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Document Structuring
Document Structuring is a subtask of Natural language generation, which involves deciding the order and grouping (for example into paragraphs) of sentences in a generated text. It is closely related to the Content determination NLG task. Example Assume we have four sentences which we want to include in a generated text # It will rain on Saturday # It will be sunny on Sunday # Max temperature will be 10 °C on Saturday # Max temperature will be 15 °C on Sunday There are 24 (4!) orderings of these messages, including * (1234) It will rain on Saturday. It will be sunny on Sunday. Max temperature will be 10 °C on Saturday. Max temperature will be 15 °C on Sunday. * (2341) It will be sunny on Sunday. Max temperature will be 10 °C on Saturday. Max temperature will be 15 °C on Sunday. It will rain on Saturday. * (4321) Max temperature will be 15 °C on Sunday. Max temperature will be 10 °C on Saturday. It will be sunny on Sunday. It will rai ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Natural Language Generation
Natural language generation (NLG) is a software process that produces natural language output. A widely cited survey of NLG methods describes NLG as "the subfield of artificial intelligence and computational linguistics that is concerned with the construction of computer systems that can produce understandable texts in English or other human languages from some underlying non-linguistic representation of information". While it is widely agreed that the output of any NLG process is text, there is some disagreement about whether the inputs of an NLG system need to be non-linguistic. Common applications of NLG methods include the production of various reports, for example weather and patient reports; image captions; and chatbots like ChatGPT. Automated NLG can be compared to the process humans use when they turn ideas into writing or speech. Psycholinguists prefer the term language production for this process, which can also be described in mathematical terms, or modeled in a com ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Content Determination
Content determination is the subtask of natural language generation (NLG) that involves deciding on the information to be communicated in a generated text. It is closely related to the task of document structuring. Example Consider an NLG system which summarises information about sick babies. Suppose this system has four pieces of information it can communicate # The baby is being given morphine via an IV drop # The baby's heart rate shows bradycardia's (temporary drops) # The baby's temperature is normal # The baby is crying Which of these bits of information should be included in the generated texts? Issues There are three general issues which almost always impact the content determination task, and can be illustrated with the above example. Perhaps the most fundamental issue is the ''communicative goal'' of the text, i.e. its ''purpose'' and ''reader''. In the above example, for instance, a doctor who wants to make a decision about medical treatment would probably be most int ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Text Corpus
In linguistics and natural language processing, a corpus (: corpora) or text corpus is a dataset, consisting of natively digital and older, digitalized, language resources, either annotated or unannotated. Annotated, they have been used in corpus linguistics for statistical statistical hypothesis testing, hypothesis testing, checking occurrences or validating linguistic rules within a specific language territory. Overview A corpus may contain texts in a single language (''monolingual corpus'') or text data in multiple languages (''multilingual corpus''). In order to make the corpora more useful for doing linguistic research, they are often subjected to a process known as annotation. An example of annotating a corpus is part-of-speech tagging, or ''POS-tagging'', in which information about each word's part of speech (verb, noun, adjective, etc.) is added to the corpus in the form of ''tags''. Another example is indicating the Lemma (morphology), lemma (base) form of each word ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Automatic Summarisation
Automatic summarization is the process of shortening a set of data computationally, to create a subset (a summary) that represents the most important or relevant information within the original content. Artificial intelligence algorithms are commonly developed and employed to achieve this, specialized for different types of data. Text summarization is usually implemented by natural language processing methods, designed to locate the most informative sentences in a given document. On the other hand, visual content can be summarized using computer vision algorithms. Image summarization is the subject of ongoing research; existing approaches typically attempt to display the most representative images from a given image collection, or generate a video that only includes the most important content from the entire collection. Video summarization algorithms identify and extract from the original video content the most important frames (''key-frames''), and/or the most important video segm ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Narrative
A narrative, story, or tale is any account of a series of related events or experiences, whether non-fictional (memoir, biography, news report, documentary, travel literature, travelogue, etc.) or fictional (fairy tale, fable, legend, thriller (genre), thriller, novel, etc.). Narratives can be presented through a sequence of written or spoken words, through still or moving images, or through any combination of these. The word derives from the Latin verb ''narrare'' ("to tell"), which is derived from the adjective ''gnarus'' ("knowing or skilled"). Historically preceding the noun, the adjective "narrative" means "characterized by or relating to a story or storytelling". Narrative is expressed in all mediums of human creativity, art, and entertainment, including public speaking, speech, literature, theatre, dance, music and song, comics, journalism, animation, video (including film and television), video games, radio program, radio, game, structured and play (activity), unstructu ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Computational Linguistics
Computational linguistics is an interdisciplinary field concerned with the computational modelling of natural language, as well as the study of appropriate computational approaches to linguistic questions. In general, computational linguistics draws upon linguistics, computer science, artificial intelligence, mathematics, logic, philosophy, cognitive science, cognitive psychology, psycholinguistics, anthropology and neuroscience, among others. Computational linguistics is closely related to mathematical linguistics. Origins The field overlapped with artificial intelligence since the efforts in the United States in the 1950s to use computers to automatically translate texts from foreign languages, particularly Russian scientific journals, into English. Since rule-based approaches were able to make arithmetic (systematic) calculations much faster and more accurately than humans, it was expected that lexicon, morphology, syntax and semantics can be learned using explicit rules, a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Natural Language Processing
Natural language processing (NLP) is a subfield of computer science and especially artificial intelligence. It is primarily concerned with providing computers with the ability to process data encoded in natural language and is thus closely related to information retrieval, knowledge representation and computational linguistics, a subfield of linguistics. Major tasks in natural language processing are speech recognition, text classification, natural-language understanding, natural language understanding, and natural language generation. History Natural language processing has its roots in the 1950s. Already in 1950, Alan Turing published an article titled "Computing Machinery and Intelligence" which proposed what is now called the Turing test as a criterion of intelligence, though at the time that was not articulated as a problem separate from artificial intelligence. The proposed test includes a task that involves the automated interpretation and generation of natural language ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
