Lexalytics

JULY 12, 2023

We’ve pioneered a number of industry firsts, including the first commercial sentiment analysis engine, the first Twitter/microblog-specific text analytics in 2010, the first semantic understanding based on Wikipedia in 2011, and the first unsupervised machine learning model for syntax analysis in 2014.

NLP 98

NLP Natural Language Processing Text Analytics BERT 98

Towards AI

JULY 20, 2023

BioBERT and similar BERT-based NER models are trained and fine-tuned using a biomedical corpus (or dataset) such as NCBI Disease, BC5CDR, or Species-800. Data formats for inputting data into NER models typically include Pandas DataFrame or text files in CoNLL format (ie. a text file with one word per line). This study by Bui et al.

Data Extraction 82

Data Extraction NLP Natural Language Processing Automation 82

O'Reilly Media

APRIL 23, 2024

Google and Amazon were still atop their respective hills of web search and ecommerce in 2010, and Meta’s growth was still accelerating, but it was hard to miss that internet growth had begun to slow. It was certainly obvious to outsiders how disruptive BERT could be to Google Search. The market was maturing.

BERT 108

BERT Algorithm AI AI 108

TensorFlow

SEPTEMBER 11, 2023

The dataset is stored in a single CSV file, with one transaction per line: $ head -n 5 sales.csv timestamp,client,product,price 2010 - 10 -05 11 :09: 56 ,c64,p35, 405.35 2010 -09- 27 15 : 00 : 49 ,c87,p29, 605.35 2010 -09-09 12 : 58 : 33 ,c97,p10, 108.99 2010 -09-06 12 : 43 : 45 ,c60,p85, 443.35

Machine Learning 120

Machine Learning BERT ML Data Analysis 120

Allen AI

NOVEMBER 27, 2023

Transformer models like BERT , which are pre-trained on large quantities of text, are the go-to approach these days for embedding text in a semantic space. These vectors are then used either to find similar documents or as features in a computationally cheap model. A variety of such embedding models are available for users to choose from.

BERT 98

BERT AI AI 98

Lexalytics

APRIL 5, 2021

Ignore the plateau around 2010: this is probably an artifact of the incompleteness of the MAG dump.) The base model of BERT [ 103 ] had 12 (!) And what’s more, Google made BERT publicly available, so that everyone could have access to contextual word vectors. BERT is just too good not to use.

Neural Network 52

Neural Network Convolutional Neural Networks Natural Language Processing BERT 52

Sebastian Ruder

DECEMBER 6, 2021

Reading Comprehension assumes a gold paragraph is provided Standard approaches for reading comprehension build on pre-trained models such as BERT. Using BERT for reading comprehension involves fine-tuning it to predict a) whether a question is answerable and b) whether each token is the start and end of an answer span.

BERT 52

BERT NLP Natural Language Processing Computational Linguistics 52