Implementing a low-cost, personalized and location based service for delivering advertisements to mobile users

Liapis, Dimitris; Vassilaras, Spyridon; Yovanof, Gregory S.

doi:10.1109/iswpc.2008.4556182

Cited by 14 publications

(5 citation statements)

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“…Another group of researchers designed a framework called LASA, Location Aware Shopping Advertisement, that uses an ontology based formulation of clients and products profiles to generate a list of ads related to the selection history of a targeted client [5]. LASA uses the shopping mall's Wi-Fi access points to detect the current location of a client, and once the client's location is detected, it will send a list of titles of different products available in all stores in the coverage area of the access point that discovered the client's current location.…”

Section: Related Workmentioning

confidence: 99%

“…The significant rapid growth of mobile advertising is making advertising companies consider mobile phones as a new platform for advertising revenue [1,2]. One of the strategic places for advertising is retail environments, as most mobile phone users visit a mall to purchase products or services, and many researchers are exploiting different methods to generate a personalized list of advertisements that could capture the interest of a mobile phone user [3][4][5].…”

Section: Introductionmentioning

confidence: 99%

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Personal destination pattern analysis with applications to mobile advertising

Barzaiq

Loke

2016

Hum. Cent. Comput. Inf. Sci.

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Many researchers expect mobile advertising to be the killer application in mobile business. In this paper, we introduce a trajectory prediction algorithm called personal destination pattern analysis () to analyse the different destinations in various trajectories of an individual, and to predict a trajectory or a set of destinations that could be visited by that individual. The algorithm works on an individual level. Every destination-pattern analysis is related to the self-history and the personal profile of a targeted individual, not on what others do. In addition, we developed a prototype system called SmartShopper. SmartShopper is a personal destination-pattern-aware pervasive system for mobile advertising in (outdoor and indoor) retail environments. The predicted destinations from the algorithm will be used by SmartShopper to generate a list of relevant advertisements adapted to the personal profile of previous destinations of a targeted individual. We tested the destination prediction accuracy of the algorithm with a synthetic dataset of a virtual mall and a real GPS dataset.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Personal destination pattern analysis with applications to mobile advertising

Barzaiq

Loke

2016

Hum. Cent. Comput. Inf. Sci.

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“…To reduce the spamming advertisements and to achieve the goal of sending personalized advertisements to a user, some researches proposed push methods by utilizing the user's contextual information . In , authors proposed a data push scheduling scheme using the user's preference model.…”

Section: Related Workmentioning

confidence: 99%

“…When many users use the corresponding advertisement system, it seems an unsuitable way to construct and implement the preference model from collecting information of each user. In , authors proposed the data push scheme in the mobile advertisement system by utilizing the user's contextual information, including the user's profile, location, and historic behavior.…”

Section: Related Workmentioning

confidence: 99%

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

Huang

Lin

Hsieh

2013

Softw. Pract. Exper.

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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.

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“…The first steps towards this direction were given by [WeA08] and [HLC08], which proposed extending user basic profile and preferences data to accommodate other sources of context information. This was further explored by [LVY08] and [SeA08], where location information was being used together with user profile data to empower users with a more compelling and interesting advertising experience, by using Global Positioning System (GPS), GSM, wireless networks, Bluetooth, Radio Frequency Identification (RFID) and other location sensor-based technologies. Unfortunately, the attempt of combining different sources of context information to improve the targeting process is not very well explored.…”

Section: Context-awarenessmentioning

confidence: 99%

Key Enablers for User-Centric Advertising Across Next Generation Networks

Simoes¹

2012

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Telecommunication and Internet services are constantly subject to changes, seeking the customer's full satisfaction. Enriching these services with innovative approaches such as contextaware, social, mobile, adaptable and interactive mechanisms, enables users to experience a variety of personalized services seamlessly across different platforms and technologies. In this sense, advertising is no exception, especially if we consider that it will become the business enabler for next generation services. Nevertheless, currently there is no cross-domain solution capable of delivering real-time advertising across heterogeneous environments or domains, and at the same time, addresses users needs, desires and intentions. This happens because most of the products available today are only used within isolated environments / silos. Therefore, managing advertising campaigns across different verticals is still very complex.However, leveraging on the advances provided by Next Generation Networks (NGNs), together with the design principles inherent to Service Oriented Architectures (SOAs) and capabilities offered by Service Delivery Platforms (SDPs), this scenario is about to change.Based on key conceptual entities called enablers, this work aims to change the current scenario. Enablers are software components, which are designed to address specific needs or requirements, but are generic enough to be reused outside a single domain (through well-defined interfaces).More concretely, this thesis introduces three distinct but complementary enablers. The Human Enabler (HE) provides a real-time context brokerage system capable of securely managing different types of user related data in a standardized way. The Reasoning Enabler (RE) is the result of a well-defined methodology that enables new knowledge to be reasoned, based on previously stored data, by aggregating, correlating and inferring new information about people and their contexts. Lastly, the Session Management Enabler (SME) is responsible for abstracting the communication layers. It provides a context-aware multimedia delivery system capable of personalizing and adapting multimedia content according to a set of user and system pre-defined context data or rules, respectively. Altogether, they form the Converged User-Centric Advertising System (CUCAS) and introduce new features that address the needs of both users and advertisers.The contribution of this research is fourfold: first, it analyzes and compares existing technologies and solutions from Information Technology (IT), telecommunications and advertising worlds. Then, based on the problems identified, a set of requirements is defined, an architecture is proposed and realized into a set of complementary enablers (CUCAS). The third point relates to the validation and evaluation of the developed prototype, which provides a better understanding of the current challenges around next generation advertising systems. Finally, based on the technological innovations, it promotes alternative business models that can change the way ...

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Implementing a low-cost, personalized and location based service for delivering advertisements to mobile users

Cited by 14 publications

References 5 publications

Personal destination pattern analysis with applications to mobile advertising

Personal destination pattern analysis with applications to mobile advertising

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

Key Enablers for User-Centric Advertising Across Next Generation Networks

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