enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. Prompt engineering - Wikipedia

    en.wikipedia.org/wiki/Prompt_engineering

    The question vectors are clustered. Questions nearest to the centroids of each cluster are selected. An LLM does zero-shot CoT on each question. The resulting CoT examples are added to the dataset. When prompted with a new question, CoT examples to the nearest questions can be retrieved and added to the prompt.

  3. Sentiment analysis - Wikipedia

    en.wikipedia.org/wiki/Sentiment_analysis

    Sentiment analysis (also known as opinion mining or emotion AI) is the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information.

  4. Semantic parsing - Wikipedia

    en.wikipedia.org/wiki/Semantic_parsing

    Examples of these insights include sentiment analysis, topic modelling, and trend analysis. Question Answering Systems: Found in systems such as IBM Watson, these systems assist in comprehending and analyzing natural language queries in order to deliver precise responses. They are particularly helpful in areas such as customer service and ...

  5. Multimodal sentiment analysis - Wikipedia

    en.wikipedia.org/wiki/Multimodal_sentiment_analysis

    Multimodal sentiment analysis also plays an important role in the advancement of virtual assistants through the application of natural language processing (NLP) and machine learning techniques. [5] In the healthcare domain, multimodal sentiment analysis can be utilized to detect certain medical conditions such as stress, anxiety, or depression. [8]

  6. Spark NLP - Wikipedia

    en.wikipedia.org/wiki/Spark_NLP

    Spark NLP for Healthcare is a commercial extension of Spark NLP for clinical and biomedical text mining. [10] It provides healthcare-specific annotators, pipelines, models, and embeddings for clinical entity recognition, clinical entity linking, entity normalization, assertion status detection, de-identification, relation extraction, and spell checking and correction.

  7. Apache OpenNLP - Wikipedia

    en.wikipedia.org/wiki/Apache_OpenNLP

    The Apache OpenNLP library is a machine learning based toolkit for the processing of natural language text. It supports the most common NLP tasks, such as language detection, tokenization, sentence segmentation, part-of-speech tagging, named entity extraction, chunking, parsing and coreference resolution.

  8. Natural-language programming - Wikipedia

    en.wikipedia.org/wiki/Natural-language_programming

    Natural-language programming (NLP) is an ontology-assisted way of programming in terms of natural-language sentences, e.g. English. [1] A structured document with Content, sections and subsections for explanations of sentences forms a NLP document, which is actually a computer program .

  9. Transformer (deep learning architecture) - Wikipedia

    en.wikipedia.org/wiki/Transformer_(deep_learning...

    sentiment analysis [1] paraphrasing [1] The T5 transformer report [47] documents a large number of natural language pretraining tasks. Some examples are: restoring or repairing incomplete or corrupted text. For example, the input, "Thank you ~~ me to your party ~~ week", might generate the output, "Thank you for inviting me to your party last ...