Category: Natural Language Processing

Natural language processing (NLP) is a subfield of computer science and artificial intelligence that deals with the interaction between computers and human (natural) languages. NLP technologies are used in a variety of areas, including machine translation, speech recognition, text classification, question answering, chatbots, and information extraction. In recent years, there has been a boom in NLP research, driven by advances in machine learning and artificial intelligence. As a result, NLP is now one of the most active and exciting areas of computer science.

N-Gram Analysis

An n-gram is a collection of n successive items in a text document that may include words, numbers, symbols, and punctuation. N-gram models are useful in many text analytics applications, where sequences of words are relevant such as in sentiment analysis, text classification, and text generation. Applications An n-gram model is a type of probabilistic language model for predicting the next… Read the full article

Semantic Triple

As its name indicates, a triple is a set of three entities that codifies a statement about semantic data in the form of subject-predicate-object expressions. Semantic Triple Example An example of a Semantic Triple is “Isaac is 42” or “Isaac knows Dave.” Semantic Triple Code This format enables knowledge to be represented in a machine-readable way. For… Read the full article

Semantic Clustering

Semantic keyword clustering is a powerful SEO tool that will help you organize the content, diversify your language, and rank for more terms. When you expand your list of keywords, break it down into separate closely related groups and use them to cover different user intents.

Entity Linking

Entity linking (EL) is the process of linking entity mentions appearing in web text with their corresponding entities in a knowledge base. In natural language processing, entity linking also referred to as named-entity linking (NEL), named-entity disambiguation (NED), named-entity recognition, and disambiguation (NERD) or named-entity normalization (NEN) is the task of assigning a unique identity to… Read the full article

Named Entity Recognition (NER)

Named entity recognition (NER) sometimes referred to as entity chunking, extraction, or identification; is a process that identifies and categorizes key information (named entities) in text into pre-defined categories such as: persons organizations locations expressions of times quantities monetary values percentages, etc. NER is used in many fields of Natural Language Processing (NLP), and it can help answer many… Read the full article

Stemming and Lemmatization

In the world of Natural Language Processing, there are two main methods for dealing with words: stemming and lemmatization. Stemming simply removes or “stems” the last few characters of a word, often leading to incorrect meanings and spelling. Lemmatization, on the other hand, considers the context and converts the word to its meaningful base form,… Read the full article

Natural Language Processing

Computers are the foundation of any business, and they have the ability to read information. Also, they have microphones that collect sound. A program helps to process these inputs, which are changed to a code that is easy for the machine to understand. Natural language processing is a branch of artificial intelligence that gives computers… Read the full article