Results 51 to 60 of about 29,472 (315)
Efficient estimation of Hindi WSD with distributed word representation in vector space
Journal of King Saud University: Computer and Information Sciences, 2022 Word Sense Disambiguation (WSD) is significant for improving the accuracy of the interpretation of a Natural language text. Various supervised learning-based models and knowledge-based models have been developed in the literature for WSD of the language ...
Archana Kumari, D.K. Lobiyal
doaj
Attention Neural Network for Biomedical Word Sense Disambiguation
Discrete Dynamics in Nature and Society, 2022 In order to improve the disambiguation accuracy of biomedical words, this paper proposes a disambiguation method based on the attention neural network. The biomedical word is viewed as the center. Morphology, part of speech, and semantic information from
Chun-Xiang Zhang +4 more
doaj +1 more source
A Corpus-Based Word Sense Disambiguation For Geez Language
Ethiopian Journal of Science and Sustainable Development, 2021 In natural language processing, languages have a number of ambiguous words and solving such kind of problem for the language can help the development of word sense disambiguation using corpusbased Approach.
Amlakie Aschale Alemu, Kinde Anlay Fante
doaj +1 more source
The impact of imbalanced training data on machine learning for author name disambiguation [PDF]
Kim, J. & Kim, J. (2018). The impact of imbalanced training data
on machine learning for author name disambiguation. Scientometrics, 2018 In supervised machine learning for author name disambiguation, negative training data are often dominantly larger than positive training data. This paper examines how the ratios of negative to positive training data can affect the performance of machine learning algorithms to disambiguate author names in bibliographic records.
arxiv +1 more source
Improving Data Integration through Disambiguation Techniques [PDF]
, 2008 In this paper Word Sense Disambiguation (WSD) issue in the context of data integration is outlined and an Approximate Word Sense Disambiguation approach (AWSD) is proposed for the automatic lexical annotation of structured and semi-structured data ...
PO, Laura
core +2 more sources
Memory-based word sense disambiguation
Computers and the humanities, 1999 We describe a memory-based classification architecture for word sense disambiguation and its application to the SENSEVAL evaluation task. For each ambiguous word, a semantic word expert is automatically trained using a memory-based approach. In each expert, selecting the correct sense of a word in a new context is achieved by finding the closest match ...
Veenstra, J. +4 more
openaire +6 more sources
WORD SENSE DISAMBIGUATION FOR TAMIL LANGUAGE USING PART-OF-SPEECH AND CLUSTERING TECHNIQUE [PDF]
Journal of Engineering Science and Technology, 2017 Word sense disambiguation is an important task in Natural Language Processing (NLP), and this paper concentrates on the problem of target word selection in machine translation.
P. ISWARYA, V. RADHA
doaj
TWE‐WSD: An effective topical word embedding based word sense disambiguation
CAAI Transactions on Intelligence Technology, 2021 Word embedding has been widely used in word sense disambiguation (WSD) and many other tasks in recent years for it can well represent the semantics of words.
Lianyin Jia +5 more
doaj +1 more source
Retrieving with good sense [PDF]
, 2000 Although always present in text, word sense ambiguity only recently became regarded as a problem to information retrieval which was potentially solvable.
Sanderson, M.
core +2 more sources
Biomedical Word Sense Disambiguation Based on Graph Attention Networks
IEEE Access, 2022 Biomedical words have many semantics. Biomedical word sense disambiguation (WSD) is an important research issue in biomedicine field. Biomedical WSD refers to the process of determining meanings of ambiguous word according to its context.
Chun-Xiang Zhang +2 more
doaj +1 more source