapter 2 - Background Work and Concepts - This chapter provides a general overview on supervised learning approaches and Support Vector Machines (SVMs) in particular. Specifically, we focused on classification ... See full document
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Recognizing Textual Entailment in Twitter Using Word Embeddings
... In this paper, we investigate the applica- tion of machine learning techniques and word embeddings to the task of Recog- nizing Textual Entailment (RTE) in Social Media. We look at a manually ... See full document
5
Text Grouping using Textual Entailment
... Recognizing Textual Entailment task is a text classification problem, ...problem. Machine learning methods can be used to solve the textual entailment ...of machine ... See full document
7
Expanding textual entailment corpora fromWikipedia using co training
... the Recognizing Textual Entailment (RTE) challenges (Dagan et ...most textual entailment recognition systems are still below ...for machine learning systems, where the ... See full document
9
Recognizing Textual Entailment based on Deep Learning Approach
... The previous table shows the comparison between the proposed model and some different other models. Each one of them uses different approach. The first approach [6] is based on Knowledge Base Completion (KBC), Where the ... See full document
6
Logic Programs vs First Order Formulas in Textual Inference
... to textual entailment have more in common than meets the ...Many textual entailment problems used to test the Nutcracker system can be solved by the answer set solver DLV ... See full document
6
Semantic Answer Validation using Universal Networking Language
... RAVE (Real-time Answer Validation Engine) [12] is a logic-based answer validator and selector designed for application in real-time question answering. RAVE uses the same tool chain for deep linguistic analysis and the ... See full document
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Performance Impact Caused by Hidden Bias of Training Data for Recognizing Textual Entailment
... The quality of a training data is one of the crucial prob- lems when a learning-centered approach including neural network (NN) is employed. (Reidsma and Carletta, 2008) demonstrated that annotation errors of the ... See full document
6
Machine Translation Evaluation with Textual Entailment Features
... Nevertheless, there are also substantial differences between TE and MT evaluation. Crucially, TE assumes the premise and hypothesis to be well-formed sentences, which is not true in MT evaluation. Thus, a possible crit- ... See full document
5
Proceedings of the ACL 2012 System Demonstrations
... Applications of GPC Rules and Character Structures in Games for Learning Chinese Characters Wei-Jie Huang, Chia-Ru Chou, Yu-Lin Tzeng, Chia-Ying Lee and Chao-Lin Liu . . . . . . . . . . . . . . 1 Specifying ... See full document
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Análise de Medidas de Similaridade Semântica na Tarefa de Reconhecimento de Implicação Textual (Analysis of Semantic Similarity Measures in the Recognition of Textual Entailment Task)[In Portuguese]
... Text Entailment) task that verifies the similarity between two senten- ces including syntactic and semantic ...and Textual Inference) with some changes and addition of other se- mantic ... See full document
10
Multi Task Learning for Semantic Relatedness and Textual Entailment
... Multi-task Learning is a learning mechanism to improve performance on the current task after having learned a different but related concept or skill on a pre- vious ...by learning tasks in parallel ... See full document
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An overview of Natural Language Inference Data Collection: The way forward?
... way entailment tasks), most of the examples do not involve deep semantic inference but are rather complicated in terms of their ...Deep Learning approaches ... See full document
7
Semantic Parsing for Textual Entailment
... In this paper we have described an approach to TE which leans heavily on generic semantic parsing technologies, combining the off-the-shelf ERG parser with formats and tools developed for the Semantic Web and a ... See full document
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