Viral or buzz marketing takes advantage of communication linkages topropagate positive influence regarding a product or service.TelE-commerce is an ideal domain within which to study viral marketing,because communication linkages can be observed. In this paper, we followa new telE-commerce...

Researchers and practitioners increasingly are gaining access to data onexplicit social networks. For example, telecommunications and technologyfirms record data on consumer networks (via phone calls, emails,voice-over-IP, instant messaging), and social-network portal sites suchas MySpace,...

Prior studies have questioned the degree of anonymity of thedouble-blind review process for scholarly research articles. Forexample, one study based on a survey of reviewers concluded that authorsoften could be identified by reviewers using a combination of theauthor's reference list and the...

Prediction in financial domains is notoriously difficult for a number ofreasons. First, theories tend to be weak or non-existent, which makesproblem formulation open ended by forcing us to consider a large numberof independent variables and thereby increasing the dimensionality ofthe search...

Model induction from relational data requires aggregation of values ofattributes of related entities. This paper makes three contributions tothe study of relational learning.(1) It presents a hierarchy ofrelational concepts of increasing complexity, using relational schemacharacteristics such as...

Abstract. In many cost-sensitive environments class probabilityestimates are used by decision makers to evaluate the expected utilityfrom a set of alternatives. Supervised learning can be used to buildclass probability estimates; however, it often is very costly to obtaintraining data with class...

This paper is about constructing confidence bands around ROC curves. Wefirst introduce to the machine learning community three band-generatingmethods from the medical field, and evaluate how well they perform. Suchconfidence bands represent the region where the “true” ROCcurve is expected to...

In many classification tasks training data have missing feature valuesthat can be acquired at a cost. For building accurate predictive models,acquiring all missing values is often prohibitively expensive orunnecessary, while acquiring a random subset of feature values may notbe most effective....

It can be expensive to acquire the data required for businesses toemploy data-driven predictive modeling, for example to model consumerpreferences to optimize targeting. Prior research has introduced“active learning” policies for identifying data that areparticularly useful for model...