The extant literature on the use of social media marketing for recruiting higher education students has an unstructured nature. To address this gap, this paper introduces a novel method called 'algorithmic document sequencing' (ADS) that links the key findings of 43 relevant articles procured from all databases to one another on the use of social…

We aimed to evaluate the performance of supervised machine learning algorithms in predicting articles relevant for full-text review in a systematic review. Overall, 16,430 manually screened titles/abstracts, including 861 references identified relevant for full-text review were used for the analysis. Of these, 40% (n = 6573) were sub-divided for…

Aim/Purpose: The purpose of this study is to review and categorize current trends in student engagement and performance prediction using machine learning techniques during online learning in higher education. The goal is to gain a better understanding of student engagement prediction research that is important for current educational planning and…

Recommender systems have become one of the main tools for personalized content filtering in the educational domain. Those who support teaching and learning activities, particularly, have gained increasing attention in the past years. This growing interest has motivated the emergence of new approaches and models in the field, in spite of it, there…

Algorithm design is a vital skill developed in most undergraduate Computer Science (CS) programs, but few research studies focus on pedagogy related to algorithms coursework. To understand the work that has been done in the area, we present a systematic survey and literature review of CS Education studies. We search for research that is both…

The emergence of generative AI technologies has provoked considerable debate among educators regarding their role in education. This study is an investigation of the benefits, disadvantages, and potential strategies for integrating generative AI in educational settings by analyzing societal impacts based on a literature review. We have surveyed…

Monte Carlo validation studies of clustering algorithms, including Ward's minimum variance hierarchical method, are reviewed. Caution concerning the uncritical selection of Ward's method for recovering cluster structure is advised. Alternative explanations for differential recovery performance are explored and recommendations are made for future…

Discusses data mining (DM) and knowledge discovery in databases (KDD), taking the view that KDD is the larger view of the entire process, with DM emphasizing the cleaning, warehousing, mining, and visualization of knowledge discovery in databases. Highlights include algorithms; users; the Internet; text mining; and information extraction.…

Examines parallel computer architecture and the use of parallel processors for text. Topics discussed include parallel algorithms; performance evaluation; parallel information processing; parallel access methods for text; parallel and distributed information retrieval systems; parallel hardware for text; and network models for information…

Discusses properties of multiple attribute tree (MAT) and inverted file structures; establishes suitability of MAT data structure for bibliographic files using worst-case performance measures; provides arguments to establish MAT average case superiority; and proposes an efficient adaptation of MAT data structure to exploit special features of MAT…

The current state of multidimensional scaling using the city-block metric is reviewed, with attention to (1) substantive and theoretical issues; (2) recent algorithmic developments and their implications for analysis; (3) isometries with other metrics; (4) links to graph-theoretic models; and (5) prospects for future development. (SLD)

Describes a project that improved the quality of BCIN, the bibliographic database of the Conservation Information Network, by correcting data fields and removing duplicate records. The database is described, deduplication theory is discussed and relevant literature is reviewed, algorithm development and testing is described, and results of…

Reviews recent research into the use of hierarchic agglomerative clustering methods for document retrieval. The topics discussed include the calculation of interdocument similarities, algorithms used to implement clustering methods on large databases, validity testing of document hierarchies, appropriate search strategies, and other applications…

Discusses the feasibility of building intelligent rule- or weight-based algorithms into general-purpose software for interactive thesaurus navigation. Previous research is surveyed; practical investigations in thesaurus navigation and query enhancement are described; and implications for automatic or intelligent thesaurus navigation are…

Discusses various strategies for assessing importance of journals for acquisition; describes a discipline-specific selection algorithm which uses journal citation data to identify journals that contribute to a discipline's research foundation as well as those used for professional practice; and reports on two studies which demonstrated the…