A recommendation mechanism for contextualized mobile advertising

Mobile advertising complements the Internet and interactive television advertising and makes it possible for advertisers to create tailor-made campaigns targeting users according to where they are, their needs of the moment and the devices they are using (i.e. contextualized mobile advertising). Therefore, it is necessary that a fully personalized mobile advertising infrastructure be made. In this paper, we present such a personalized contextualized mobile advertising infrastructure for the advertisement of commercial/non-commercial activities. We name this infrastructure MALCR, in which the primary ingredient is a recommendation mechanism that is supported by the following concepts: (1) minimize users' inputs (a typical interaction metaphor for mobile devices) for implicit browsing behaviors to be best utilized; (2) implicit browsing behaviors are then analyzed with a view to understanding the users' interests in the values of features of advertisements; (3) having understood the users' interests, Mobile Ads relevant to a designated location are subsequently scored and ranked; (4) Top-N scored advertisements are recommended. The recommendation mechanism is novel in its combination of two-level Neural Network learning, Neural Network sensitivity analysis, and attribute-based filtering. This recommendation mechanism is also justified (by thorough evaluations) to show its ability in furnishing effective personalized contextualized mobile advertising.     

Why smartphone advertising attracts customers: A model of Web advertising,flow, and personalization

Thirty-five percent of US adults own a smartphone and more than seventy-three percent of the population in South Korea owns a smartphone in the first quarter of 2013. The number of people that use a smartphone has radically increased. Smartphone users always maintain connectivity, and frequent and swift communication with others. As the mobile advertising market is drastically expanded, advertisers and companies should be more attentive to effective smartphone advertising. This study suggests a comprehensive advertising model that combines a Web advertising model, personalization and flow theory in understanding the antecedents of purchase intention and influence processes in the context of smartphone advertisements. The results show that personalization has a positive association with informativeness, credibility, and entertainment of the advertising message while having a negative association with irritation. Purchase intention is increased by advertising value and flow experience. Advertising value has a positive relationship with credibility, entertainment, and incentives. Flow experience is positively associated with credibility, entertainment, incentives. Irritation negatively affects flow experience but advertising value. This study theoretically contributes to the application of the smartphone advertising model and practically contributes influential factors for effective advertising to marketers and advertisers.     

Determinants of consumers’ attitudes toward mobile advertising: The mediating roles of intrinsic and extrinsic motivations

Mobile advertising is booming, due to the popularity of mobile devices. Drawing on motivation theory, this study examines the factors that influence consumers’ attitudes toward mobile advertising. The authors identify timeliness, localization, and personalization of the advertisement message as antecedents of extrinsic motivation, as well as consumer innovativeness and perceived enjoyment as antecedents of intrinsic motivation. Using structural equation modeling, the study analyzes the conceptual model with a sample of 218 mobile phone users. Both intrinsic and extrinsic motivations mediate the effects of the advertising message’s characteristics on mobile phone users’ attitudes toward mobile advertising.     

Predicting user click behaviour in search engine advertisements

According to the specific requirements and interests of users, search engines select and display advertisements that match user needs and have higher probability of attracting users’ attention based on their previous search history. New objects such as user, advertisement or query cause a deterioration of precision in targeted advertising due to their lack of history. This article surveys this challenge. In the case of new objects, we first extract similar observed objects to the new object and then we use their history as the history of new object. Similarity between objects is measured based on correlation, which is a relation between user and advertisement when the advertisement is displayed to the user. This method is used for all objects, so it has helped us to accurately select relevant advertisements for users’ queries. In our proposed model, we assume that similar users behave in a similar manner. We find that users with few queries are similar to new users. We will show that correlation between users and advertisements’ keywords is high. Thus, users who pay attention to advertisements’ keywords, click similar advertisements. In addition, users who pay attention to specific brand names might have similar behaviours too.     

