A Basic Study of User Utility Maximizing Content Retrieval from Information Networks

Abstract

SummaryThis paper proposes some basic methods of content search yielding high user utility or user's satisfaction from numerous information sources scattered over large‐scale networks. In these methods, the search policy is decided by the estimated user utility gain and/or current user utility for each search action, and the most favorable combination of information sources and search content items is selected so as to enlarge the total user utility of the entire search activity. In addition, we evaluate the efficiency of the methods by computer simulations, in which we specify the network topology, user utility functions, probabilities of existence of the search content items in each information source, and so on, apply the proposed methods and other methods for comparison, and compare their aggregate utility gains as an estimation index. The proposed methods are found to achieve good performance in general and an index value about 2.45 times that of ordinary search is observed in an extreme simulation scenario. We discuss the pros and cons of the proposed methods for all the simulation scenarios.