End user

About: End user is a research topic. Over the lifetime, 12262 publications have been published within this topic receiving 197007 citations. The topic is also known as: end user & final buyer.

The measurement of end-user computing satisfaction

Abstract: This article contrasts traditional versus end-user computing environments and report on the development of an instrument which merges ease of use and information product items to measure the satisfaction of users who directly interact with the computer for a specific application. Using a survey of 618 end users, the researchers conducted a factor analysis and modified the instrument. The results suggest a 12-item instrument that measures five components of end-user satisfaction - content, accuracy, format, ease of use, and timeliness. Evidence of the instrument's discriminant validity is presented. Reliability and validity is assessed by nature and type of application. Finally, standards for evaluating end-user applications are presented, and the instrument's usefulness for achieving more precision in research questions is explored.

A survey on context-aware systems

Abstract: Context-aware systems offer entirely new opportunities for application developers and for end users by gathering context data and adapting systems behaviour accordingly. Especially in combination with mobile devices, these mechanisms are of high value and are used to increase usability tremendously. In this paper, we present common architecture principles of context-aware systems and derive a layered conceptual design framework to explain the different elements common to most context-aware architectures. Based on these design principles, we introduce various existing context-aware systems focusing on context-aware middleware and frameworks, which ease the development of context-aware applications. We discuss various approaches and analyse important aspects in context-aware computing on the basis of the presented systems.

Method and apparatus for providing electronic advertisements to end users in a consumer best-fit pricing manner

Abstract: A method and apparatus for providing electronic advertisements to end users in a consumer best-fit pricing manner includes an index database, a user profile database, and a consumer scale matching process. The index database provides storage space for the titles of electronic advertisements. The user profile database provides storage for a set of characteristics which correspond to individual end users of the apparatus. The consumer scale matching process is coupled to the content database and the user profile database and compares the characteristics of the individual end users with a consumer scale associated with the electronic advertisement. The apparatus then charges a fee to the advertiser, based on the comparison by the matching process. In one embodiment, a consumer scale is generated for each of multiple electronic advertisements. These advertisements are then transferred to multiple yellow page servers, and the titles associated with the advertisements are subsequently transferred to multiple metering servers. At the metering servers, a determination is made as to where the characteristics of the end users served by each of the metering servers fall on the consumer scale. The higher the characteristics of the end users served by a particular metering server fall, the higher the fee charged to the advertiser.

Method and apparatus for determining behavioral profile of a computer user

Abstract: Computer network method and apparatus provides targeting of appropriate audience based on psychographic or behavioral profiles of end users. The psychographic profile is formed by recording computer activity and viewing habits of the end user. Content of categories of interest and display format in each category are revealed by the psychographic profile, based on user viewing of agate information. Using the profile (with or without additional user demographics), advertisements are displayed to appropriately selected users. Based on regression analysis of recorded responses of a first set of users viewing the advertisements, the target user profile is refined. Viewing by and regression analysis of recorded responses of subsequent sets of users continually auto-targets and customizes ads for the optimal end user audience.