A modern company should utilize the improvement of technology and information that already became a supporting facilities for their business processes . For supporting sales for a company , they can use a technology for online marketing using e-commerce . A technology that can support e-commerce well is a web service with a REST method that have a purpose to create a service that can be accessed by another different companies on a different websites , and it has a loosely coupled characters that not depends to each other services . Although technology has developed , but for small and medium enterprises ( SMEs ) farmers are still untouched technology as a supporter of promotion and marketing products . Online-based marketing technology is a solution in terms of promotion and marketing . So product data in rural areas can be accessed easily , so it can reach every area . Companies who were keen to harness the potential of the Internet soon became disillusioned with over-hyped expectations . E-commerce companies are now reducing expenses and investment in online marketing and technology [ Aldridge et al. 1997:162 , Bonanos 2001 , Mollison 2002 , Joseph & Poon 2001 ] . It stands to reason that a more targeted approach would be more efficient and cost effective . The paper discusses the findings of a study designed to increase the generalisability , validity and reliability of earlier studies concerning the relationships between attitude toward the ad and aspects of the advertising hierarchy of effects model in the online marketing context . The findings suggest that the traditional advertising hierarchy of effects model is relevant in the online marketing environment , and that investment in online marketing communication can be evaluated using this stable and reliable method . It is , however , suggested that further research is needed to improve the generalisability of the findings . The study shows that online sales promotion direct impaction on the customer ’s attitude and purchase intention is not significant , but by the perception of consumers ease of use and perceived risks induce an indirect impaction . The conclusions of this study would provide helpful suggestions on the online marketing operation . Cloud computing as an exciting development in a educational Institute and online marketing perspective . Students and administrative personnel have the opportunity to quickly and economically access various application platforms and resources through the web pages on-demand . We also find out the existence of marking accounts exists so that a threshold is set to filter these accounts which are not real users . We believe that our approach could be used in industry for identifying high-value users for online marketing purpose . A Personal Recommender System Online Social Networking Sites . system for online marketing site plays a key role for the e-marketing or purchase made online by consumers . As there are many recommendations for a particular keyword , determining which recommendations have higher impact for a particular user is difficult . Real-time response and interactive narrative provide a game-like experience in two systems : Boom Chameleon for evaluating virtual models and StyleCam for developing online product marketing and advertising . A lot of studies in the information systems , advertising , and marketing literature have shown that for the past two decades online banner ad click-through rate is decreasing steadily ( Idemudia et al. 2007 ) . To address this issue , we develop the Visual Perception Model ( VP ) for Online Target marketing and then conducted an experiment by manipulating the independent variables ( i.e. perceived security of online banner ads and match between web user ’s need and banner ad contents ) . The theoretical background for the VP Model is the Visual Perception Theories . This thesis explores techniques and methods of digital advertising . In the first part , the scope and features of digital advertising as well as the tools deployed are presented and defined . An analysis of the complete circle of consumer 's behaviour , as well as all the stages of consumer 's decision journey is here introduced using the Zero Moment of Truth ( ZMOT ) approach . Due to the lack of statistical framework and a viable modeling approach , true data-driven methodology does not exist today in the industry . While predictive modeling has been thoroughly researched in recent years in the digital advertising domain , the attribution problem focuses more on accurate and stable interpretation of the influence of each user interaction to the final user decision rather than just user classification . Traditional classification models fail to achieve those goals . With the wide deployment of digital technologies , come along information artifacts in various forms for various purposes that consumers have to interact with . This paper reports a multi-phase study to address the following questions in the digital advertising context : ( 1 ) to what extent did consumers use ads in the past ? ( 2 ) What are consumers ’ perceived values toward ads ? Abstract : The current research dealt with the simplicity and complexity of the structure of the design of digital advertising , which is subject to technical concepts and methods of modern technology Allow for more complex interactions between the computer and the advertising design and imposed on the design of digital advertising to requires the complexity faced by the direction of complexity and clarity , which depends on the organization of elements and design shapes within the complex electronic structure to achieve aesthetic goals and serve the goals For digital advertising correctly and not overpriced the problem of research lies in the following question posed by the researcher . What is the simplicity and complexity of the digital advertising design structure?The purpose of the research is to focus on the discovery of the rug and the complexity of the structure of the design of digital advertising , while the importance of research by contributing to enrich the knowledge and