Effects of watermark and music on mobile message advertisements

The development of mobile telecommunication has made breakthrough advances in recent years. Compared to the Internet, mobile telecommunications has anywhere, anytime and always online characteristics. As growth in the Internet advertising market continues, mobile advertising has attracted attention. In this research, the effectiveness of two types of mobile message advertisements, watermarks and music are studied and compared. Two experiments were carried out to test four proposed hypotheses. The independent variable in experiment 1 was the watermark transparency (20%, 40% and 60%). The independent variable in experiment 2 was the music format with five levels: no music, vocal and instrumental version at high volume, vocal and instrumental version at low volume, instrumental version at high volume and instrumental version at low volume. The results showed that the watermarks transparency and format were effective in mobile advertising. The 60% watermark was found better than the 20% and 40% watermarks. The 40% watermark was found better than the 20% watermark for advertisement recall only. Music and vocal/instrumental music versions were effective in mobile advertisements. The vocal music version was found effective in mobile advertising. Music with both vocal and instrumental versions was more effective in advertisement recall than instrumental music for mobile device users.     

An agent system for advertisement inclusion using human-based computation

In this paper, we will present a system based on intelligent agents, which uses human-based computation (HBC) for advertisement adjustment in images. This system will learn from human interaction to obtain a salience map of the most important parts of an image and will use this information to fit a fixed-sized advertisement in the least important part of the image. Although this approximation has been developed to be used in many different applications, its advantages are more evident when used to add advertisements to real time channels, such as websites or video streaming. In this way, media rich applications (principally online) are the most appropriate for this process. Several studies have demonstrated that badly placed advertisements are frequently ignored by users (and may even provoke irritation) and thus do not serve their purpose. In this way, correct advertisement placement is fundamental to maximize an advertisement's effectiveness. As we will see, our agent system is more robust than previous approximations because it is less influenced by specific image features and takes into account the most important parts of an image from the human point of view. In addition, we will compare our approximation with a classical biological model for visual saliency.     

The effects of product involvement and impulse buying on purchase intentions in mobile text advertising

While research in mobile advertising is abundant, limited attention has been paid to date to how consumers respond to mobile advertisements for different product categories and in which way impulsivity affects intentions to purchase. In this paper, we study the dimensionality of the product involvement construct and its effects on consumers’ purchase intentions via a simulated field experiment (N = 736). We show that the cognitive dimension of product involvement and impulsiveness significantly affect purchase intentions. We also present that the relationship between product involvement and purchase intention is moderated by the consumers’ impulse buying personality traits. These findings progress the current state-of-the-art in mobile advertising research, while also having significant practical consequences for the design of effective mobile SMS advertising campaigns.     

基于星形用户社区模型的Twitter广告投放

目前,Twitter的广告投放市场巨大,但针对个性化的广告投放却很少,提出一种基于星形社区模型的广告投放方式.采用网页爬虫获取Twitter用户社交信息,利用高斯模型的多因素权系数算法处理用户社交信息,初步筛选出对产品感兴趣和有影响力的用户,并对其建立星形结构模型,二次筛选,确定出度核心节点并识别出目标星形子图社区,将该社区的出度核心节点作为广告投放载体进行个性化的投放.实验结果表明该广告投放方式具有较高的社区用户满意度.     

The selective use of redundancy for video streaming over Vehicular Ad Hoc Networks

Video streaming over Vehicular Ad Hoc Networks (VANETs) offers the opportunity to deploy many interesting services. These services, however, are strongly prone to packet loss due to the highly dynamic topology and shared wireless medium inherent in the VANETs. A possible strategy to enhance the delivery rate is to use redundancy for handling packet loss. This is a suitable technique for VANETs as it does not require any interaction between the source and receivers.In this work, we discuss novel approaches for the use of redundancy based on the particularities of video streaming over VANETs. A thorough study on the use of redundancy through Erasure Coding and Network Coding in both video unicast and video broadcast in VANETs is provided. We investigate each strategy, design novel solutions and compare their performance. We evaluated the proposed solutions from the perspective not only of cost as bandwidth utilization, but also the offered receiving rate of unique video content at the application layer. This perspective is fundamental to understanding how redundancy can be used without limiting the video quality that can be displayed to end users.Furthermore, we propose the selective use of redundancy solely on data that is more relevant to the video quality. This approach offers increases in overall video quality without leading to an excessive overhead nor to a substantial decrease in the receiving rate of unique video content.     

