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HotFlip: White-Box Adversarial Examples for Text Classification
TLDR
We propose an efficient method to generate white-box adversarial examples to trick a character-level neural classifier. Expand
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Ontology-based information extraction: An introduction and a survey of current approaches
TLDR
We provide an introduction to ontology-based information extraction (OBIE) and review the details of different OBIE systems developed so far. Expand
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Ontology Translation on the Semantic Web
TLDR
Ontology translation is required when translating datasets, generating ontology extensions and querying through different ontologies. Expand
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HotFlip: White-Box Adversarial Examples for NLP
TLDR
We propose an efficient method to generate white-box adversarial examples that trick character-level and word-level neural models. Expand
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On Adversarial Examples for Character-Level Neural Machine Translation
TLDR
We investigate adversarial examples for character-level neural machine translation (NMT), and contrast black-box adversaries with a novel white-box adversary, which employs differentiable string-edit operations to rank adversarial changes. Expand
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Ontology translation by ontology merging and automated reasoning
TLDR
This paper describes ontology translation in three categories: dataset translation, ontology extension generation and querying through different ontologies. Expand
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Discovering Executable Semantic Mappings Between Ontologies
TLDR
This paper presents an systematic approach to combining ontology matching, object reconciliation and multi-relational data mining to find the executable mapping rules in a highly automatic manner. Expand
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Semantic data mining: A survey of ontology-based approaches
TLDR
Semantic Data Mining refers to the data mining tasks that systematically incorporate domain knowledge, especially formal semantics, into the process. Expand
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Calculating Feature Weights in Naive Bayes with Kullback-Leibler Measure
TLDR
We propose a new feature weighting method for calculating the weights of features in naive Bayesian learning using Kullback-Leibler measure. Expand
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Learning to Refine an Automatically Extracted Knowledge Base Using Markov Logic
TLDR
A number of text mining and information extraction projects such as Text Runner and NELL seek to automatically build knowledge bases from the rapidly growing amount of information on the web. Expand
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