The WebGenre Blog: The power of genre applied to digital information. By Marina Santini » Entries tagged with "nlp"

Book Review: Fundamentals of Predictive Text Mining 2nd Ed. (2015)

Book Review: Fundamentals of Predictive Text Mining 2nd Ed. (2015)

Book Review: Weiss S. M., Indurkhya N. and Zhang T. (2015). Fundamentals of Predictive Text Mining. Springer-Verlag, London. Second Edition Informer website Winter 2016 Issue, Book Review The volume “Fundamentals of Predictive Text Mining”, 2nd ed. has nine chapters, a table of contents, a list of references, a Subject Index and an Author Index. The book also includes a Preface written by the three authors, Summary Abbriavions: ML=Machine Learning; NLP=Natural Language Processing; IR= Information Retrieval 1) In Chapter 1, “Overview of … Read entire article »

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Lecture: Word Senses

Lecture: Word Senses

Outline: word senses, lexical semantics, homonymy, polysemy, metonymy, meronymy, antonomy, synonmy, hyponymy, hypernymy, wordnet, mesh, babelnet, lemma, wordform, zeugma test, senseval, selectional restrictions, membership meronymy, part-whole meronymy, semantic analysis, language technology Lecture: Word Senses from Marina Santini … Read entire article »

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Lecture 3: Structuring the Unstructured via Sentiment Analysis

Lecture 3: Structuring Unstructured Texts Through Sentiment Analysis from Marina Santini … Read entire article »

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Opinion Retrieval and Ranking: the creeping and ineluctable force of Genre

Last Updated: 27 May 2013 Two fundamental principles concurring to the definition and characterization of the concept of genre are conventions and expectations. Simply put, in textual (written or spoken) communication, genres are words that connote different types of text. For instance, on the web the home page genre is different from the blog genre; in a company, the minutes genre is different from the white paper genre; in the press the leader genre is different from the letter to the editor genre… Genres have the power of shaping information following rhetorical and discourse patterns that have become conventionalized. Genre conventions are implemented by the writer(s). When acknowledged, genre conventions raise predictable expectations in the readers or more generally in those who “process” a text… Although I am oversimplifying here, broadly speaking … Read entire article »

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Presentation: Text analytics and R – Open Question: is it a good match?

* The Quest: finding the optimal way to handle Big Textual Data for Information Discovery & Actionable Intelligence * The Open Question: is R convenient for text analytics of Big TEXTUAL Data? * The Mission: identification of pros, cons, limits, benefits Current Status: investigation in progress… Live casts of the this R meetup are available here: First talk: Text analytics and R by Marina Santini Second and third talks: Wordclouds from Twitter with R by Måns Magnusson and An example of text analytics in R by Joakim Lundborg http://www.meetup.com/StockholmR/pages/Live_casts_from_past_meetups/ You can find R code suggestions in this thread:  http://www.meetup.com/StockholmR/events/103353372/?&a=uc1_te … Read entire article »

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