Embedding Meaning: Definition, Examples, and Translations
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embedding
[ɪmˈbɛdɪŋ ]
Definition
data representation
Embedding refers to a method of representing data in a lower-dimensional space, typically used in machine learning and natural language processing. It allows for the transformation of complex data into a vector format that can be easily processed by algorithms. Common forms of embedding include word embeddings such as Word2Vec or GloVe, which capture semantic meanings of words. These representations are essential for tasks like sentiment analysis, translation, and information retrieval.
Synonyms
mapping, representation, vectorization.
Examples of usage
- Word embeddings help improve the accuracy of NLP tasks.
- The model uses image embeddings to classify photos.
- Using embeddings, the algorithm can understand similarities between words.
Translations
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Interesting Facts
Technology
- In computer science, embedding often refers to integrating one set of information into another, such as images or videos into websites.
- Word embeddings in natural language processing help machines understand the meanings of words by placing them in a multi-dimensional space based on context.
- Machine learning uses embeddings to improve the performance of algorithms on tasks like recommendation systems by combining data in intuitive ways.
Psychology
- The process of embedding memories involves repetition and emotional connection, making certain experiences more vivid and memorable.
- Therapeutic techniques often use embedding to help individuals internalize positive thoughts by integrating them into their self-image.
- Cognitive behavioral therapy may involve embedding new behavior patterns into daily life to foster lasting change.
Literature
- Literary embedding refers to authors incorporating stories within stories, creating layers of narrative that enhance depth and understanding.
- Postmodern writers often utilize embedding as a technique to challenge traditional storytelling, making readers reflect on the boundaries of fiction.
- Embedded narratives can also symbolize how interconnected our thoughts and emotions are, reflecting complex human experiences.
Education
- 'Embedding' in educational contexts can refer to integrating skills across subjects, like combining math with art to foster comprehensive learning.
- In digital learning, educators embed quizzes or videos into lessons, creating engaging and interactive experiences.
- The concept encourages teachers to weave critical thinking and problem-solving skills throughout different subjects for holistic education.
Origin of 'embedding'
Main points about word origin
- The term 'embedding' comes from the Old English word 'embeddan', meaning to 'fix firmly in' or 'to place into'.
- Originally used in the context of construction and art, it describes literally placing objects into a material so they are secured.
- The concept has evolved in modern usage to include digital and technical applications, reflecting advancements in technology.
The term 'embedding' has its roots in the concept of embedding in mathematics, where it denotes the inclusion of one structure within another. In computer science, particularly in the fields of machine learning and neural networks, the term has been adopted to describe the process of converting high-dimensional data into a low-dimensional vector space. This transformation simplifies the data and helps capture its essential features. The development of word embeddings in the 2010s, especially with algorithms like Word2Vec introduced by Google in 2013, propelled the use of the term into the mainstream of artificial intelligence applications. As machine learning techniques grew more sophisticated, embeddings expanded beyond text, finding applications in images, graphs, and more, significantly impacting data representation across various domains.