34,521 research outputs found
Mobile Agent based Market Basket Analysis on Cloud
This paper describes the design and development of a location-based mobile
shopping application for bakery product shops. Whole application is deployed on
cloud. The three-tier architecture consists of, front-end, middle-ware and
back-end. The front-end level is a location-based mobile shopping application
for android mobile devices, for purchasing bakery products of nearby places.
Front-end level also displays association among the purchased products. The
middle-ware level provides a web service to generate JSON (JavaScript Object
Notation) output from the relational database. It exchanges information and
data between mobile application and servers in cloud. The back-end level
provides the Apache Tomcat Web server and MySQL database. The application also
uses the Google Cloud Messaging for generating and sending notification of
orders to shopkeeper.Comment: 6 pages, 7 figure
Trust and Privacy Permissions for an Ambient World
Ambient intelligence (AmI) and ubiquitous computing allow us to consider a future where computation is embedded into our daily social lives. This vision raises its own important questions and augments the need to understand how people will trust such systems and at the same time achieve and maintain privacy. As a result, we have recently conducted a wide reaching study of people’s attitudes to potential AmI scenarios with a view to eliciting their privacy concerns. This chapter describes recent research related to privacy and trust with regard to ambient technology. The method used in the study is described and findings discussed
SERVICE-PROCESS CONFIGURATIONS IN ELECTRONIC RETAILING: A TAXONOMIC ANALYSIS OF ELECTRONIC FOOD RETAILERS
Service-processes of electronic retailers are founded on electronic technologies that provide flexibility to sense and respond online to the dynamic and complex needs of customers. In this paper, we develop a taxonomy of service-processes in electronic retailing and demonstrate their linkage to customer satisfaction and customer loyalty. The taxonomy is grounded in a conceptual classification scheme that differentiates service-process stages on a continuum of flexibility. Using data on electronic service-processes collected from 255 electronic food retailers, we identified eight configurations for the taxonomy. We also collected and analyzed publicly reported customer satisfaction survey data that were available for 52 electronic food retailers in the study sample. The results of this analysis indicate positive and significant correlation of the ordering of the taxonomy configurations with (i) customer satisfaction with product information, product selection, web site aesthetics, web site navigation, customer support, and ease of return, and (ii) customer loyalty. Taken together, the results of our empirical analyses demonstrate that the taxonomy captures information and variety within and across the electronic service-process configurations in ways that can be related to customer satisfaction and customer loyalty.Marketing, Research and Development/Tech Change/Emerging Technologies,
Shallow decision-making analysis in General Video Game Playing
The General Video Game AI competitions have been the testing ground for
several techniques for game playing, such as evolutionary computation
techniques, tree search algorithms, hyper heuristic based or knowledge based
algorithms. So far the metrics used to evaluate the performance of agents have
been win ratio, game score and length of games. In this paper we provide a
wider set of metrics and a comparison method for evaluating and comparing
agents. The metrics and the comparison method give shallow introspection into
the agent's decision making process and they can be applied to any agent
regardless of its algorithmic nature. In this work, the metrics and the
comparison method are used to measure the impact of the terms that compose a
tree policy of an MCTS based agent, comparing with several baseline agents. The
results clearly show how promising such general approach is and how it can be
useful to understand the behaviour of an AI agent, in particular, how the
comparison with baseline agents can help understanding the shape of the agent
decision landscape. The presented metrics and comparison method represent a
step toward to more descriptive ways of logging and analysing agent's
behaviours
Data mining technology for the evaluation of learning content interaction
Interactivity is central for the success of learning. In e-learning and other educational multimedia environments, the evaluation of interaction and behaviour is particularly crucial. Data mining – a non-intrusive, objective analysis technology – shall be proposed as the central evaluation technology for the analysis of the usage of computer-based educational environments and in particular of the interaction with educational content. Basic mining techniques are reviewed and their application in a Web-based third-level course environment is illustrated. Analytic models capturing interaction aspects from the application domain (learning) and the software infrastructure (interactive multimedia) are required for the meaningful interpretation of mining results
