Results 91 to 100 of about 4,133 (219)

Model architecture of fastText classification model.

, 2020
Model architecture of fastText classification model.
Yong Fang (301344), Liang Liu (50022), Yongcheng Liu (2467399), Cheng Huang (115619)   +3 more
core   +1 more source

NCHLT Setswana fastText-Skipgram embeddings

, 2023
Static word and subword embeddings for the Skipgram flavour of the fastText architecture (Bojanowski et al., 2017).
Roald Eiselen
core   +1 more source

From Sparse Features to Transformers: A Statistical Evaluation of TF-IDF, FastText, and IndoBERT for Sentiment Classification of Indonesian Travel App Reviews

Journal of Applied Informatics and Computing
This study compares three text representation techniques, namely TF-IDF, FastText, and IndoBERT, in the sentiment classification task of Indonesian-language user reviews of travel applications.
Claudian Tikulimbong Tangdilomban, Syaifullah Yusuf Ramdhan, Muhammad Rizal, Cici Suhaeni, Bagus Sartono   +4 more
doaj   +1 more source

Kubord-fasttext - Aftonbladet 2010–2024 - token

Kubord-fasttext is a collection of fasttext models, developed within a collaboration between KBLab and Språkbanken Text, that have been trained on the same underlying data as Kubord 2. The models have been trained on the token and the lemma level.
https://ror.org/03xfh2n14
core   +1 more source

NCHLT Siswati fastText-Skipgram embeddings

, 2023
Static word and subword embeddings for the Skipgram flavour of the fastText architecture (Bojanowski et al., 2017).
Roald Eiselen
core   +1 more source

Kubord-fasttext - Aftonbladet 2010–2022 - lemma

Kubord-fasttext is a collection of fasttext models, developed within a collaboration between KBLab and Språkbanken Text, that have been trained on the same underlying data as Kubord 2. The models have been trained on the token and the lemma level.
https://ror.org/03xfh2n14
core   +1 more source

Mendeteksi Emosi Berdasarkan Postingan Sosial Media X Menggunakan Algoritma Long Short-Term Memory

Techno.Com
Emosi merupakan aspek penting dalam komunikasi manusia yang sering muncul melalui unggahan di media sosial. Emosi tersebut diekspresikan dalam teks berbahasa Indonesia di platform media sosial X.
Irni Irana Ainin Nadhiroh, Mohammad Zoqi Sarwani, Muhammad Udin   +2 more
doaj   +1 more source

Kubord-fasttext - Aftonbladet 2010–2022 - token

Kubord-fasttext is a collection of fasttext models, developed within a collaboration between KBLab and Språkbanken Text, that have been trained on the same underlying data as Kubord 2. The models have been trained on the token and the lemma level.
https://ror.org/03xfh2n14
core   +1 more source

Capturing Subword Information: FastText

This chapter provides a comprehensive analysis of the FastText language model, contrasting it with earlier architectures like Word2Vec and GloVe. It begins by identifying a fundamental limitation of previous models: their treatment of words as atomic, indivisible units.
openaire   +1 more source

Kubord-fasttext - Göteborgsposten 2013–2024 - lemma

Kubord-fasttext is a collection of fasttext models, developed within a collaboration between KBLab and Språkbanken Text, that have been trained on the same underlying data as Kubord 2. The models have been trained on the token and the lemma level.
https://ror.org/03xfh2n14
core   +1 more source