Markos Giannopoulos
May 1 · 3 min read
Automating business news generation from quarterly earnings results. Image from Automated Insights

Not sure how, but I woke up to a scramble of googling on NLG. I got the impression out that while there are some very interesting applications like automated journalism (weather, sports, business news) as well as in business intelligence (2-page summaries of 300-page financial results), the field is not as progressed on the “opposite” side of NLG, Natural Language Processing (NLP). Here are some resources to get you (me) started.

  • Natural-language generation — Wikipedia
    Natural-language generation (NLG) is one of the tasks of natural language processing that focuses on generating natural language from structured data such as a knowledge base or a logical form (linguistics). It can be used to produce long documents that summarize or explain the contents of computer databases, for example making news reports (automated journalism), summarizing medical records, generating technical manuals, or generating product descriptions for a large e-commerce site. It can also be used to generate short blurbs of text in interactive conversations (a chatbot) which might even be read out loud by a text-to-speech system.
    https://en.m.wikipedia.org/wiki/Natural-language_generation
  • Automatic summarization — Wikipedia
    Automatic summarization is the process of shortening a text document with software, in order to create a summary with the major points of the original document. Technologies that can make a coherent summary take into account variables such as length, writing style and syntax.
    https://en.m.wikipedia.org/wiki/Automatic_summarization
  • Natural Language Generation for News Automation | Tietojenkäsittelytiede | Courses | University of Helsinki
    This course will begin with an overview of the typical technical architecture of a Natural Language Generation (NLG) system and some of the techniques used at different stages of the pipeline. In the following sessions, each presented by a different participant, we will look more closely at recent advances in different technologies that form parts of the traditional pipeline, as well as more recent alternatives to the pipeline, including NLG using neural networks. https://courses.helsinki.fi/en/582767/117339112
  • The Ultimate Guide to Natural Language Generation (Automated Insights)
    Natural language generation (NLG) is a software process that automatically transforms data into written narrative.
    https://medium.com/@AutomatedInsights/the-ultimate-guide-to-natural-language-generation-bdcb457423d6
  • Natural Language Generation course at the The University of Edinburgh
    This course provides an introduction to the theory and practice of computational approaches to natural language generation. The course covers common approaches to content selection and organization, sentence planning, and realisation. It includes both symbolic approaches to generation, as well as more recent statistical and trainable techniques. It also aims to provide an understanding of evaluation methods used in this field, an understanding of key aspects of human language production, exposure to techniques and tools used to develop practical systems that can communicate with users, and insight into open research problems in applications of natural language generation, e.g., summarization, paraphrase, dialogue, multimodal discourse.
    https://www.inf.ed.ac.uk/teaching/courses/nlg/
  • Building Applied Natural Language Generation Systems
    In this article, we give an overview of Natural Language Generation (nlg) from an applied system-building perspective. The article includes a discussion of when nlg techniques should be used; suggestions for carrying out requirements analyses; and a description of the basic nlg tasks of content determination, discourse planning, sentence aggregation, lexicalization, referring expression generation, and linguistic realisation. Throughout, the emphasis is on established techniques that can be used to build simple but practical working systems now. We also provide pointers to techniques in the literature that are appropriate for more complicated scenarios.
    https://pdfs.semanticscholar.org/728e/18fbf00f5a80e9a070db4f4416d66c7b28f4.pdf
  • When Reporters Get Hands-on with Robo-Writing: Professionals consider automated journalism’s capabilities and consequences: Digital Journalism: Vol 5, No 10
    https://www.tandfonline.com/doi/full/10.1080/21670811.2017.1289819?src=recsys
  • [1703.09902] Survey of the State of the Art in Natural Language Generation: Core tasks, applications and evaluation
    This paper surveys the current state of the art in Natural Language Generation (NLG), defined as the task of generating text or speech from non-linguistic input.
    https://arxiv.org/abs/1703.09902
  • Studio for Students | Arria NLG
    Studio for Students If you are a student, university official, professor, or a university researcher, you qualify to participate in Arria’s NLG Studio for Students Program. Through this new program, you will get full no-cost access to our bleeding-edge Arria NLG Studio in addition to curated trainings, special licenses, and other perks.
    https://www.arria.com/space/studio-for-students/
  • php-nlgen/README at master · DrDub/php-nlgen · GitHub
    These are pure PHP helper classes to implement recursive-descent
    natural language generators [1]. The classes provided are an abstract
    generator, an ontology container and a lexicon container. https://github.com/DrDub/php-nlgen

Human on Tech

Thoughts and ramblings on the Web and its humans

Markos Giannopoulos

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Probing the mysterious space between human thoughts and what a machine can understand :)

Human on Tech

Thoughts and ramblings on the Web and its humans

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