application of the specialists and specialists to study the simplicity and complexity in the structure of digital advertising design and the introduction of specialized designers working on the subject of simplicity and complexity in the design of digital advertising And the terminology in it , and the researcher has developed spatial boundaries represented by a number of Iraqi digital ad designs , and time limits ( limited in the period of 2017 ) As for the substantive boundaries represented in ( study of simplicity and complexity in the structure of design Digital advertising.while the second section chapter which consist the theoretical frame which interest in three researcher , the first research turning to ( Simplicity in the digital advertising design)while the the second research interest in ( complexity in the digital advertising design)and the third research turning into about the(structure digital advertising design ) . Lattice-Based PSA . In this age of massive data gathering for purposes of personalization , targeted ads , etc . there is an increased need for technology that allows for data analysis in a privacy-preserving manner . Online platforms attract advertisers by offering capabilities to reach audiences likely to be receptive to their ads in a timely and accurate manner . However , the collection and processing of user information required for targeting of ads may lead to privacy concerns . We model the competition between two platforms as a two-stage game where platforms announce their targeting capabilities in the first stage and advertising fees in the second stage . Wherein the obtaining user identification method comprising : receiving a request for obtaining user identification request contains the IP address the user at least ; converts the user IP address corresponding to the line identification ; Analyzing line identifier corresponding to the user is allowed to provide identifying information ; If the line corresponding to the user identification allows providing identity information , the line identification is converted to the corresponding user ID , and the user identifier is returned to the requesting device . By the above-described embodiment , the present application is possible in the case of user authorization , by converting the line identification of the user IP address corresponding to the user ID , user ID and can be used for accurate delivery of ads . We use decision-theoretic techniques to provide a principled way for a potential buyer to make purchasing decisions about private user location data . We illustrate our approach in three scenarios : the delivery of targeted ads specific to a user ’s home location , the estimation of traffic speed , and location prediction . In all three cases , the methodology leads to quantifiably better purchasing decisions than competing methods . Social networks offer various services such as recommendations of social events , or delivery of targeted advertising material to certain users . In this work , we focus on a specific type of services modeled as constrained graph partitioning ( CGP ) . These organizations ’ revenue model is based on advertisement where advertisers are paired with user profiles that are built on top of collected data . This data is being used for a variety of purposes apart from delivering targeted advertisements . Mathematical decision models are impartial to the data on which they operate . 1 . A method for delivery of advertisements or ads , which comprises the step of providing drinks container lid having on its upper surface a printed label , wherein the label comprises a printed advertising or information of news , wherein the printed label is attached to the device for attaching the cover at a predetermined orientation labels advertising of news or information on the cover . ! 2 . Previous research has investigated tracking practices and tracking agencies associated with popular Web sites . Here we investigate the network properties of the third party referral structures that facilitate gathering of user information for the delivery of personalized ads . By considering third party domains associated with the top ten search results for a diverse set of queries , we arrived at the networks of third party domains in four search markets . To optimize that ads on a website can be relevant to the user required a design method . Ontologies are used as domain knowledge in the delivery of relevant ads . Ontology is built through a process of conceptualization , adapted from methods Gruninger and Fox and Methontology . Internet display advertising is a critical revenue source for publishers and online content providers , and is supported by massive amounts of user and publisher data . Targeting display ads can be improved substantially with machine learning methods , but building many models on massive data becomes prohibitively expensive computationally . This paper presents a combination of strategies , deployed by the online advertising firm Dstillery , for learning many models from extremely high-dimensional data efficiently and without human intervention . In many e-commerce applications , ranging from dynamic Web content presentation , to personalized ad targeting , to individual recommendations to the customers , it is important to build personalized profiles of individual users from their transactional histories . These profiles constitute models of individual user behavior and can be specified with sets of rules learned from user transactional histories using various data mining techniques . Driven by the rapid growth of large scale real-time data mining applications for personalized ads and content recommendations , distributed stream processing systems are widely applied in modern big-data architectures . Designs of existing stream computing systems are mostly focusing on the scalability and availability issues . However , the accurate recommendation of online ads is a major problem which plagued advertisers and agencies . By analyzing the unstructured characteristics of online ads and search engine user behavior data , proposed a kind