Global-local word embedding for text classification

Only humans can understand and comprehend the actual meaning that underlies natural written language, whereas machines can form semantic relationships only after humans have provided the parameters that are necessary to model the meaning. To enable computer models to access the underlying meaning in written language, accurate and sufficient document representation is crucial. Recent word embedding approaches have drawn much attention to text mining research. One of the main benefits of such approaches is the use of global corpuses with the generation of pre-trained word vectors. Although very effective, these approaches have their disadvantages, namely sole reliance on pre-trained word vectors that may neglect the local context and increase word ambiguity. In this thesis, four new document representation approaches are introduced to mitigate the risk of word ambiguity and inject a local context into globally pre-trained word vectors. The proposed approaches, which are frameworks for document representation while using word embedding learning features for the task of text classification, are: Content Tree Word Embedding; Composed Maximum Spanning Content Tree; Embedding-based Word Clustering; and Autoencoder-based Word Embedding. The results show improvement in the F_score accuracy measure for a document classification task applied to IMDB Movie Reviews, Hate Speech Identification, 20 Newsgroups, Reuters-21578, and AG News as benchmark datasets in comparison to using three deep learning-based word embedding approaches, namely GloVe, Word2Vec, and fastText, as well as two other document representations: LSA and Random word embedding

A scientometric study of media literacy literature based on Scopus record through 2011

The present research is an attempt to describe the quantity and quality of publication trends of media literacy based on Scopus reports. The population under study was composed of 510 documents on media literacy published through 2011. The results were analyzed based on date of publication, type of document, language of the documents, source of publications, subject areas, authors and their affiliations, and the countries involved in developing the articles. Citation indicators formed the second phase of investigation in the present study. With a negligible amount of fluctuation, the number of publications on media literacy has increased steadily over the years, with the greatest number occurring in 2011.  The analysis of data based on document types indicated that, of the 510 documents, 330 were articles (64.70%), 85 were reviews (16.66%), and 64 were conference papers (12.54%). 446 documents (84.45%) were published in English and the rest presented in other languages. The United States with 190 documents (37.25%), the United Kingdom with 43 documents (8.43%), and Australia with 14 documents (2.74%) were the most represented countries, with the most prolific authors known as Austin, Hobbs, and Cheung. Thematically, the greatest number of documents were produced in Social Sciences with 360 documents (70.57%), followed by Medicine with 92 documents (18.03%). The largest number of documents has been published in Comunicar followed by American Behavioral Scientist, and Simile.  The most cited articles from 1996 up to 2011 included 22 documents on the H-index zone. Analysis of the results of H-index zone by subject categories indicated that most documents on h-index zone belonged to social sciences and Medicine areas. Psychology had the most influence on media literacy, as was shown by the ratio of most cited documents to total number of documents on media literacy in any of the subject categories. The results highlight the multidisciplinary nature of media literacy. As for the H-index zone, 16 documents (73.91%) belonged to the United States. Overall, the United States, with 190 (37.25%) publications (out of a total of 510), had an important role in enhancing the quantity and quality of the media literacy literatur

Opportunities in game-based stroke rehabilitation

Stroke is the most common cause of long-Term disability of adults in developed countries. Continuous participation in rehabilitation can alleviate some of tis consequences, and support recover of stroke patients. However, physical rehabilitation requires commitment to tedious exercises routines overlengthy periods of time, which often causes patients to drop out of therapy routines. In this context, game-based stroke rehabilitation has the potential to address two important barriers: accessibility of rehabilitation, and patient motovation. This paper provides a summary of design efforts in human-computer interaction (HCI) and games research to support stroke rehabilitation. Based on our review, we discuss challenges and opportunities in game-based stroke rehabilitation and outline areas for future work that need to be addressed to offer engaging game-based stroke rehabilitation. © 2014 IEEE

Comparison of Open Source Learning Management Softwares and Presenting a Native Evaluation Tool

Introduction: Nowadays all educational institutes are trying to use technology in their structure. This effort has been faced with different barriers, including cost, time, and support. Therefore, using open source softwares can partially help us in using technology. In this article, we review main features of several open source learning management softwares, while presenting a tool which includes all the necessary features of a Learning Management System(LMS). Methods: An evaluation tool with 118 operational features for LMS softwares was developed. Five famous open source softwares of learning management system were compared based on its variables. These sofwares were: Moodle, Olat, Dokeos, ILIAS, and Docebo. Results: Most of the open source LMS softwares have operational characteristics such as mass media, curriculum and student management, personalization, and financial management. However, they are different in details. Conclusion: There are quite a number of similarities and some differences between open source LMS softwares. Generally, choosing an open source LMS would be based on the demands of any educational organization. In this article, necessary characteristics of a suitable open source learning management computer program are presente

Opportunities in game-based stroke rehabilitation

Stroke is the most common cause of long-Term disability of adults in developed countries. Continuous participation in rehabilitation can alleviate some of tis consequences, and support recover of stroke patients. However, physical rehabilitation requires commitment to tedious exercises routines overlengthy periods of time, which often causes patients to drop out of therapy routines. In this context, game-based stroke rehabilitation has the potential to address two important barriers: accessibility of rehabilitation, and patient motovation. This paper provides a summary of design efforts in human-computer interaction (HCI) and games research to support stroke rehabilitation. Based on our review, we discuss challenges and opportunities in game-based stroke rehabilitation and outline areas for future work that need to be addressed to offer engaging game-based stroke rehabilitation. © 2014 IEEE.</p