Perception of Interactivity: Affects of Four Key Variables in Mobile Advertising

There are indications that interactivity could benefit the effectiveness of mobile advertisements. But there are few guidelines on how to design interactive mobile advertisements. This study investigated the influences of various design features of mobile advertisements on perceived interactivity and the relationship between perceived interactivity and attitude toward mobile advertisements. An experiment consisting of 2 sessions was conducted to test 5 proposed hypotheses with 40 participants. Results showed that the number of user control options and the customizability of advertisements have significant influences on users' perception of interactivity. The more options a message advertisement provides, the more interactive the participants perceive the advertisement; a customizable game advertisement is perceived as more interactive than an uncustomizable game advertisement. But no significant effects of presenting instructional information of mobile Web advertisements and including humorous elements were found. Finally, perceived interactivity was found a strong predictor of attitude toward mobile advertisement.     

Privacy‐preserving targeted mobile advertising: requirements,design and a prototype implementation

With the continued proliferation of mobile devices, the collection of information associated with such devices and their users—such as location, installed applications and cookies associated with built‐in browsers—has become increasingly straightforward. By analysing such information, organisations are often able to deliver more relevant and better focused advertisements. Of course, such targeted mobile advertising gives rise to a number of concerns, with privacy‐related concerns being prominent. In this paper, we discuss the necessary balance that needs to be struck between privacy and utility in this emerging area and propose privacy‐preserving targeted mobile advertising as a solution that tries to achieve that balance. Our aim is to develop a solution that can be deployed by users but is also palatable to businesses that operate in this space. This paper focuses on the requirements and design of privacy‐preserving targeted mobile advertising and also describes an initial prototype. We also discuss how more detailed technical aspects and a complete evaluation will underpin our future work in this area. Copyright © 2016 John Wiley & Sons, Ltd.     

Eliminating the effect of freezing frames on user perceptive by using a time interleaving technique

Streaming video over a wireless network faces several challenges such as high packet error rates, bandwidth variations, and delays, which could have negative effects on the video streaming and the viewer will perceive a frozen picture for certain durations due to loss of frames. In this study, we propose a Time Interleaving Robust Streaming (TIRS) technique to significantly reduce the frozen video problem and provide a satisfactory quality for the mobile viewer. This is done by reordering the streaming video frames as groups of even and odd frames. The objective of streaming the video in this way is to avoid the losses of a sequence of neighbouring frames in case of a long sequence interruption. We evaluate our approach by using a user panel and mean opinion score (MOS) measurements; where the users observe three levels of frame losses. The results show that our technique significantly improves the smoothness of the video on the mobile device in the presence of frame losses, while the transmitted data are only increased by almost 9% (due to reduced time locality).     

Who avoids location-based advertising and why? Investigating the relationship between user perceptions and advertising avoidance

This study investigates how perceptual factors are associated with mobile consumers’ avoidance of location-based mobile advertising (LBA), and whether the relationships between the perceptual factors and LBA avoidance are influenced by consumers’ mobile device usage levels. The results of a national web survey with 605 Singaporean mobile consumers show that those who find LBA impedes goals, requires sacrifice, and lacks utility are more likely to avoid it. When examining the differences of heavy, medium, and light mobile device users, the analyses reveal that the effects of perceived utility and entertainment on LBA avoidance are greater for medium and heavy users than for light users. Theoretical and practical implications of our findings are discussed, as are the limitations and suggestions for future research.     

Predicting the influence of users’ posted information for eWOM advertising in social networks

Many social network websites have been aggressively exploring innovative electronic word-of-mouth (eWOM) advertising strategies using information shared by users, such as posts and product reviews. For example, Facebook offers a service allowing marketers to utilize users’ posts to automatically generate advertisements. The effectiveness of this practice depends on the ability to accurately predict a post’s influence on its readers. For an advertising strategy of this nature, the influence of a post is determined jointly by the features of the post, such as contents and time of creation, and the features of the author of the post. We propose two models for predicting the influence of a post using both sources of influence, post- and author-related features, as predictors. An empirical evaluation shows that the proposed predictive features improve prediction accuracy, and the models are effective in predicting the influence score.     

Provisioning of energy consumption information for mobile ads

Advertisement-embedded mobile applications have been reported to consume a non-trivial amount of energy. Although a few studies have focused on the energy consumption of mobile advertisements (ads), no previous work has addressed the mobile ad ecosystem, which consists of users, application developers, and ad providers. In this paper, we define the advertisement energy information (AEI) required for the mobile ad ecosystem, and we propose a set of application programming interfaces (APIs) to provide AEI that considers various requirements of the underlying ecosystem. To realize the APIs, we developed a system service in Android to collect the AEI accurately and with low overhead. The experiment results show the validity of the proposed scheme, and the case studies demonstrate the usefulness of the proposed APIs.     