of personalized ads recommendation method based on User-Interest-Behavior model , which can extract the user ’s interest preferences by the topic model and generate the recommended list of ads based on the nearest neighbor and user behavior . The experimental results demonstrate that the personalized ads recommendation method based on nearest neighbor and user behavior can recommend personalized ads and have a better performance than the content-based recommendation method . With the popularity of social networks such as Facebook and twitter , social recommendations have become possible , which rely on individual 's social connections in order to make personalized recommendations of ads , content , products , and people . Since recommendations involving sensitive information , adversaries may re-identify a user 's sensitive information from the recommendation results using background information . New ideas , arising by involving the patient , could help many , but product development and marketing is hard . We hypothesize that digital fabrication ( DF ) , e.g. 3D printing , may be an opportunity to involve patients in the process of custom design and creation of personalized ADs . As DF is minimizing the requirement for manual activities , DF has the potential to enable people in creating ADs for personal use , despite physical limitations . In this paper we present an approach for the presentation of personalized advertisements on mobile devices , which is based on a user model that takes into account user ’s interests over time . The approach has been adopted within the LUNA wireless network project , which is targeted at realizing a business model such that the services provided in the area of Trento , in the North of Italy , are accessible and usable by everybody , at a very low cost . Focusing on the latter issue , previous work has studied which ad positions are , on aggregate , more noticed by users . This work takes the first step toward the personalized positioning of ads on article pages . We demonstrate a correlation between the level of attention that users devote to a story , and the position of the most noticeable graphic element on the side bar . After the review process , we are pleased to include seven papers in this issue , five of which came from extended version of MoMM2010 conference papers and the other two came from direct submissions . In the first paper , Adany , Kraus and Ordonez investigate the area of personalized TV ads to improve the effectiveness of ads distribution to targeted viewers . They study the parameters that contribute to uncertainties of ads allocations to the viewers . Mobile devices provide a continuous data stream of contextual behavioral information which can be leveraged for a variety of user services , such as in personalizing ads and customizing home screens . In this paper , we aim to better understand gender-related behavioral patterns found in application , Bluetooth , and Wi-Fi usage . The area under the curve for the best “ liking ” and “ desire to view again ” classifiers was 0.8 and 0.78 respectively when using a challenging leave-one-commercial-out testing regime . The technique could be employed in personalizing video ads that are presented to people whilst they view programming over the Internet or in copy testing of ads to unobtrusively quantify effectiveness . However , in today ’s world of customer-centricity and individualised services , the richest source of economic value-creation comes from enterprise-customer contacts beyond transactions . The need to make sense of a mass of such touch-points makes process a prevalent and emerging concept in the Front- Office of enterprises , including organisational competences such as marketing operations , customer-relationship management , campaign creation and monitoring , brand management , sales and advisory services , multichannel management , service innovation and management life-cycle , among others . While BPM will continue to make important contributions to the factory of enterprises , the engineering of customer-centric business processes defines a new field of multi-disciplinary work focused on serving customers and improving their experiences .
A modern company should utilize the improvement of technology and information that already became a supporting facilities for their business processes . For supporting sales for a company , they can use a technology for online marketing using e-commerce . A technology that can support e-commerce well is a web service with a REST method that have a purpose to create a service that can be accessed by another different companies on a different websites , and it has a loosely coupled characters that not depends to each other services .
Although technology has developed , but for small and medium enterprises ( SMEs ) farmers are still untouched technology as a supporter of promotion and marketing products . Online-based marketing technology is a solution in terms of promotion and marketing . So product data in rural areas can be accessed easily , so it can reach every area .
Companies who were keen to harness the potential of the Internet soon became disillusioned with over-hyped expectations . E-commerce companies are now reducing expenses and investment in online marketing and technology [ Aldridge et al. 1997:162 , Bonanos 2001 , Mollison 2002 , Joseph & Poon 2001 ] . It stands to reason that a more targeted approach would be more efficient and cost effective .
The paper discusses the findings of a study designed to increase the generalisability , validity and reliability of earlier studies concerning the relationships between attitude toward the ad and aspects of the advertising hierarchy of effects model in the online marketing context . The findings suggest that the traditional advertising hierarchy of effects model is relevant in the online marketing environment , and that investment in online marketing communication can be evaluated using this stable and reliable method . It is , however , suggested that further research is needed to improve the generalisability of the findings .
