arXiv subjects

Richard Furuta

Publications and source records attributed to Richard Furuta.

5 recordsLinked to original sources

arXiv2023

An Interactive Web-Based System for Creating Single Panel Cartoons with Visually Valid Compositions

The creation of cartoon-based stories (comics) requires a lot of creativity and hard work for naive users. We observe that single-panel cartoons are the building blocks of any comic story. To develop a strong comic story, it is critical to obtain visually valid single panels. In this work, we have developed a methodology to guarantee the placement of characters to obtain a valid cartoon frame based on the methods used by professional cartoonists. Using this methodology, we have developed a web-based system to create single-panel cartoons from a given set of character images. We have made this system available in GitHub as open-source so that this basic single-panel cartoon can be used as infrastructure to develop more complex structures. Our web-based system for single-panel cartoons can be viewed at http://storytelling.viz.tamu.edu.

cs.HC↗

arXiv2018

Anatomy of Scholarly Information Behavior Patterns in the Wake of Academic Social Media Platforms

As more scholarly content is born digital or converted to a digital format, digital libraries are becoming increasingly vital to researchers seeking to leverage scholarly big data for scientific discovery. Although scholarly products are available in abundance-especially in environments created by the advent of social networking services-little is known about international scholarly information needs, information-seeking behavior, or information use. The purpose of this paper is to address these gaps via an in-depth analysis of the information needs and information-seeking behavior of researchers, both students and faculty, at two universities, one in the U.S. and the other in Qatar. Based on this analysis, the study identifies and describes new behavior patterns on the part of researchers as they engage in the information-seeking process. The analysis reveals that the use of academic social networks has notable effects on various scholarly activities. Further, this study identifies differences between students and faculty members in regard to their use of academic social networks, and it identifies differences between researchers according to discipline. Although the researchers who participated in the present study represent a range of disciplinary and cultural backgrounds, the study reports a number of similarities in terms of the researchers' scholarly activities.

cs.DL↗

arXiv2017

Recommendation of Scholarly Venues Based on Dynamic User Interests

The ever-growing number of venues publishing academic work makes it difficult for researchers to identify venues that publish data and research most in line with their scholarly interests. A solution is needed, therefore, whereby researchers can identify information dissemination pathways in order to both access and contribute to an existing body of knowledge. In this study, we present a system to recommend scholarly venues rated in terms of relevance to a given researcher's current scholarly pursuits and interests. We collected our data from an academic social network and modeled researchers' scholarly reading behavior in order to propose a new and adaptive implicit rating technique for venues. We present a way to recommend relevant, specialized scholarly venues using these implicit ratings that can provide quick results, even for new researchers without a publication history and for emerging scholarly venues that do not yet have an impact factor. We performed a large-scale experiment with real data to evaluate the current scholarly recommendation system and showed that our proposed system achieves better results than the baseline. The results provide important up-to-the-minute signals that compared with post-publication usage-based metrics represent a closer reflection of a researcher's interests.

cs.SI↗

arXiv2016

Font Identification in Historical Documents Using Active Learning

Identifying the type of font (e.g., Roman, Blackletter) used in historical documents can help optical character recognition (OCR) systems produce more accurate text transcriptions. Towards this end, we present an active-learning strategy that can significantly reduce the number of labeled samples needed to train a font classifier. Our approach extracts image-based features that exploit geometric differences between fonts at the word level, and combines them into a bag-of-word representation for each page in a document. We evaluate six sampling strategies based on uncertainty, dissimilarity and diversity criteria, and test them on a database containing over 3,000 historical documents with Blackletter, Roman and Mixed fonts. Our results show that a combination of uncertainty and diversity achieves the highest predictive accuracy (89% of test cases correctly classified) while requiring only a small fraction of the data (17%) to be labeled. We discuss the implications of this result for mass digitization projects of historical documents.

cs.CV↗

arXiv2011

Distributed Collections of Web Pages in the Wild

As the Distributed Collection Manager's work on building tools to support users maintaining collections of changing web-based resources has progressed, questions about the characteristics of people's collections of web pages have arisen. Simultaneously, work in the areas of social bookmarking, social news, and subscription-based technologies have been taking the existence, usage, and utility of this data for granted with neither investigation into what people are doing with their collections nor how they are trying to maintain them. In order to address these concerns, we performed an online user study of 125 individuals from a variety of online and offline communities, such as the reddit social news user community and the graduate student body in our department. From this study we were able to examine a user's needs for a system to manage their web-based distributed collections, how their current tools affect their ability to maintain their collections, and what the characteristics of their current practices and problems in maintaining their web-based collections were. We also present extensions and improvements being made to the system both in order to adapt DCM for usage in the Ensemble project and to meet the requirements found by our user study.

cs.DL↗