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Topic analysis consists of two main tasks: topic identification and text segmentation. While the first is a simple classification of a specific text, the latter case implies that a document may contain multiple topics, and the task of computerized text segmentation may be to discover these topics automatically and segment the text accordingly ...
Approaches for temporal information include Block and Newman's determination of the temporal dynamics of topics in the Pennsylvania Gazette during 1728–1800. Griffiths & Steyvers used topic modeling on abstracts from the journal PNAS to identify topics that rose or fell in popularity from 1991 to 2001 whereas Lamba & Madhusushan [6] used topic modeling on full-text research articles ...
Syntactic Structures is an important work in linguistics by American linguist Noam Chomsky, originally published in 1957.A short monograph of about a hundred pages, it is recognized as one of the most significant and influential linguistic studies of the 20th century.
To exploit a parallel text, some kind of text alignment identifying equivalent text segments (phrases or sentences) is a prerequisite for analysis. Machine translation algorithms for translating between two languages are often trained using parallel fragments comprising a first-language corpus and a second-language corpus, which is an element ...
In the 1980s, Annemarie Sullivan Palincsar and Ann L. Brown developed a technique called reciprocal teaching that taught students to predict, summarize, clarify, and ask questions for sections of a text. The use of strategies like summarizing after each paragraph has come to be seen as effective for building students' comprehension.
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.
Stanley is recalling 2.6 million mugs sold in the U.S. after the company received dozens of consumer complaints, including some users who reported getting burned and requiring medical attention ...
The missing letter effect unfolds as it is more difficult to detect target letters within function words as they are “pushed into the background” following structural analysis than it is to detect letters in content words which “stand in the foreground” and uncover the meaning of the text.