Results 231 to 240 of about 631,702 (254)
Some of the next articles are maybe not open access.
A Distributed Architecture System for Recognizing Textual Entailment
Ninth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC 2007), 2007Solving complex problems has become a usual fact in the natural language processing domain, where it is normal to use large information databases like lexicons, semantic relations, dictionaries. This paper describes the steps followed in building the system participating in the RTE3 competition.
Adrian Iftene +2 more
openaire +1 more source
A simple hybrid approach to recognizing textual entailment
Journal of Intelligent & Fuzzy Systems, 2018We explore various machine learning-based classifiers applied to rule-based features for recognizing textual entailment. The features, extracted with a set of synthesized matching rules, reflect syntactic and semantic similarity between the text and the hypothesis. The fact that we use only seven relatively simple features makes our method suitable for
Rohini Basak +2 more
openaire +1 more source
Recognizing Textual Entailment Using Inference Phenomenon
2018Inference phenomena refer to inference relations in local fragments between two texts. Current research on inference phenomenon focuses on the construction of data annotation, whereas there are few research on how to identify those inference phenomena in texts, which will contributes to improving the performance of recognizing textual entailment.
Han Ren, Xia Li, Wenhe Feng, Jing Wan
openaire +2 more sources
Recognizing Textual Entailment: Is Word Similarity Enough?
2006We describe the system we used at the PASCAL-2005 Recognizing Textual Entailment Challenge. Our method for recognizing entailment is based on calculating “directed” sentence similarity: checking the directed “semantic” word overlap between the text and the hypothesis.
Valentin Jijkoun, Maarten de Rijke
openaire +1 more source
Recognizing Textual Entailment with Attentive Reading and Writing Operations
2018Inferencing the entailment relations between natural language sentence pairs is fundamental to artificial intelligence. Recently, there is a rising interest in modeling the task with neural attentive models. However, those existing models have a major limitation to keep track of the attention history because usually only one single vector is utilized ...
Liang Liu 0015 +5 more
openaire +2 more sources
Recognizing Textual Entailment and Computational Semantics
2014Recognizing textual entailment (RTE)—deciding whether one piece of text contains new information with respect to another piece of text—remains a big challenge in natural language processing. One attempt to deal with this problem is combining deep semantic analysis and logical inference, as is done in the Nutcracker RTE system.
openaire +2 more sources
Towards Better Ontological Support for Recognizing Textual Entailment
2010Many applications in modern information technology utilize ontological knowledge to increase their performance, precision, and success rate. However, the integration of ontological sources is in general a difficult task since the semantics of all concepts, individuals, and relations must be preserved across the various sources. In this paper we discuss
openaire +2 more sources
QRNN-Transformer: Recognizing Textual Entailment
2024 IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)Xiaogang Zhu 0003 +5 more
openaire +2 more sources
Refining the Judgment Threshold to Improve Recognizing Textual Entailment Using Similarity
Lecture Notes in Computer Science, 2012Quang-Thuy Ha
exaly