Intelligent agents for World Wide Web advertising decisions

We describe a new paradigm for the inclusion of advertisements on the WWW. This paradigm takes advantage of the internet's great ability for instantaneous online processing of information in real time. A methodology is described for the use of intelligent agents to help in the determination of the appropriateness of displaying a given advertisement to a visitor to a site using very specific information about potential customers. Use is made of fuzzy systems modeling for the construction of these agents. © 1997 John Wiley & Sons, Inc.     

Sentiment-oriented contextual advertising

Web advertising (Online advertising), a form of advertising that uses the World Wide Web to attract customers, has become one of the world’s most important marketing channels. This paper addresses the mechanism of Content-based advertising (Contextual advertising), which refers to the assignment of relevant ads to a generic web page, e.g., a blog post. As blogs become a platform for expressing personal opinion, they naturally contain various kinds of expressions, including both facts and comments of both a positive and negative nature. Besides, in line with the major tenet of Web 2.0 (i.e., user-centric), we believe that the web-site owners would be willing to be in charge of the ads which are positively related to their contents. Hence, in this paper, we propose the utilization of sentiment detection to improve Web-based contextual advertising. The proposed sentiment-oriented contextual advertising (SOCA) framework aims to combine contextual advertising matching with sentiment analysis to select ads that are related to the positive (and neutral) aspects of a blog and rank them according to their relevance. We experimentally validate our approach using a set of data that includes both real ads and actual blog pages. The results indicate that our proposed method can effectively identify those ads that are positively correlated with the given blog pages.     

糟糕的谎言和广告

人们不得不对创意代理公司BBH伦敦感到遗憾。当晚会沉静香槟走气,刚刚为Terminal 5保住合约的认知一定已经让他们彻底清醒了。我确定创意者们一定在焦虑地对视．因为他们不知道如何销售希思罗机场的新航站楼。这栋航站楼自2008年3月份开放以来就多灾多难。如今它已经和铁达尼号,兴登堡和入侵伊拉克等噩梦一样长留人们心中。     

网络广告破冰

根据交互式广告局（IAB）的数据,2007年美国网络广告市场投放规模超过225亿元美元（包含搜索引擎在内）,约合1642．5亿元人民币,达到中国的15．78倍,而美国整个GDP规模只是中国的5倍。据业内人士估算,在中国绝大多数企业的广告投放中,互联网广告仅仅占到5％左右。中国网络流量的增长速度远远高于网络广告销售额的增长速度。但即使是这5％的广告份额,也足以囊括进众多互联网公司的发展预期。除了收费邮箱、SP、网络游戏等一系列或成功或失败的盈利尝试之后,除了网易一头扎进网游之外,幸存下来的门户巨头们最后都不约而同地将主要收入来源锁定在了广告上。门户网站上的广告就像报纸、杂志的广告的电子版,带有几分传统广告的强制性,但在web2．0时代,广告以一种更加不着痕迹的方式出现,或者只在你需要的时候出现。无论是目前流行于欧美、国内鲜有的BT行为定向广告,还是谷歌创立的AdWords关键词广告,或是百度更加本土化的竞价排名,以及用户体验放在第一位的社区类网站。无论提到的植人也好,内容营销也好。我们发现让消费者信息接收点更频繁,让网民接收信息的反感度降低。新网络广告技术让我们在这个过程中,有更多的机会使消费者和网民真正能够感受到产品的好处。这个过程也使得强制性的广告慢慢变得平和,最终融入性、参与性的广告会变成数字媒体的主流……     

Frequency capping in online advertising

We study the following online problem. There are n advertisers. Each advertiser \(a_i\) has a total demand \(d_i\) and a value \(v_i\) for each supply unit. Supply units arrive one by one in an online fashion, and must be allocated to an agent immediately. Each unit is associated with a user, and each advertiser \(a_i\) is willing to accept no more than \(f_i\) units associated with any single user (the value \(f_i\) is called the frequency cap of advertiser \(a_i\) ). The goal is to design an online allocation algorithm maximizing the total value. We first show a deterministic \(3/4\) -competitiveness upper bound, which holds even when all frequency caps are \(1\) , and all advertisers share identical values and demands. A competitive ratio approaching \(1-1/e\) can be achieved via a reduction to a different model considered by Goel and Mehta (WINE ‘07: Workshop on Internet and Network, Economics: 335–340, 2007). Our main contribution is analyzing two \(3/4\) -competitive greedy algorithms for the cases of equal values, and arbitrary valuations with equal integral demand to frequency cap ratios. Finally, we give a primal-dual algorithm which may serve as a good starting point for improving upon the ratio of \(1-1/e\) .     

