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Chinese Story Generation with FastText Transformer Network
2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC), 2019The sequence transformer models are based on complex recurrent neural network or convolutional networks that include an encoder and a decoder. High-accuracy models are usually represented by used connect the encoder and decoder through an attention mechanism. Story generation is an important thing.
Jhe-Wei Lin, Yu-Che Gao, Rong-Guey Chang
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Devise Sparse Compression Schedulers to Enhance FastText Methods
49th International Conference on Parallel Processing - ICPP : Workshops, 2020In natural language processing(NLP), the general way to understand the meaning of a word is via word embedding. The word embedding training model can convert words into multidimensional vectors and make the words that do not know “meaning” into vectors with “meaning”. Famous word embedding training models, include models such as FastText, Word2Vec, and
Chen-Ting Chao +5 more
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Cyberbullying Detection, Based on the FastText and Word Similarity Schemes
ACM Transactions on Asian and Low-Resource Language Information Processing, 2020With recent developments in online social networks (OSNs), these services are widely applied in daily lives. On the other hand, cyberbullying, which is a relatively new type of harassment through the internet-based electronic devices, is rising in online social networks.
Kun Wang 0023 +5 more
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Automated Short Answer Grading Using Fasttext
Lecture Notes in Networks and SystemsSampa Das, Udit Kumar Chakraborty
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Adaptive GloVe and FastText Model for Hindi Word Embeddings
Proceedings of the 7th ACM IKDD CoDS and 25th COMAD, 2020Today, a lot of research is carried out on word embeddings in NLP domain. The algorithms like GloVe, FastText are used to develop word embeddings. However, not enough work is done on Indian languages due to lack of resource availability. The datasets required for testing word embeddings are not available for Indian languages.
Vijay Gaikwad, Yashodhara Haribhakta
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Deception Detection and Analysis in Spoken Dialogues based on FastText
2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), 2018Detecting deception is complicated for humans even though it often happens in human communications. In contrast, machines can capture small features to achieve accurate deception-detection, which is difficult for humans. Classifiers based on supervised learning make it possible to analyze effective features for deception-detection by giving positive ...
Naoki Hosomi +3 more
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Computational implementations of semantic knowledge represent the meaning of words as numerical vectors, derived from their usage in (natural) language. This methodology, known as distributional semantics, has seen substantial advancements, such as the extension reviewed in this article: fastText.
Bonandrini, R, Gatti, D.
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Bonandrini, R, Gatti, D.
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Performance Comparison of Word2vec and fastText Embedding Models
Journal of Digital Contents Society, 2020Word2vec 임베딩 모델은 단순하고 성능이 우수하기 때문에, 자연어 처리 분야에서 가장 널리 쓰이는 모델 중 하나이지만 몇 가지 한계도 있다. 이런 한계를 극복하기 위해 일반적인 언어에 적용 가능한 fastText 임베딩 모델이 제안되었고, 이후 한국어에 적합한 특정한 fastText 모델도 제안되었다. 본 연구는 유사도 검사, 유추 검사 및 감정 분석을 통해 몇 가지 word2vec 및 fastText 모델의 성능을 비교 평가하는 것을 목표로 한다. fastText 모델을 제안한 이전 연구의 결과와는 달리, 최소한 유추 검사와 감정 분석의 측면에서는 fastText 모델이 word2vec 모델보다 더 우수하다고 단정 지을
Hyungsuc Kang, Janghoon Yang
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A Fusion Method for Word Vector Based on Fasttext-KdTree
2019 Seventh International Conference on Advanced Cloud and Big Data (CBD), 2019Text categorization is an important part of the field of natural language processing, and it is also one of the current research hot issues. However, at present, text categorization technology still faces the problem of losing some semantic information caused by new words.
Yu Dai 0001 +4 more
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On the Use of Phonotactic Vector Representations with FastText for Language Identification
2020This paper explores a better way to learn word vector representations for language identification (LID). We have focused on a phonotactic approach using phoneme sequences in order to make phonotactic units (phone-grams) to incorporate context information.
David Romero, Christian Salamea
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