Differentiation of online text-based advertising and the effect on users’ click behavior

Online syndicated text-based advertising is ubiquitous on news sites, blogs, personal websites, and on search result pages. Until recently, a common distinguishing feature of these text-based advertisements has been their background color. Following intervention by the Federal Trade Commission (FTC), the format of these advertisements has undergone a subtle change in their design and presentation. Using three empirical experiments, we investigate the effect of industry-standard advertising practices on click rates, and demonstrate changes in user behavior when this familiar differentiator is modified. Using three large-scale experiments (N₁ = 101, N₂ = 84, N₃ = 176) we find that displaying advertisement and content results with a differentiated background results in significantly lower click rates. Our results demonstrate the strong link between background color differentiation and advertising, and reveal how alternative differentiation techniques influence user behavior.     

Wireless CDN video streaming architecture for IPTV

Wireless IPTV (Internet Protocol TeleVision) aims to make the traditional IPTV and related services available to users anywhere, anytime, on any device, and through any network. Mobile streaming TV is one of the alternatives to deploy such a system; others are DVB-H or MediaFLO. In this paper we propose an alternative CDN-based architecture to distribute contents to different access networks, in order to create a triple screen platform. The core elements of the system are the video streamers, acting as surrogates of the mobile CDN-based architecture, installed in the access networks (including mobile), and the transcoding servers in the premises of the content providers. The paper focused on the wireless part of the system, analyzing the architecture and performance results related with the video coding and the efficiency obtained due to the placement of the streaming servers. The system has been deployed by a Spanish media company for its use with different Telcos, ISPs and media companies.     

Real-time data dissemination in mobile peer-to-peer networks

Mobile peer-to-peer networks have found many uses such as streaming of audio and video data. There are circumstances, such as emergency situations and disaster recovery, when real-time delivery is a fundamental requirement. The problem is challenging due to the limited network capacity, the variable transmission rates and the unpredictability with respect to the network conditions in the mobile peer-to-peer network.In this paper we address the problem of real-time data dissemination of multimedia streams in mobile peer-to-peer networks. Four routing algorithms are proposed based on a packet's deadline, priority or a combination of these metrics. They are simulated under different setups in a mobile peer-to-peer network with Bluetooth connectivity and nodes broadcasting audio and video streams using different priorities. We compare the performance of the algorithms using a number of metrics. Detailed experimental results are presented. Based on these results, propositions on the usage of the algorithms and the design of network requirements are presented.     

The personalized context‐aware mobile advertisement system using a novel approaching detection method over cellular networks

With the rapid development of smartphones and personal tablet computers, it brings a greatly growing rate of ubiquitous applications for location‐based services (LBS). One famous LBS is the mobile advertisement. A mobile advertisement system brings benefits and opportunities among users, service providers, and advertisers. In this paper, we propose a personalized context‐aware mobile advertisement system (PCA‐MAS) over cellular networks, which contains two new techniques called (i) approaching detection method (ADM) and (ii) context‐aware ad targeting method (CAADTM). ADM can find some point of interests that a user is approaching; CAADTM pushes advertisements that satisfy user's requirement based on the user's context, that is, user's profile, current time, current position, and so on. Our experimental results show that (i) ADM has the good hit rate to determine those point of interests that a user is approaching within the 150‐m radius of the approaching range, and (ii) CAADTM has the good hit rate of finding appropriate advertisements that a user prefers through the favorite content table filtering, the annoying content table filtering, and the advertisement clicking feedback. Copyright © 2013 John Wiley & Sons, Ltd.     

基于MDP的移动流媒体能耗优化方法

针对移动流媒体应用的高能耗问题,面向异构平台环境,提出了基于马尔科夫决策过程的移动流媒体能耗优化方法。通过综合不同用户使用习惯、视频播放功耗、播放时长及当前网络状态,基于最大奖励原则对CPU资源进行合理分配,以达到降低功耗的目标。实验结果表明,相比于系统默认异核多处理调度策略,提出的能耗优化方法能在保持流媒体视频播放质量的同时,有效降低其在移动终端的能耗。