Install
Natural Language Processing
Text, speech, translation, and retrieval with modern NLP techniques.
- 18 Tracked terms
- Last 30 days Feed window
What this topic collects on
An article joins this feed when it matches these terms. Each one is also a search of its own.
Related topics
Latest in Natural Language Processing
Machine Learning Use Cases: 10 Ways Machine Learning is Used in the Real World
23+ hour, 17+ min ago (702+ words) Modern ML now combines data, models, tools, and workflows across many industries. AI agents and multimodal systems are expanding machine learning from prediction toward practical task execution. Video services, online stores, music apps, and social platforms use ML to predict…...
Applied Sciences, Vol. 16, Pages 9294: Large Language Models in the Analysis of Radar Plotting Images in Accordance with COLREGs
2+ day, 18+ hour ago (392+ words) The development of artificial intelligence (AI) opens new possibilities for the automatic interpretation of radar images in maritime navigation. Traditionally, the interpretation of radar indications requires the experience of the officer of the watch, who assesses the risk of collision…...
Multidimensional semantic risk
4+ day, 12+ hour ago (197+ words) I have previously written about Tessa, the National Eating Disorders Association’s chatbot, which when quietly given generative capabilities by its vendor without the …...
Converting between cosine similarity and concentration ratio
5+ day, 11+ hour ago (239+ words) I’ve written three posts on cosine similarity lately. The first looked at interpreting cosine similarity. The second looked at an approximation related to the first. The third looked at how ranking according to cosine similarity works better than cosine similarity…...
Applied Sciences, Vol. 16, Pages 9176: A Unified Neural Framework for Punctuation and Capitalization Restoration Using XLM-RoBERTa–BiLSTM
5+ day, 18+ hour ago (485+ words) Accurate punctuation and capitalization are essential for the readability, interpretability, and structural coherence of machine-generated text. Their absence is particularly problematic in automatic speech recognition outputs and other forms of unstructured text, where missing punctuation and incorrect capitalization reduce both…...
What counts as a large cosine similarity?
6+ day, 11+ hour ago (457+ words) Machine learning represents words as vectors and measures the similarity of words by the angles between the vectors. where θ is the angle between the vectors, and so This is the cosine similarity between the words represented by x and…...
What Are Embeddings? How AI Converts Meaning Into Numbers
6+ day, 15+ hour ago (1590+ words) Consider these two sentences: "I want to buy a phone with a long-lasting battery." and "Which smartphone should I choose if I don't want to charge it frequently?" The wording barely overlaps. No shared phrase, almost no shared vocabulary. Yet…...
Vectors: How Numbers Turns Meaning Into Direction
1+ week, 1+ day ago (1288+ words) When we say -’ The boy is playing in the garden.’ we see words. Now a language model can only interpret numbers. Before an AI system can compare …...
Spherical Topic Models Bring Coherence to Short-Text Machine Learning
1+ week, 2+ day ago (55+ words) Probabilistic topic models have long served as one of the workhorses of text mining, offering a statistical lens through which vast collections of documents can be organized into interpretable themes. From latent Dirichlet allocation onward, these models have assumed that…...
Day 7: Dot Product & Cosine Similarity, and How Machines Measure Similarity
1+ week, 2+ day ago (47+ words) Part 7 of a 50-day journey from zero to building AI agents. Picking up from yesterday Yesterday we treated vectors as just …...