![]() ![]() In the research community the dominant approach to this problem is based on machine learning techniques: a general inductive process automatically builds a classifier by learning, from a set of preclassified documents, the characteristics of the categories. We found that enhanced GloVe outperformed GloVe with a relative improvement of 25% in the F-score.read more read lessĪbstract: The automated categorization (or classification) of texts into predefined categories has witnessed a booming interest in the last 10 years, due to the increased availability of documents in digital form and the ensuing need to organize them. ![]() Given a seed term selected from a concept in the ontology, we measured our algorithms' ability to automatically extract synonyms for those terms that appeared in the ground truth concept. We used the WordNet ontology to expand the healthcare corpus by including synonyms, hyponyms, and hypernyms for each layman term occurrence in the corpus. Our approach was evaluated used healthcare text downloaded from, a healthcare social media platform using two standard laymen vocabularies, OAC CHV, and MedlinePlus. Furthermore, the enhanced GloVe showed a statistical significance over the two ground truth datasets with P Conclusions This paper presents an automatic approach to enrich consumer health vocabularies using the GloVe word embeddings and an auxiliary lexical source, WordNet. Furthermore, our enhanced GloVe approach outperformed basic GloVe with an average F-score of 61%, a relative improvement of 25%. Results The results show that GloVe was able to find new laymen terms with an F-score of 48.44%. The basic GloVe and our novel algorithms incorporating WordNet were evaluated using two laymen datasets from the National Library of Medicine (NLM), Open-Access Consumer Health Vocabulary (OAC CHV) and MedlinePlus Healthcare Vocabulary. Our approach further improves the consumer health vocabularies by incorporating synonyms and hyponyms from the WordNet ontology. Methods Our entirely automatic approach uses machine learning, specifically Global Vectors for Word Embeddings (GloVe), on a corpus collected from a social media healthcare platform to extend and enhance consumer health vocabularies. ![]() In this paper, we present an automatic method to enrich laymen's vocabularies that has the benefit of being able to be applied to vocabularies in any domain. Objective Many of the presented vocabularies are built manually or semi-automatically requiring large investments of time and human effort and consequently the slow growth of these vocabularies. To bridge this gap, several professional vocabularies and ontologies have been created to map laymen medical terms to professional medical terms and vice versa. In healthcare, it is rare to find a layman knowledgeable in medical terminology which can lead to poor understanding of their condition and/or treatment. A layman may have difficulty communicating with a professional due to not understanding the specialized terms common to the domain. Now it’s time to test your focus and vocabulary with one of the top word games of 2021.Abstract: Background Clear language makes communication easier between any two parties. turn music, sounds, and notifications on/off earn extra coins by answering quiz questions, guessing extra words, playing 1 level each day Ask friends when you are stuck in a level and build your Wordify Wisdom to prove that you are the word search & word find master. Additionally, answer general knowledge quiz questions to earn extra coins and use them to get hints. Play one level daily to earn coins and tickets for free. Think you know it all and no one can beat your word connect skills? Join the word puzzle competitions with other players across the globe and see your placement daily, weekly, monthly. Note that you get one general hint at the top of the level and you can get more hints (1 hint = 1 letter of the word you need to guess) by using your coins. If you guess an extra word you get extra coins so show your skills. The word challenge in Wordify is simple: connect letters to make the needed words. Featuring 7000 levels in hundreds of word puzzle packs you are set to enjoy one of the most interesting connect words puzzle challenges of 2021. Test your vocabulary and general knowledge with Wordify Words & Puzzles, the all-new free word search puzzle game.
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