The present study identifies and assesses the bibliographic trend in Artificial Intelligence (AI) research for the years 2015-2020 using the science mapping method of bibliometric study. The required data has been collected from the Scopus database. To make the collected data analysis-ready, essential data transformation was performed manually and with the help of a tool viz. OpenRefine. For determining the trend and performing the mapping techniques, top five open access and commercial journals of AI have been chosen based on their citescore driven ranking. The work includes 6880 articles published in the specified period for analysis. The trend is based on Country-wise publications, year-wise publications, topical terms in AI, top-cited articles, prominent authors, major institutions, involvement of industries in AI and Indian appearance. The results show that compared to open access journals; commercial journals have a higher citescore and number of articles published over the years. Additionally, IEEE is the prominent publisher which publishes 84% of the top-cited publications. Further, China and the United States are the major contributors to literature in the AI domain. The study reveals that neural networks and deep learning are the major topics included in top AI research publications. Recently, not only public institutions but also private bodies are investing their resources in AI research. The study also investigates the relative position of Indian researchers in terms of AI research. Present work helps in understanding the initial development, current stand and future direction of AI.

The development in the number and scale of universities throughout the world, as well as the expansion of their research endeavors as a method of enhancing their reputations and attracting both students and sponsors, is driving demand in this lucrative academic publishing sector. Because publishing metrics have become the key indicator of academic achievement and the primary motivator for career development, they have become the primary gauge of academic performance and the primary incentive for career progress. The concept "publish or perish" has become norm many fields. As a result, the rate of scientific publishing has increased exponentially in recent decades, with output rates approaching 2.5 million per year by 2017. The proliferation of so-called "predatory" journals, which provide speedy publishing without peer review or considerable editorial control, is another result of this increase in demand for publication channels.To counter the current science climate, Open Science has emerged.

This is an open access article distributed under the terms of the Creative Commons Attribution Licese (http://creativecommons.org/licenses/by/4.0)

Hoy traemos a este espacio el último número, recién salido de la revista International Journal of Emerging Technologies in Learning (iJET) This interdisciplinary journal aims to focus on the exchange of relevant trends and research results as well as the presentation of practical experiences gained while developing and testing elements of technology enhanced learning. So it aims to bridge the gap between pure academic research journals and more practical publications. So it covers the full range from research, application development to experience reports and product descriptions. Readers don't have to pay any fee. Vol 14, No 02 (2019) Table of Contents Papers Multi-Dimensional Analysis to Predict Students' Grades in Higher Education Eslam Abou Gamie, Samir Abou El-Seoud, Mostafa Salama, Walid Hussein Implemented and Tested Conception Proposal of Adaptation Model for Adaptive Hypermedia Mehdi Tmimi, Mohamed Benslimane, Mohammed Berrada, Kamar Ouzzani Multidimensional Approach Based on Deep Learning to Improve the Prediction Performance of DNN Models Mohamed El Fouki, Noura Aknin, Kamal Eddine El Kadiri Visualization Teaching of Deformation Monitoring and Data Processing based on MATLAB 3D Course Teaching Based on Educational Game Development Theory – Case Study of Game Design Course The Development and Performance Evaluation of Digital Museums Toward Second Classroom of Primary and Secondary School – Taking Zhejiang Education Technology Digital Museum as An Example Ying Zheng, Yuhui Yang, Huifang Chai, Mo Chen, Jianping Zhang Students' Beliefs Regarding the Use of E-portfolio to Enhance Cognitive Skills in a Blended Learning Environment Prakob Koraneekij, Jintavee Khlaisang Learning Effect of Implicit Learning in Joining-in-type Robot-assisted Language Learning System AlBara Khalifa, Tsuneo Kato, Seiichi Yamamoto The Different Roles of Help-Seeking Personalities in Social Support Group Activity on E-Portfolio for Career Development Suthanit Wetcho, Jaitip Na-Songkhla Short Papers A Review of Digital Skills of Malaysian English Language Teachers Mohd Zulhilmi Che Had, Radzuwan Ab Rashid International Journal of Emerging Technologies in Learning.

We propose a method for efficiently finding all parallel passages in a large corpus, even if the passages are not quite identical due to rephrasing and orthographic variation. The key ideas are the representation of each word in the corpus by its two most infrequent letters, finding matched pairs of strings of four or five words that differ by at most one word and then identifying clusters of such matched pairs. Using this method, over 4600 parallel pairs of passages were identified in the Babylonian Talmud, a Hebrew-Aramaic corpus of over 1.8 million words, in just over 11 seconds. Empirical comparisons on sample data indicate that the coverage obtained by our method is essentially the same as that obtained using slow exhaustive methods. INTRODUCTION Ancient text corpora in classical languages such as Greek, Latin, Hebrew and Aramaic typically include numerous examples of text reuse, including repetitions of long passages of 20 words or more. Identifying such passages is important because it allows scholars to trace the development of ideas and concepts through time and across geographical ranges. Additionally, even within a given time period and geographical location, the identification of multiple parallel sources for any given idea provides a platform for scholarly inquiry.