The study shows that online sales promotion direct impaction on the customer ’s attitude and purchase intention is not significant , but by the perception of consumers ease of use and perceived risks induce an indirect impaction . The conclusions of this study would provide helpful suggestions on the online marketing operation .
Cloud computing as an exciting development in a educational Institute and online marketing perspective . Students and administrative personnel have the opportunity to quickly and economically access various application platforms and resources through the web pages on-demand .
We also find out the existence of marking accounts exists so that a threshold is set to filter these accounts which are not real users . We believe that our approach could be used in industry for identifying high-value users for online marketing purpose .
A Personal Recommender System Online Social Networking Sites . system for online marketing site plays a key role for the e-marketing or purchase made online by consumers . As there are many recommendations for a particular keyword , determining which recommendations have higher impact for a particular user is difficult .
Real-time response and interactive narrative provide a game-like experience in two systems : Boom Chameleon for evaluating virtual models and StyleCam for developing online product marketing and advertising .
A lot of studies in the information systems , advertising , and marketing literature have shown that for the past two decades online banner ad click-through rate is decreasing steadily ( Idemudia et al. 2007 ) . To address this issue , we develop the Visual Perception Model ( VP ) for Online Target marketing and then conducted an experiment by manipulating the independent variables ( i.e. perceived security of online banner ads and match between web user ’s need and banner ad contents ) . The theoretical background for the VP Model is the Visual Perception Theories .
This thesis explores techniques and methods of digital advertising . In the first part , the scope and features of digital advertising as well as the tools deployed are presented and defined . An analysis of the complete circle of consumer 's behaviour , as well as all the stages of consumer 's decision journey is here introduced using the Zero Moment of Truth ( ZMOT ) approach .
Due to the lack of statistical framework and a viable modeling approach , true data-driven methodology does not exist today in the industry . While predictive modeling has been thoroughly researched in recent years in the digital advertising domain , the attribution problem focuses more on accurate and stable interpretation of the influence of each user interaction to the final user decision rather than just user classification . Traditional classification models fail to achieve those goals .
With the wide deployment of digital technologies , come along information artifacts in various forms for various purposes that consumers have to interact with . This paper reports a multi-phase study to address the following questions in the digital advertising context : ( 1 ) to what extent did consumers use ads in the past ? ( 2 ) What are consumers ’ perceived values toward ads ?
Abstract : The current research dealt with the simplicity and complexity of the structure of the design of digital advertising , which is subject to technical concepts and methods of modern technology Allow for more complex interactions between the computer and the advertising design and imposed on the design of digital advertising to requires the complexity faced by the direction of complexity and clarity , which depends on the organization of elements and design shapes within the complex electronic structure to achieve aesthetic goals and serve the goals For digital advertising correctly and not overpriced the problem of research lies in the following question posed by the researcher . What is the simplicity and complexity of the digital advertising design structure?The purpose of the research is to focus on the discovery of the rug and the complexity of the structure of the design of digital advertising , while the importance of research by contributing to enrich the knowledge and application of the specialists and specialists to study the simplicity and complexity in the structure of digital advertising design and the introduction of specialized designers working on the subject of simplicity and complexity in the design of digital advertising And the terminology in it , and the researcher has developed spatial boundaries represented by a number of Iraqi digital ad designs , and time limits ( limited in the period of 2017 ) As for the substantive boundaries represented in ( study of simplicity and complexity in the structure of design Digital advertising.while the second section chapter which consist the theoretical frame which interest in three researcher , the first research turning to ( Simplicity in the digital advertising design)while the the second research interest in ( complexity in the digital advertising design)and the third research turning into about the(structure digital advertising design ) .
Lattice-Based PSA . In this age of massive data gathering for purposes of personalization , targeted ads , etc . there is an increased need for technology that allows for data analysis in a privacy-preserving manner .
Online platforms attract advertisers by offering capabilities to reach audiences likely to be receptive to their ads in a timely and accurate manner . However , the collection and processing of user information required for targeting of ads may lead to privacy concerns . We model the competition between two platforms as a two-stage game where platforms announce their targeting capabilities in the first stage and advertising fees in the second stage .
