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Community Question Answering Ranking: Methodology Survey
References:
22
Abstract
This paper surveys the evolution of word embeddings along with the methodologies used in Community Question Answering (cQA), and how these methodologies use word embeddings to achieve higher performance metrics. The paper first discusses vector modelling and how it affected Natural Language Processing (NLP) as a whole, then it details some of the approaches used like the one-hot-encoding, word2vec...
Keywords
2022
Article
Open Access
2-Y Citation Average
0.15
Language
Country
Community Question Answering Ranking: Methodology Survey
References:
22
Abstract
This paper surveys the evolution of word embeddings along with the methodologies used in Community Question Answering (cQA), and how these methodologies use word embeddings to achieve higher performance metrics. The paper first discusses vector modelling and how it affected Natural Language Processing (NLP) as a whole, then it details some of the approaches used like the one-hot-encoding, word2vec...
Keywords
2022
Article
Open Access
2-Y Citation Average
0.15
Language
Country