Multimodal Preference Aggregation for Multimedia Information Retrieval

Multimodal Preference Aggregation for Multimedia Information Retrieval

Representing and fusing multimedia information is a key issue to discover semantics in multimedia. In this paper we address more specifically the problem of multimedia content retrieval through the joint design of an original multimodal information representation and of a machine learning-based fusion algorithm. We first define a novel preference-based representation particularly adapted to the...

Multimedia Information Retrieval at the Center for Intelligent Information Retrieval

This material is based on work supported in part by the National Science Foundation, Library of Congress and Department of Commerce under cooperative agreement number EEC-9209623, in part by the United States Patent and Trademarks Office and the Defense Advanced Research Projects Agency/ITO under ARPA order number D468, issued by ESC/AXS contract number F19628-95-C-0235, in part by NSF IRI-9619...

Visual Information Retrieval through Interactive Multimedia Queries Former Title: Intelligent Multimodal Interfaces for Visual Information Retrieval PhD Second Year Report

Preference aggregation with incomplete information

We show that in an environment of incomplete information, if individual preferences are sufficiently rich, then monotonicity and the Pareto property applied only when there is common knowledge of Pareto dominance imply (i) there must exist a common prior over the smallest common knowledge event and (ii) aggregation must be ex-ante utilitarian with respect to that common prior. This work builds ...

Multimedia Information Retrieval

Information Retrieval (IR) is an active research area for many years. Initially, the field focused on the efficient and effective processing of user information needs expressed as a set of keywords. In fact, this model is still active today (e.g., web search engines). However, large volumes of information are available in non-textual form, such as images, audio files and videos. The research fi...