Wherein the obtaining user identification method comprising : receiving a request for obtaining user identification request contains the IP address the user at least ; converts the user IP address corresponding to the line identification ; Analyzing line identifier corresponding to the user is allowed to provide identifying information ; If the line corresponding to the user identification allows providing identity information , the line identification is converted to the corresponding user ID , and the user identifier is returned to the requesting device . By the above-described embodiment , the present application is possible in the case of user authorization , by converting the line identification of the user IP address corresponding to the user ID , user ID and can be used for accurate delivery of ads .
We use decision-theoretic techniques to provide a principled way for a potential buyer to make purchasing decisions about private user location data . We illustrate our approach in three scenarios : the delivery of targeted ads specific to a user ’s home location , the estimation of traffic speed , and location prediction . In all three cases , the methodology leads to quantifiably better purchasing decisions than competing methods .
Social networks offer various services such as recommendations of social events , or delivery of targeted advertising material to certain users . In this work , we focus on a specific type of services modeled as constrained graph partitioning ( CGP ) .
These organizations ’ revenue model is based on advertisement where advertisers are paired with user profiles that are built on top of collected data . This data is being used for a variety of purposes apart from delivering targeted advertisements . Mathematical decision models are impartial to the data on which they operate .
1 . A method for delivery of advertisements or ads , which comprises the step of providing drinks container lid having on its upper surface a printed label , wherein the label comprises a printed advertising or information of news , wherein the printed label is attached to the device for attaching the cover at a predetermined orientation labels advertising of news or information on the cover . ! 2 .
Previous research has investigated tracking practices and tracking agencies associated with popular Web sites . Here we investigate the network properties of the third party referral structures that facilitate gathering of user information for the delivery of personalized ads . By considering third party domains associated with the top ten search results for a diverse set of queries , we arrived at the networks of third party domains in four search markets .
To optimize that ads on a website can be relevant to the user required a design method . Ontologies are used as domain knowledge in the delivery of relevant ads . Ontology is built through a process of conceptualization , adapted from methods Gruninger and Fox and Methontology .
Internet display advertising is a critical revenue source for publishers and online content providers , and is supported by massive amounts of user and publisher data . Targeting display ads can be improved substantially with machine learning methods , but building many models on massive data becomes prohibitively expensive computationally . This paper presents a combination of strategies , deployed by the online advertising firm Dstillery , for learning many models from extremely high-dimensional data efficiently and without human intervention .
In many e-commerce applications , ranging from dynamic Web content presentation , to personalized ad targeting , to individual recommendations to the customers , it is important to build personalized profiles of individual users from their transactional histories . These profiles constitute models of individual user behavior and can be specified with sets of rules learned from user transactional histories using various data mining techniques .
Driven by the rapid growth of large scale real-time data mining applications for personalized ads and content recommendations , distributed stream processing systems are widely applied in modern big-data architectures . Designs of existing stream computing systems are mostly focusing on the scalability and availability issues .
However , the accurate recommendation of online ads is a major problem which plagued advertisers and agencies . By analyzing the unstructured characteristics of online ads and search engine user behavior data , proposed a kind of personalized ads recommendation method based on User-Interest-Behavior model , which can extract the user ’s interest preferences by the topic model and generate the recommended list of ads based on the nearest neighbor and user behavior . The experimental results demonstrate that the personalized ads recommendation method based on nearest neighbor and user behavior can recommend personalized ads and have a better performance than the content-based recommendation method .
With the popularity of social networks such as Facebook and twitter , social recommendations have become possible , which rely on individual 's social connections in order to make personalized recommendations of ads , content , products , and people . Since recommendations involving sensitive information , adversaries may re-identify a user 's sensitive information from the recommendation results using background information .
New ideas , arising by involving the patient , could help many , but product development and marketing is hard . We hypothesize that digital fabrication ( DF ) , e.g. 3D printing , may be an opportunity to involve patients in the process of custom design and creation of personalized ADs . As DF is minimizing the requirement for manual activities , DF has the potential to enable people in creating ADs for personal use , despite physical limitations .
In this paper we present an approach for the presentation of personalized advertisements on mobile devices , which is based on a user model that takes into account user ’s interests over time . The approach has been adopted within the LUNA wireless network project , which is targeted at realizing a business model such that the services provided in the area of Trento , in the North of Italy , are accessible and usable by everybody , at a very low cost .
