Evidence map›Paper›PMID 34337621›Full record

ArticleUMAP ... proceedings of the ... Conference on User Modeling, Adaptation and Personalization. UMAP (Conference)2019

Auto-Suggesting Browsing Actions for Personalized Web Screen Reading.

Vikas Ashok, Syed Masum Billah, Yevgen Borodin, I V Ramakrishnan

Abstract read
In one paragraph

Article in UMAP ... proceedings of the ... Conference on User Modeling, Adaptation and Personalization. UMAP (Conference), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Inaccessible and Deceptive: Examining Experiences of Deceptive Design with People Who Use Visual Accessibility Technology.Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference · 2025
    Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Vikas AshokStony Brook University.
Syed Masum BillahStony Brook University.
Yevgen BorodinCharmtech Labs LLC.
I V RamakrishnanStony Brook University.

Funding

Capti Screen Reading Assistant for Goal Directed Web BrowsingR44EY021962 · NEI · CHARMTECH LABS, LLC · PI BORODIN, YEVGEN · 2016 to 2017
$1.0M
Semantics-Preserving Virtualization: A Computing System Framework to Run Any Screen Reader on Any Device with Easy CustomizationR01EY026621 · NEI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI PORTER, DONALD ELLIOTT · 2016 to 2018
$952k
NEI NIH HHS R01 EY026621NEI NIH HHS R44 EY021962
6 · The paper itself

Abstract

Web browsing has never been easy for blind people, primarily due to the serial press-and-listen interaction mode of screen readers - their "go-to" assistive technology. Even simple navigational browsing actions on a page require a multitude of shortcuts. Auto-suggesting the next browsing action has the potential to assist blind users in swiftly completing various tasks with minimal effort. Extant auto-suggest feature in web pages is limited to filling form fields; in this paper, we generalize it to any web screen-reading browsing action, e.g., navigation, selection, etc. Towards that, we introduce

Indexed as

Auto SuggestBlindDial-based InteractionHuman-centered computing → Accessibility technologiesInformation systems → PersonalizationPersonalized Web AutomationVision ImpairmentWeb AccessibilityWeb interfaces

Identifiers

PMID34337621
PMCPMC8319855

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.