4 citations · 9 across the 6 of their papers we have counts for
6 papers · 1 filter
Explaining Scenarios for Information Personalization
Naren Ramakrishnan, Mary Beth Rosson, John M. Carroll
Personalization customizes information access. The PIPE ("Personalization is Partial Evaluation") modeling methodology represents interaction with an information space as a program…
The Expresso Microarray Experiment Management System: The Functional Genomics of Stress Responses in Loblolly Pine
Lenwood S. Heath, Naren Ramakrishnan, Ronald R. Sederoff +7
Conception, design, and implementation of cDNA microarray experiments present a variety of bioinformatics challenges for biologists and computational scientists. The multiple stage…
Mixed-Initiative Interaction = Mixed Computation
Naren Ramakrishnan, Robert Capra, Manuel A. Perez-Quinones
We show that partial evaluation can be usefully viewed as a programming model for realizing mixed-initiative functionality in interactive applications. Mixed-initiative interaction…
The Partial Evaluation Approach to Information Personalization
Naren Ramakrishnan, Saverio Perugini
Information personalization refers to the automatic adjustment of information content, structure, and presentation tailored to an individual user. By reducing information overload…
When being Weak is Brave: Privacy in Recommender Systems
Naren Ramakrishnan, Benjamin J. Keller, Batul J. Mirza +2
We explore the conflict between personalization and privacy that arises from the existence of weak ties. A weak tie is an unexpected connection that provides serendipitous recommen…
Evaluating Recommendation Algorithms by Graph Analysis
Batul J. Mirza, Benjamin J. Keller, Naren Ramakrishnan
We present a novel framework for evaluating recommendation algorithms in terms of the `jumps' that they make to connect people to artifacts. This approach emphasizes reachability v…