Focusing on the latter issue , previous work has studied which ad positions are , on aggregate , more noticed by users . This work takes the first step toward the personalized positioning of ads on article pages . We demonstrate a correlation between the level of attention that users devote to a story , and the position of the most noticeable graphic element on the side bar .
After the review process , we are pleased to include seven papers in this issue , five of which came from extended version of MoMM2010 conference papers and the other two came from direct submissions . In the first paper , Adany , Kraus and Ordonez investigate the area of personalized TV ads to improve the effectiveness of ads distribution to targeted viewers . They study the parameters that contribute to uncertainties of ads allocations to the viewers .
Mobile devices provide a continuous data stream of contextual behavioral information which can be leveraged for a variety of user services , such as in personalizing ads and customizing home screens . In this paper , we aim to better understand gender-related behavioral patterns found in application , Bluetooth , and Wi-Fi usage .
The area under the curve for the best “ liking ” and “ desire to view again ” classifiers was 0.8 and 0.78 respectively when using a challenging leave-one-commercial-out testing regime . The technique could be employed in personalizing video ads that are presented to people whilst they view programming over the Internet or in copy testing of ads to unobtrusively quantify effectiveness .
However , in today ’s world of customer-centricity and individualised services , the richest source of economic value-creation comes from enterprise-customer contacts beyond transactions . The need to make sense of a mass of such touch-points makes process a prevalent and emerging concept in the Front- Office of enterprises , including organisational competences such as marketing operations , customer-relationship management , campaign creation and monitoring , brand management , sales and advisory services , multichannel management , service innovation and management life-cycle , among others . While BPM will continue to make important contributions to the factory of enterprises , the engineering of customer-centric business processes defines a new field of multi-disciplinary work focused on serving customers and improving their experiences .
IMPLEMENTASI MICROSERVICE REPRESENTATIONAL STATE TRANSFER PADA WEB SERVICE ONLINE SHOPPING CART DALAM SISTEM INFORMASI E-COMMERCE Application The Farmer Business Using Method E-Market Place An investigation into search engines as a form of targeted advert delivery An exploratory investigation of attitude toward the website and the advertising hierarchy of effects The Impact of Sales Promotion on the C2C Online Purchasing Behavior: An Empirical Study Benefit of Cloud Computing for Educational Institutions and Online Marketing Identifying High Value Users in Twitter Based on Text Mining Approaches Personalized Recommender System: A Personal Recommender System Online Social Networking Sites Game-like navigation and responsiveness in non-game applications Visual Perception Model for Online Target Marketing Τεχνικές & εργαλεία ψηφιακής διαφήμισης Data-driven multi-touch attribution models What consumers think, feel, and do toward digital ads: a multi-phase study البساطة والتعقید فی بنیة تصمـیم الإعلان الرقمی Revisiting Private Stream Aggregation: Lattice-Based PSA The Role of User Privacy Concerns in Shaping Competition Among Platforms Obtain user identification methods, advertising methods and devices and systems To Buy or Not to Buy A unified agent-based framework for constrained graph partitioning Privacy as a Currency: Un-regulated? The method, apparatus and equipment for the delivery of advertising materials and ads Network Analysis of Third Party Tracking: User Exposure to Tracking Cookies through Search Konseptualisasi Ontologi Iklan Website Scalable hands-free transfer learning for online advertising Expert-Driven Validation of Rule-Based User Models in Personalization Applications Building a Massive Stream Computing Platform for Flexible Applications A Kind of Personalized Advertising Recommendation Method Based on User-Interest-Behavior Model Preserving the Privacy of Social Recommendation with a Differentially Private Approach From Patient to Maker - A Case Study of Codesigning an Assistive Device using 3D printing. Dynamic User Modeling for Personalized Advertisement Delivery on Mobile Devices Engagement-based user attention distribution on web article pages Multimedia systems journal special issue on Mobile Multimedia applications A gender-specific behavioral analysis of mobile device usage data Predicting online media effectiveness based on smile responses gathered over the Internet Enabling Front-Office Transformation and Customer Experience through Business Process Engineering
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ICEE TrustCom/BigDataSE AMCIS KDD ECIS NDSS SECRYPT Web Intelligence KDD BigData Congress SmartCity UNISCON HT ISBA FG
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