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Showing 1 to 8 of 8 for “"word patterns"”.

  1. Why, New York City? Gauging the Quality of Life Through the Thoughts of Tweeters

    … Twitter data around specific keyword terms to determine dominant topics, word patterns, and sentiment leanings in a geographical area. Focusing on New York City and Los Angeles for comparative analysis, the keyword term “why” will be used to build a Python analysis around topic …

    cuny-grad Repository record for Why, New York City? Gauging the Quality of Life Through the Thoughts of Tweeters (opens in a new tab)

  2. Topic models for short text data

    … available for a reliable inference (i.e.: the words in a document). A popular heuristic utilized to overcome this problem is to perform before training some form of document aggregation by context (e.g.: author, hashtag). We dedicated one part of this dissertation to modeling explicitly the …

    essex Repository record for Topic models for short text data (opens in a new tab)

  3. The production and perception of Libyan Arabic stress patterns by English speaking learners: A comparison with native speakers

    … and perception of some selected stress patterns in Libyan Arabic by English speaking learners and compares them to the production and perception of the native speakers. Two tasks were utilised to investigate the participants’ performance: a picture naming and an identification task. Word

    essex Repository record for The production and perception of Libyan Arabic stress patterns by English speaking learners: A comparison with native speakers (opens in a new tab)

  4. N-gram models of agreement in language

    … be traced to a relatively small number of common word sequences usually comprised of grammatical terms, and a large number of infrequent word patterns comprised of thematic terms with high mutual information. The drawback for conventional approaches is an exceedingly large number of other n-grams …

    waikato-masters Repository record for N-gram models of agreement in language (opens in a new tab)

  5. Triplet entropy loss: improving the generalisation of short speech language identification systems

    … it appears as though the models still memorise word patterns present in the spectrograms rather than learning the finer nuances of a language. The research shows that Triplet Entropy Loss has great potential and should be investigated further, but not only in language identification tasks but …

    cape-town Repository record for Triplet entropy loss: improving the generalisation of short speech language identification systems (opens in a new tab)

  6. Natural Language Processing methods for short informal text

    … model was inspired by the relation between the word's frequency and the context words frequencies (words surrounding the selected word) over time. This relation had been translated to co-occurrence patterns and stored as word embeddings after being transformed into feature space. The features …

    essex Repository record for Natural Language Processing methods for short informal text (opens in a new tab)

  7. A Comparative Content Analysis of Five Spelling Programs in the 1st, 3rd, and 5th Grade

    … Mifflin, Scholastic Spelling, Sitton Spelling, Words Their Way, and Treasures were analyzed. The following questions guided the study: To what extent do current spelling series reflect research-based practices and what underlying theoretical framework is stated or implied in each series? What …

    usd-thes Repository record for A Comparative Content Analysis of Five Spelling Programs in the 1st, 3rd, and 5th Grade (opens in a new tab)

  8. Domain-agnostic named entity recognition on unstructured text

    … compliment character embeddings to learn better word representations even with less training data. Experimental results demonstrate the effectiveness of our proposed domain-agnostic techniques on multiple datasets. We set the new state-of-the-art for BioNLP13CG and give a competitive performance …

    uiuc Repository record for Domain-agnostic named entity recognition on unstructured text (opens in a new tab)