A comprehensive survey on word representation models: From classical to state-of-the-art word representation language models
Word representation has always been an important research area in the history of natural
language processing (NLP). Understanding such complex text data is imperative, given that …
language processing (NLP). Understanding such complex text data is imperative, given that …
Point-of-interest recommender systems based on location-based social networks: a survey from an experimental perspective
P Sánchez, A Bellogín - ACM Computing Surveys (CSUR), 2022 - dl.acm.org
Point-of-Interest recommendation is an area of increasing research and development
interest within the widely adopted technologies known as Recommender Systems. Among …
interest within the widely adopted technologies known as Recommender Systems. Among …
Deep learning for anomaly detection: A survey
R Chalapathy, S Chawla - arXiv preprint arXiv:1901.03407, 2019 - arxiv.org
Anomaly detection is an important problem that has been well-studied within diverse
research areas and application domains. The aim of this survey is two-fold, firstly we present …
research areas and application domains. The aim of this survey is two-fold, firstly we present …
Detecting formal thought disorder by deep contextualized word representations
J Sarzynska-Wawer, A Wawer, A Pawlak… - Psychiatry …, 2021 - Elsevier
Computational linguistics has enabled the introduction of objective tools that measure some
of the symptoms of schizophrenia, including the coherence of speech associated with formal …
of the symptoms of schizophrenia, including the coherence of speech associated with formal …
Perbandingan Kinerja Word Embedding Word2Vec, Glove, Dan Fasttext Pada Klasifikasi Teks
Karakteristik teks yang tidak terstruktur menjadi tantangan dalam ekstraksi fitur pada bidang
pemrosesan teks. Penelitian ini bertujuan untuk membandingkan kinerja dari word …
pemrosesan teks. Penelitian ini bertujuan untuk membandingkan kinerja dari word …
A comparative study on word embeddings in deep learning for text classification
Word embeddings act as an important component of deep models for providing input
features in downstream language tasks, such as sequence labelling and text classification …
features in downstream language tasks, such as sequence labelling and text classification …
[HTML][HTML] Detection of fake news using deep learning CNN–RNN based methods
IK Sastrawan, IPA Bayupati, DMS Arsa - ICT express, 2022 - Elsevier
Fake news is inaccurate information that is intentionally disseminated for a specific purpose.
If allowed to spread, fake news can harm the political and social spheres, so several studies …
If allowed to spread, fake news can harm the political and social spheres, so several studies …
Ensembling classical machine learning and deep learning approaches for morbidity identification from clinical notes
The past decade has seen an explosion of the amount of digital information generated
within the healthcare domain. Digital data exist in the form of images, video, speech …
within the healthcare domain. Digital data exist in the form of images, video, speech …
Text similarity in vector space models: a comparative study
O Shahmirzadi, A Lugowski… - 2019 18th IEEE …, 2019 - ieeexplore.ieee.org
Automatic measurement of semantic text similarity is an important task in natural language
processing. In this paper, we evaluate the performance of different vector space models to …
processing. In this paper, we evaluate the performance of different vector space models to …
[HTML][HTML] i-Pulse: A NLP based novel approach for employee engagement in logistics organization
Although most logistics and freight forwarding organizations, in one way or another, claim to
have core values. The engagement of employees is a vast structure that affects almost every …
have core values. The engagement of employees is a vast structure that affects almost every …