Research

Bio:

Abebe Rorissa is an Associate Professor at the Department of Information Studies, College of Computing and Information, University at Albany. Prior to joining the University at Albany in September 2005, Dr. Rorissa worked in Ethiopia, Lesotho, Namibia, and the US as a lecturer/instructor and professional librarian (systems/automation). Since September 1988, he has taught courses in library and information sciences, mathematics, research methods, and statistics. Dr. Rorissa has published in major LIS journals, served as proceedings editor, program committee member, and reviewer for several journals and national and international conferences as well as an advisory board member of publications by professional organizations.

 

Research Interests:

His research interests include multimedia information organization and retrieval, measurement and scaling of users' information needs and their perceptions of multimedia information sources and services, and use/acceptance/adoption and impact of information and communication technologies (ICTs).

 

Research Projects:

2007 - 2008

A comparative study of flickr tags and index terms in general image collections
A study to determine if there is a difference between flickr tags and index terms in general image collections. Funded by the University at Albany; FRAP B.

2006

Use and impact of the internet across the digital divide: A two country longitudinal study within the framework of the Unified Theory of Acceptance and Use of Technology (UTAUT)
A study was proposed to design an instrument and test the Unified Theory of Acceptance and Use of Technology (UTAUT) using two samples from opposite ends of the digital divide. Proposal submitted for funding [funds not received].

2003 - 2004

Human Similarity Judgments versus Entropy-based Similarity Measures of Images: An Exploratory Study
A study conducted to see if entropy-based features of images and similarity measures based on the geometric models of similarity match human similarity judgments of pairs of images. Funded by the Texas Center for Digital Knowledge (TxCDK), University of North Texas.