Evaluating new requirements to pen-centric intelligent user interface based on end-to-end mathematical expressions recognition

Zhelezniakov, Dmytro; Cherneha, Anastasiia; Zaytsev, Viktor; Ignatova, Tetiana; Radyvonenko, Olga; Yakovchuk, Oleg

doi:10.1145/3377325.3377482

Cited by 9 publications

(2 citation statements)

References 23 publications

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“…Similarly, Anthony et al [22] implemented a handwriting-based input interface for intelligent tutoring systems. Zhelezniakov et al [23] proposed SMath as a handwritten mathematical expression system for interactive input and automatic calculations. The major challenge in handwritingbased methods is the recognition rate.…”

Section: Handwriting-based Input Methodsmentioning

confidence: 99%

MathTOUCH Editor: Rich-text Editor for Math E-learning Using an Intelligent Math Input Interface

Shirai,

Nakahara,

Fukui

2023

Journal of Information Processing

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In this study, we presented MathTOUCH, a rich-text editor, to create mathematical documents. In mathematics e-learning with learning management systems, existing math input methods have heavy workloads; therefore, math notations are a long-standing challenge. Furthermore, when creating mathematical documents, such as writing reports and posting questions on the forum, users must enter both texts in a natural language input manner and mathematical expressions in a math input manner. Hence, users' workload increases. To address this issue, we developed the MathTOUCH editor to implement an intelligent math input interface that enables users to enter equations through predictive conversion from the colloquial-style text. A user study was conducted with 71 participants to evaluate the effectiveness of the proposed editor. The results indicate that users could enter equations with the MathTOUCH editor approximately 1.5 times faster than with a standard interface, and the participants also reported greater subjective satisfaction.

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Section: Handwriting-based Input Methodsmentioning

confidence: 99%

MathTOUCH Editor: Rich-text Editor for Math E-learning Using an Intelligent Math Input Interface

Shirai,

Nakahara,

Fukui

2023

Journal of Information Processing

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“…CQAVis [145] is an application to filter high-quality comments from online community question answering forums. Zhelezniakov et al [146] investigated the requirements for pen-centered mathematical expression recognition applications. SaIL [147] is an assistive web navigation tool that injects important ARIA landmarks automatically.…”

Section: Applicationsmentioning

confidence: 99%

A Review of Recent Deep Learning Approaches in Human-Centered Machine Learning

Kaluarachchi

Reis

Nanayakkara

2021

Sensors

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After Deep Learning (DL) regained popularity recently, the Artificial Intelligence (AI) or Machine Learning (ML) field is undergoing rapid growth concerning research and real-world application development. Deep Learning has generated complexities in algorithms, and researchers and users have raised concerns regarding the usability and adoptability of Deep Learning systems. These concerns, coupled with the increasing human-AI interactions, have created the emerging field that is Human-Centered Machine Learning (HCML). We present this review paper as an overview and analysis of existing work in HCML related to DL. Firstly, we collaborated with field domain experts to develop a working definition for HCML. Secondly, through a systematic literature review, we analyze and classify 162 publications that fall within HCML. Our classification is based on aspects including contribution type, application area, and focused human categories. Finally, we analyze the topology of the HCML landscape by identifying research gaps, highlighting conflicting interpretations, addressing current challenges, and presenting future HCML research opportunities.

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