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  2. Automatic summarization - Wikipedia

    en.wikipedia.org/wiki/Automatic_summarization

    Abstractive summarization methods generate new text that did not exist in the original text. [12] This has been applied mainly for text. Abstractive methods build an internal semantic representation of the original content (often called a language model), and then use this representation to create a summary that is closer to what a human might express.

  3. Multi-document summarization - Wikipedia

    en.wikipedia.org/wiki/Multi-document_summarization

    Multi-document summarization is an automatic procedure aimed at extraction of information from multiple texts written about the same topic. The resulting summary report allows individual users, such as professional information consumers, to quickly familiarize themselves with information contained in a large cluster of documents.

  4. Marketing and artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Marketing_and_artificial...

    Marketing is a complex field of decision making which involves a large degree of both judgment and intuition on behalf of the marketer. [10] The enormous increase in complexity that the individual decision-maker faces renders the decision-making process almost an impossible task. The marketing decision engine can help distill the noise.

  5. Email marketing - Wikipedia

    en.wikipedia.org/wiki/Email_marketing

    Email marketing is the act of sending a commercial message, typically to a group of people, using email. In its broadest sense, every email sent to a potential or current customer could be considered email marketing. It involves using email to send advertisements, request business, or solicit sales or donations. The term usually refers to ...

  6. Text mining - Wikipedia

    en.wikipedia.org/wiki/Text_mining

    Text mining technology is now broadly applied to a wide variety of government, research, and business needs. All these groups may use text mining for records management and searching documents relevant to their daily activities. Legal professionals may use text mining for e-discovery, for example.

  7. Perplexity AI - Wikipedia

    en.wikipedia.org/wiki/Perplexity_AI

    Perplexity AI is a conversational search engine that uses large language models (LLMs) to answer queries using sources from the web and cites links within the text response. [3] Its developer, Perplexity AI, Inc., is based in San Francisco, California .

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