Social and Behavioral Sciences Commons^™

A Heuristic Baseline Method For Metadata Extraction From Scanned Electronic Theses And Dissertations, Muntabir H. Choudhury, Jian Wu, William A. Ingam, Edward A. Fox

Computer Science Faculty Publications

Extracting metadata from scholarly papers is an important text mining problem. Widely used open-source tools such as GROBID are designed for born-digital scholarly papers but often fail for scanned documents, such as Electronic Theses and Dissertations (ETDs). Here we present a preliminary baseline work with a heuristic model to extract metadata from the cover pages of scanned ETDs. The process started with converting scanned pages into images and then text files by applying OCR tools. Then a series of carefully designed regular expressions for each field is applied, capturing patterns for seven metadata fields: titles, authors, years, degrees, academic programs, …

Repurposing Visual Input Modalities For Blind Users: A Case Study Of Word Processors, Hae-Na Lee, Vikas Ashok, I.V. Ramakrishnan

Computer Science Faculty Publications

Visual 'point-and-click' interaction artifacts such as mouse and touchpad are tangible input modalities, which are essential for sighted users to conveniently interact with computer applications. In contrast, blind users are unable to leverage these visual input modalities and are thus limited while interacting with computers using a sequentially narrating screen-reader assistive technology that is coupled to keyboards. As a consequence, blind users generally require significantly more time and effort to do even simple application tasks (e.g., applying a style to text in a word processor) using only keyboard, compared to their sighted peers who can effortlessly accomplish the same tasks …

Towards Making Videos Accessible For Low Vision Screen Magnifier Users, Ali Selman Aydin, Shirin Feiz, Vikas Ashok, Iv Ramakrishnan

Computer Science Faculty Publications

People with low vision who use screen magnifiers to interact with computing devices find it very challenging to interact with dynamically changing digital content such as videos, since they do not have the luxury of time to manually move, i.e., pan the magnifier lens to different regions of interest (ROIs) or zoom into these ROIs before the content changes across frames.

In this paper, we present SViM, a first of its kind screen-magnifier interface for such users that leverages advances in computer vision, particularly video saliency models, to identify salient ROIs in videos. SViM's interface allows users to zoom in/out …

Sail: Saliency-Driven Injection Of Aria Landmarks, Ali Selman Aydin, Shirin Feiz, Vikas Ashok, Iv Ramakrishnan

Computer Science Faculty Publications

Navigating webpages with screen readers is a challenge even with recent improvements in screen reader technologies and the increased adoption of web standards for accessibility, namely ARIA. ARIA landmarks, an important aspect of ARIA, lets screen reader users access different sections of the webpage quickly, by enabling them to skip over blocks of irrelevant or redundant content. However, these landmarks are sporadically and inconsistently used by web developers, and in many cases, even absent in numerous web pages. Therefore, we propose SaIL, a scalable approach that automatically detects the important sections of a web page, and then injects ARIA landmarks …

Smartcitecon: Implicit Citation Context Extraction From Academic Literature Using Unsupervised Learning, Chenrui Gao, Haoran Cui, Li Zhang, Jiamin Wang, Wei Lu, Jian Wu

Computer Science Faculty Publications

We introduce SmartCiteCon (SCC), a Java API for extracting both explicit and implicit citation context from academic literature in English. The tool is built on a Support Vector Machine (SVM) model trained on a set of 7,058 manually annotated citation context sentences, curated from 34,000 papers in the ACL Anthology. The model with 19 features achieves F₁=85.6%. SCC supports PDF, XML, and JSON files out-of-box, provided that they are conformed to certain schemas. The API supports single document processing and batch processing in parallel. It takes about 12–45 seconds on average depending on the format to process a …

Acknowledgement Entity Recognition In Cord-19 Papers, Jian Wu, Pei Wang, Xin Wei, Sarah Rajtmajer, C. Lee Giles, Christopher Griffin

Computer Science Faculty Publications

Acknowledgements are ubiquitous in scholarly papers. Existing acknowledgement entity recognition methods assume all named entities are acknowledged. Here, we examine the nuances between acknowledged and named entities by analyzing sentence structure. We develop an acknowledgement extraction system, AckExtract based on open-source text mining software and evaluate our method using manually labeled data. AckExtract uses the PDF of a scholarly paper as input and outputs acknowledgement entities. Results show an overall performance of F₁=0.92. We built a supplementary database by linking CORD-19 papers with acknowledgement entities extracted by AckExtract including persons and organizations and find that only up to …

Rotate-And-Press: A Non-Visual Alternative To Point-And-Click, Hae-Na Lee, Vikas Ashok, I. V. Ramakrishnan

Computer Science Faculty Publications

Most computer applications manifest visually rich and dense graphical user interfaces (GUIs) that are primarily tailored for an easy-and-efficient sighted interaction using a combination of two default input modalities, namely the keyboard and the mouse/touchpad. However, blind screen-reader users predominantly rely only on keyboard, and therefore struggle to interact with these applications, since it is both arduous and tedious to perform the visual 'point-and-click' tasks such as accessing the various application commands/features using just keyboard shortcuts supported by screen readers.

In this paper, we investigate the suitability of a 'rotate-and-press' input modality as an effective non-visual substitute for the visual …

Opening Books And The National Corpus Of Graduate Research, William A. Ingram, Edward A. Fox, Jian Wu

Computer Science Faculty Publications

Virginia Tech University Libraries, in collaboration with Virginia Tech Department of Computer Science and Old Dominion University Department of Computer Science, request $505,214 in grant funding for a 3-year project, the goal of which is to bring computational access to book-length documents, demonstrating that with Electronic Theses and Dissertations (ETDs). The project is motivated by the following library and community needs. (1) Despite huge volumes of book-length documents in digital libraries, there is a lack of models offering effective and efficient computational access to these long documents. (2) Nationwide open access services for ETDs generally function at the metadata level. …