Results 231 to 240 of about 35,833 (287)
An Adaptive Method for Organization Name Disambiguation with Feature Reinforcing
An Adaptive Method for Organization Name Disambiguation with Feature Reinforcingopenaire
Towards Manipuri Tonal Contrast Disambiguation Using Acoustic Features
2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST), 2022 Thiyam Susma Devi, Pradip K. Das
openaire +2 more sources
Some of the next articles are maybe not open access.
Related searches:
Related searches:
Multiple Features Driven Author Name Disambiguation
2021 IEEE International Conference on Web Services (ICWS), 2021Author Name Disambiguation (AND) has received more attention recently, accompanied by the increase of academic publications. To tackle the AND problem, existing studies have proposed many approaches based on different types of information, such as raw document feature (e.g., co-author, title, and keywords), fusion feature (e.g., a hybrid publication ...
Qian Zhou +4 more
openaire +1 more source
Topological Features Based Entity Disambiguation
Journal of Computer Science and Technology, 2016This work proposes an unsupervised topological features based entity disambiguation solution. Most existing studies leverage semantic information to resolve ambiguous references. However, the semantic information is not always accessible because of privacy or is too expensive to access.
Chen-Chen Sun +4 more
openaire +1 more source
Feature expansion for word sense disambiguation
International Conference on Natural Language Processing and Knowledge Engineering, 2003. Proceedings. 2003, 2004One of the most serious obstacles in research on word sense disambiguation (WSD) is sparseness of training data. We describe and motivate a method of feature expansion as a means of resolving the data sparseness problem in supervised corpus-based WSD. The expanded features are extracted from an existing corpus and WordNet automatically.
null Nai-Lung Tsao +2 more
openaire +1 more source
Automatic author name disambiguation by differentiable feature selection
Journal of Information Science, 2023Author name disambiguation (AND) is the task of resolving the ambiguity problem in bibliographic databases, where distinct real-world authors may share the same name or same author may have distinct names. The aim of AND is to split the name-ambiguous entities (articles) into the corresponding authors. Existing AND algorithms mainly focus on designing
ZhiJian Fang +5 more
openaire +1 more source
Word sense disambiguation method with topic feature
IET International Conference on Information Science and Control Engineering 2012 (ICISCE 2012), 2012Word sense disambiguation (WSD) is usually confined in a sentence, which results in short text. Moreover, the deficiency of sense-labelled corpus incurs serious data sparsity. Short text and data sparsity hinder the performance improvement of WSD. As an unsupervised learning method, topic model tries to cluster and compress semantic information in the ...
null Yun Zhou +3 more
openaire +1 more source
Partial Label Learning via Feature-Aware Disambiguation
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016Partial label learning deals with the problem where each training example is represented by a feature vector while associated with a set of candidate labels, among which only one label is valid. To learn from such ambiguous labeling information, the key is to try to disambiguate the candidate label sets of partial label training examples.
Min-Ling Zhang +2 more
openaire +1 more source
Unsupervised word sense disambiguation with N-gram features
Artificial Intelligence Review, 2012The present paper concentrates on the issue of feature selection for unsupervised word sense disambiguation (WSD) performed with an underlying Naive Bayes model. It introduces web N-gram features which, to our knowledge, are used for the first time in unsupervised WSD.
Daniel Preotiuc-Pietro +1 more
openaire +1 more source