A crucial bottleneck in medical artificial intelligence (AI) is high-quality labeled medical datasets. In this paper, we test a large variety of wisdom of the crowd algorithms to label medical images that were initially classified by individuals recruited through an app-based platform. Individuals classified skin lesions from the International…

Despite a tremendous increase in the use of video for conducting research in classrooms as well as preparing and evaluating teachers, there remain notable challenges to using classroom videos at scale, including time and financial costs. Recent advances in artificial intelligence could make the process of analyzing, scoring, and cataloguing videos…

Online assessment is one of the important factors in online learning today. An online summary assessment is an example of an open-ended question, offering the advantage of probing students' understanding of the learning materials. However, grading students' summary writings is challenging due to the time-consuming process of evaluating students'…

In this article, I introduce a collaborative annotation activity that supports students in critically examining AI-generated writing in relation to criteria including specificity and complexity. I engage students in collaboratively annotating the AI-generated essays, guiding students to identify instances in which the essays could be more…

Numerous approaches have been introduced to automate the process of text summarization, but only few can be easily adapted to multiple languages. This paper introduces a multilingual text processing pipeline integrated in the open-source "ReaderBench" framework, which can be retrofit to cover more than 50 languages. While considering the…

Collections are the tools that people use to make sense of an ever-increasing number of archived web pages. As collections themselves grow, we need tools to make sense of them. Tools that work on the general web, like search engines, are not a good fit for these collections because search engines do not currently represent multiple document…

Presented is an empirical confirmation of clustering behavior that has been proposed as a conjecture in the literature; namely, that document ordering is more significant in an algorithm using a full document space search, rather than a search of just unclustered documents, each time a density test is performed. (4 references) (Author)

A study was undertaken to classify mechanically a document collection using the free-language words in titles and abstracts of physics research papers. Using a clustering algorithm, results were obtained which closely duplicated clusters obtained by previous experiments with citations. A brief comparison is made with a traditional manual…

Discussion of information retrieval focuses on an Interaction Information Retrieval model in which documents are interconnected; queries and documents are treated in the same way; and retrieval is the result of the interconnection between query and documents. A theoretical mathematical formulation of this type of retrieval is given. (Contains 31…

Sketchcode is a metaprograming pseudo-language documentation technique intended to simplify the process of program writing and debugging for both high and low-level users. Helpful hints and examples for the use of the technique are included. (CMV)

Describes the development of a structural model of document retrieval based on lexical-semantic relationships between index terms. An algorithm that uses tree-to-tree distance to measure structural closeness between a document and a query statement is explained, and the proposed model is compared to a vector retrieval model. (18 references) (LRW)

Discussion of the failure of individual keywords to identify conceptual content of documents in retrieval systems highlights Metric Similarity Modeling, a method for creating vector space representation of documents based on modeling target interdocument similarity values. Semantic relatedness, latent semantic indexing, an indexing and retrieval…

This issue contains nine articles that provide an overview of trends and research in parallel information retrieval. Topics discussed include network design for text searching; the Connection Machine System; PThomas, an adaptive information retrieval system on the Connection Machine; algorithms for document clustering; and system architecture for…

Reviews aspects of the relationship between machine learning and information retrieval. Highlights include learning programs that extend from knowledge-sparse learning to knowledge-rich learning; the role of the thesaurus; knowledge bases; artificial intelligence; weighting documents; work frequency; and merging classification structures. (78…