GameSense: game-like in-image advertising

Considering the continuously increasing availability and accessibility of multimedia contents via social networking sites, our research addresses how to monetize the social multimedia contents with an efficient advertising approach. This paper presents a novel game-like advertising system called GameSense, which is driven by the compelling contents of online images. The contextually relevant ads (i.e., product logos) are embedded at appropriate positions within the online games, which are created on the basis of online images. The ads are selected based on multimodal relevance, i.e. text relevance, user relevance and visual content similarity. The game is able to provide viewers rich experience and thus promotes the embedded ads to provide more effective advertising. GameSense represents one of the first attempts toward effective online mashup applications which connect a photo-sharing site with an advertising agency. The effectiveness of GameSense is evaluated over a large-scale real world image set.     

Finding an optimal dynamic advertising policy

In this paper a solution is presented to an important marketing problem : the timing of advertising expenditure. Using a differential equation to model the relationship between the sales and advertising rates and using profit as a criterion, a synthesis of the optimal dynamic advertising policy as a function of the current sales level and length of the campaign is derived. In addition, using profit as a criterion, the profitability under an optimal dynamic advertising policy is compared with the profits obtained using an optimal static policy. It is shown that a significant increase in profits can result from employing the optimal dynamic policy.     

Unintrusive customization techniques for Web advertising

Most online advertisement systems in place today use the concept of consumer targeting: each user is identified and, according to his or her system setup, browsing habits and available off-line information, categorized in order to customize the advertisements for highest user responsiveness. This constant monitoring of a user's online habits, together with the trend to centralize this data and link it with other databases, continuously nurtures fears about the growing lack of privacy in a networked society. In this paper, we propose a novel technique of adapting online advertisement to a user's short term interests in a non-intrusive way. As a proof-of-concept we implemented a dynamic advertisement selection system able to deliver customized advertisements to users of an online search service or Web directory. No user-specific data elements are collected or stored at any time. Initial experiments indicate that the system is able to improve the average click-through rate substantially compared to random selection methods.     

A mean-variance approach to advertising media selection

We propose a simple model of advertising media selection taking into account the uncertainty of the audiences reached effectively. The model is based upon the mean-variance point of view but the formulation differs from the now classical model used in portfolio theory.Here the goal is to minimize the variability of the total desirable audience. A practical solution method is proposed and applied to some examples.     

Variables importance in questionnaire data on advertising

In this article, we deal with the problem of measuring the importance of features, that determine the purchase of the product after being exposed to an advertisement. We use an algorithm called Monte Carlo feature selection, which is based on multiple usage of decision trees, to achieve a ranking of variables from the questionnaire data. Our data generation process relies on low-involvement during the advertisement watching phase and the comparison of advertised products is based on purchase in a virtual shop.     

浅析旁路互联网广告的原理与应用

本文介绍了在现今时代,当网络成为主流媒体的时候,旁路互联网广告的主要表现形式、应用技术、原理分析等.     

AdOn: toward contextual overlay in-video advertising

This paper presents a contextual video advertising system, called AdOn, which supports intelligent overlay in-video advertising. Unlike most current ad-networks such as Youtube that overlay the ads at fixed locations in the videos (e.g., on the bottom fifth of videos 15 s in), AdOn is able to automatically detect a set of spatio-temporal non-intrusive locations and associate the contextually relevant ads with these locations. The overlay ad locations are obtained on the basis of video structuring, face and text detection, as well as visual saliency analysis, so that the intrusiveness to the users can be minimized. The ads are selected according to content-based multimodal relevance so that the relevance can be maximized. AdOn represents one of the first attempts towards contextual overlay video advertising by leveraging information retrieval and multimedia content analysis techniques. The experiments conducted on a video database with more than 100 video programs and 7,000 ad products indicated that AdOn is superior to existing advertising approaches in terms of ad relevance and user experience.     

