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Showing 1 to 6 of 6 for “"Lemmatization"”.

  1. Examination and utilization of rare features in text classification of injury narratives

    … or grouping methods such as stemming and lemmatization are often used in the text preprocessing stage. Despite their popularity, these classic grouping methods are not without limitations. The proposed "Type M+S Word Grouping Method" groups rare and unseen words morphologically and …

    purdue-thes Repository record for Examination and utilization of rare features in text classification of injury narratives (opens in a new tab)

  2. Towards a machine-learning architecture for lexical functional grammar parsing

    … algorithms to learn morphological features, lemmatization classes and grammatical functions from treebanks we can reduce the amount of manual specification and improve robustness, accuracy and domain- and language -independence for LFG parsing systems. Function labels can often be relatively …

    dcu Repository record for Towards a machine-learning architecture for lexical functional grammar parsing (opens in a new tab)

  3. Dynamic Model Generation and Semantic Search for Open Source Projects using Big Data Analytics

    … language processing (NLP) [15] techniques like lemmatization. In the second step, the transformed data is semantically analyzed for feature extraction using Term Frequency Inverse Document Frequency (TF-IDF), synonym detection using Word2Vec [3] and component detection using Machine Learning …

    umkc Repository record for Dynamic Model Generation and Semantic Search for Open Source Projects using Big Data Analytics (opens in a new tab)

  4. KB4DL: Building a Knowledge Base for Deep Learning

    … Natural Language Processing techniques such as Lemmatization, POS tagging, Named Entity Recognition to process the filtered data from research articles/papers and obtain Triplet <Subject, Predicate, Object> format. These triplets are used to validate the extracted meta data and use to fill in …

    umkc Repository record for KB4DL: Building a Knowledge Base for Deep Learning (opens in a new tab)

  5. Candidates, the economy and voting behavior

    … processing techniques including tokenization, lemmatization, and doc-term matrix, to open-ended responses to construct a matrix of relevant (repeated) terms, and train a machine learning classifier that classifies vote choice from those data. I show that the more voters dislike the opposing …

    uiuc Repository record for Candidates, the economy and voting behavior (opens in a new tab)

  6. Curtus: An NLP Tool to Map Job Skills to Academic Courses

    <p>Many businesses are burdened with the need to train students for the job instead of finding them prepared for it. Few business leaders feel that colleges prepare students for future jobs from day one. It can be a challenge for colleges to determine if their curricula meet the industry needs. …

    columbus-state Repository record for Curtus: An NLP Tool to Map Job Skills to Academic Courses (opens in a new tab)