Using Noninvasive Brain Measurement to Explore the Psychological Effects of Computer Malfunctions on Users during Human-Computer Interactions
In today’s technologically driven world, there is a need to better understand the ways that common computer malfunctions affect computer users. These malfunctions may have measurable influences on computer user’s cognitive, emotional, and behavioral responses. An experiment was conducted where participants conducted a series of web search tasks while wearing functional nearinfrared spectroscopy (fNIRS) and galvanic skin response sensors. Two computer malfunctions were introduced during the sessions which had the potential to influence correlates of user trust and suspicion. Surveys were given after each session to measure user’s perceived emotional state, cognitive load, and perceived trust. Results suggest that fNIRS can be used to measure the different cognitive and emotional responses associated with computer malfunctions. These cognitive and emotional changes were correlated with users’ self-report levels of suspicion and trust, and they in turn suggest future work that further explores the capability of fNIRS for the measurement of user experience during human-computer interactions
Towards the Development of a Simulator for Investigating the Impact of People Management Practices on Retail Performance
Often models for understanding the impact of management practices on retail
performance are developed under the assumption of stability, equilibrium and
linearity, whereas retail operations are considered in reality to be dynamic,
non-linear and complex. Alternatively, discrete event and agent-based modelling
are approaches that allow the development of simulation models of heterogeneous
non-equilibrium systems for testing out different scenarios. When developing
simulation models one has to abstract and simplify from the real world, which
means that one has to try and capture the 'essence' of the system required for
developing a representation of the mechanisms that drive the progression in the
real system. Simulation models can be developed at different levels of
abstraction. To know the appropriate level of abstraction for a specific
application is often more of an art than a science. We have developed a retail
branch simulation model to investigate which level of model accuracy is
required for such a model to obtain meaningful results for practitioners.Comment: 24 pages, 7 figures, 6 tables, Journal of Simulation 201
Integrity protection for code-on-demand mobile agents in e-commerce
The mobile agent paradigm has been proposed as a promising solution to facilitate distributed computing over open and heterogeneous networks. Mobility, autonomy, and intelligence are identified as key features of mobile agent systems and enabling characteristics for the next-generation smart electronic commerce on the Internet. However, security-related issues, especially integrity protection in mobile agent technology, still hinder the widespread use of software agents: from the agent’s perspective, mobile agent integrity should be protected against attacks from malicious hosts and other agents. In this paper, we present Code-on-Demand(CoD) mobile agents and a corresponding agent integrity protection scheme. Compared to the traditional assumption that mobile agents consist of invariant code parts, we propose the use of dynamically upgradeable agent code, in which new agent function modules can be added and redundant ones can be deleted at runtime. This approach will reduce the weight of agent programs, equip mobile agents with more flexibility, enhance code privacy and help the recoverability of agents after attack. In order to meet the security challenges for agent integrity protection, we propose agent code change authorization protocols and a double integrity verification scheme. Finally, we discuss the Java implementation of CoD mobile agents and integrity protection
Empathic voice assistants: Enhancing consumer responses in voice commerce
Artificial intelligence (AI)-enabled voice assistants (VAs) are transforming firm-customer interactions but often come across as lacking empathy. This challenge may cause business managers to question the overall effectiveness of VAs in shopping contexts. Recognizing empathy as a core design element in the next generation of VAs and the limits of scenario-based studies in voice commerce, this article investigates how empathy exhibited by an existing AI agent (Alexa) may alter consumer shopping responses. AI empathy moderates the original structural model bridging functional, relational, and social-emotional dimensions. Findings of an individual-session online experiment show higher intentions to delegate tasks, seek decision assistance, and trust recommendations from AI agents perceived as empathic. In contrast to individual shoppers, families respond better to functional VA attributes such as ease of use when AI empathy is present. The results contribute to the literature on AI empathy and conversational commerce while informing managerial AI design decisions
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