Optimizing direct response in Internet display advertising

Internet display advertising has grown into a multi-billion dollar a year global industry and direct response campaigns account for about three-quarters of all Internet display advertising. In such campaigns, advertisers reach out to a target audience via some form of a visual advertisement (hereinafter also called “ad”) to maximize short-term sales revenue. In this study, we formulate an advertiser’s revenue maximization problem in direct response Internet display advertisement campaigns as a mixed integer program via piecewise linear approximation of the revenue function. A novelty of our approach is that ad location and content issues are explicitly incorporated in the optimization model. Computational experiments on a large-scale actual campaign indicate that adopting the optimal media schedule can significantly increase advertising revenues without any budget changes, and reasonably sized instances of the problem can be solved within short execution times.     

Targeted interest-driven advertising in cities using Twitter

Targeted advertising is a key characteristic of online as well as traditional-media marketing. However it is very limited in outdoor advertising, that is, performing campaigns by means of billboards in public places. The reason is the lack of information about the interests of the particular passersby, except at very imprecise and aggregate demographic or traffic estimates. In this work we propose a methodology for performing targeted outdoor advertising by leveraging the use of social media. In particular, we use the Twitter social network to gather information about users’ degree of interest in given advertising categories and about the common routes that they follow, characterizing in this way each zone in a given city. Then we use our characterization for recommending physical locations for advertising. Given an advertisement category, we estimate the most promising areas to be selected for the placement of an ad that can maximize its targeted effectiveness. We show that our approach is able to select advertising locations better with respect to a baseline reflecting a current ad-placement policy. To the best of our knowledge this is the first work on offline advertising in urban areas making use of (publicly available) data from social networks.     

Effects of advertising billboards during simulated driving

There is currently a great deal of interest in the problem of driver distraction. Most research focuses on distractions from inside the vehicle, but drivers can also be distracted by objects outside the vehicle. Major roads are increasingly becoming sites for advertising billboards, and there is little research on the potential effects of this advertising on driving performance. The driving simulator experiment presented here examines the effects of billboards on drivers, including older and inexperienced drivers who may be more vulnerable to distractions. The presence of billboards changed drivers’ patterns of visual attention, increased the amount of time needed for drivers to respond to road signs, and increased the number of errors in this driving task.     

Online advertising by the comparison challenge approach

To enhance the effectiveness of online comparisons from a manufacturer’s point of view, we develop a framework for the comparison challenge approach. To develop the comparison challenge framework, we analyze 12 factors that determine the characteristics of comparison and propose models of valuable comparison challenges using the CompareMe and CompareThem strategies. We demonstrate the approaches with the example of PC selection. To help plan the comparison challenges, we formulate a mathematical programming model that maximizes the total value of comparison under the constraints of comparison opportunity and budgetary limitation. The model is applied to eight comparison scenarios, and its performance is contrasted with the view of balancing long-term perspective and short-term revenue increase. The performance of the comparison challenge approach is contrasted with those of random banner and similarity-based comparison approaches, and shows a substantially higher effect.     

Co-evolution-based mechanism design for sponsored search advertising

Sponsored search advertising (SSA), the primary revenue source of Web search engine companies, has become the dominant form of online advertising. Search engine companies, such as Google and Baidu, are naturally interested in SSA mechanism design with the aim to improve the overall effectiveness and profitability of SSA ecosystems. Due to model intractability, however, traditional game theory and mechanism design frameworks provide only limited help as to the design and evaluation of practical SSA mechanisms. In this paper, we propose a niche-based co-evolutionary simulation approach, aiming at computationally evaluating SSA auction mechanisms based on advertisers’ equilibrium bidding behavior generated through co-evolution of their bidding strategies. Using this approach, we evaluate and compare key performance measures of several practical SSA auction mechanisms, including the generalized first and second price auction, the Vickrey–Clarke–Groves mechanism, and a novel hybrid mechanism adopted by sogou.com, a major search engine in China.