994 research outputs found

    CHORUS Deliverable 2.1: State of the Art on Multimedia Search Engines

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    Based on the information provided by European projects and national initiatives related to multimedia search as well as domains experts that participated in the CHORUS Think-thanks and workshops, this document reports on the state of the art related to multimedia content search from, a technical, and socio-economic perspective. The technical perspective includes an up to date view on content based indexing and retrieval technologies, multimedia search in the context of mobile devices and peer-to-peer networks, and an overview of current evaluation and benchmark inititiatives to measure the performance of multimedia search engines. From a socio-economic perspective we inventorize the impact and legal consequences of these technical advances and point out future directions of research

    Term-driven E-Commerce

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    Die Arbeit nimmt sich der textuellen Dimension des E-Commerce an. Grundlegende Hypothese ist die textuelle Gebundenheit von Information und Transaktion im Bereich des elektronischen Handels. Überall dort, wo Produkte und Dienstleistungen angeboten, nachgefragt, wahrgenommen und bewertet werden, kommen natürlichsprachige Ausdrücke zum Einsatz. Daraus resultiert ist zum einen, wie bedeutsam es ist, die Varianz textueller Beschreibungen im E-Commerce zu erfassen, zum anderen können die umfangreichen textuellen Ressourcen, die bei E-Commerce-Interaktionen anfallen, im Hinblick auf ein besseres Verständnis natürlicher Sprache herangezogen werden

    Internet Marketing for Profit Organizations: A framework for the implementation of strategic internet marketing

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    Merged with duplicate record 10026.1/828 on 13.03.2017 by CS (TIS)The development of the Internet has significantly changed the face of established markets and operation approaches across a tremendous spectrum of different industries. Within the competitive environment of those industries, the opportunities and risks derived from the new platform are so ubiquitous that unused opportunities quickly translate into potential risks. Those opportunities and risks demand for a structured approach how to implement a sustainable Internet marketing strategy that targets clear business objectives. Marketing and strategic management theory describes very clear structural principles towards their operational implementation. Based on those principles an extensive literature review has been conducted which confirms the result from representative statistics that demonstrate the lack of a comprehensive framework for strategic Internet marketing. The distinct result of this research is such a comprehensive framework which has been directly derived from the illustrated principles of strategic management and Internet marketing. All major components of this generic framework are designed, evaluated in dedicated surveys and validated in extensive case studies. The main achievements of the research are: • A comprehensive review of the current state-of-the-art Internet marketing strategies • Conceptual specification of a strategic Internet marketing framework with generic applicability to profit organizations • Demonstration of the practical feasibility of the proposed framework at the implementation level (via several examples like the SIMTF and SIMPF) • Confirmation of the applicability of the framework based upon a survey of potential beneficiaries • Validation of the effectiveness of the approach via case study scenarios Changing the understanding of a former technical discipline, the thesis describes how Internet marketing becomes a precise strategic instrument for profit organizations. The new structured, complete and self-similar framework facilitates sales organizations to significantly increase the effectiveness and efficiency of their marketing operations. Furthermore, the framework ensures a high level of transparency about the impact and benefit of individual activities. The new model explicitly answers concerns and problems raised and documented in existing research and accommodate for the current limitations of strategic Internet marketing. The framework allows evaluating existing as well as future Internet marketing tactics and provides a reference model for all other definitions of objectives, KPI and work packages. Finally this thesis also matures the subject matter of Internet marketing as a discipline of independent scientific research providing an underlying structure for subsequent studies.Darmstadt Node of the CSCAN Network at University of Applied Sciences, Darmstad

    Online advertising: analysis of privacy threats and protection approaches

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    Online advertising, the pillar of the “free” content on the Web, has revolutionized the marketing business in recent years by creating a myriad of new opportunities for advertisers to reach potential customers. The current advertising model builds upon an intricate infrastructure composed of a variety of intermediary entities and technologies whose main aim is to deliver personalized ads. For this purpose, a wealth of user data is collected, aggregated, processed and traded behind the scenes at an unprecedented rate. Despite the enormous value of online advertising, however, the intrusiveness and ubiquity of these practices prompt serious privacy concerns. This article surveys the online advertising infrastructure and its supporting technologies, and presents a thorough overview of the underlying privacy risks and the solutions that may mitigate them. We first analyze the threats and potential privacy attackers in this scenario of online advertising. In particular, we examine the main components of the advertising infrastructure in terms of tracking capabilities, data collection, aggregation level and privacy risk, and overview the tracking and data-sharing technologies employed by these components. Then, we conduct a comprehensive survey of the most relevant privacy mechanisms, and classify and compare them on the basis of their privacy guarantees and impact on the Web.Peer ReviewedPostprint (author's final draft

    A planetary nervous system for social mining and collective awareness

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    We present a research roadmap of a Planetary Nervous System (PNS), capable of sensing and mining the digital breadcrumbs of human activities and unveiling the knowledge hidden in the big data for addressing the big questions about social complexity. We envision the PNS as a globally distributed, self-organizing, techno-social system for answering analytical questions about the status of world-wide society, based on three pillars: social sensing, social mining and the idea of trust networks and privacy-aware social mining. We discuss the ingredients of a science and a technology necessary to build the PNS upon the three mentioned pillars, beyond the limitations of their respective state-of-art. Social sensing is aimed at developing better methods for harvesting the big data from the techno-social ecosystem and make them available for mining, learning and analysis at a properly high abstraction level. Social mining is the problem of discovering patterns and models of human behaviour from the sensed data across the various social dimensions by data mining, machine learning and social network analysis. Trusted networks and privacy-aware social mining is aimed at creating a new deal around the questions of privacy and data ownership empowering individual persons with full awareness and control on own personal data, so that users may allow access and use of their data for their own good and the common good. The PNS will provide a goal-oriented knowledge discovery framework, made of technology and people, able to configure itself to the aim of answering questions about the pulse of global society. Given an analytical request, the PNS activates a process composed by a variety of interconnected tasks exploiting the social sensing and mining methods within the transparent ecosystem provided by the trusted network. The PNS we foresee is the key tool for individual and collective awareness for the knowledge society. We need such a tool for everyone to become fully aware of how powerful is the knowledge of our society we can achieve by leveraging our wisdom as a crowd, and how important is that everybody participates both as a consumer and as a producer of the social knowledge, for it to become a trustable, accessible, safe and useful public good.Seventh Framework Programme (European Commission) (grant agreement No. 284709

    Exploring the Online Micro-targeting Practices of Small, Medium, and Large Businesses

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    Facebook and other advertising platforms exploit users data for marketing purposes by allowing advertisers to select specific users and target them (the practice is being called micro-targeting). However, advertisers such as Cambridge Analytica have maliciously used these targeting features to manipulate users in the context of elections. The European Commission plans to restrict or ban some targeting functionalities in the new European Democracy Action Plan act to protect users from such harms. The difficulty is that we do not know the economic impact of these restrictions on regular advertisers. In this paper, to inform the debate, we take a first step by understanding who is advertising on Facebook and how they use the targeting functionalities. For this, we asked 890 U.S. users to install a monitoring tool on their browsers to collect the ads they receive on Facebook and information about how these ads were targeted. By matching advertisers on Facebook with their LinkedIn profiles, we could see that 71% of advertisers are small and medium-sized businesses with 200 employees or less, and they are responsible for 61% of ads and 57% of ad impressions. Regarding micro-targeting, we found that only 32% of small and medium-sized businesses and 30% of large-sized businesses micro-target at least one of their ads. These results should not be interpreted as micro-targeting not being useful as a marketing strategy, but rather that advertisers prefer to outsource the micro-targeting task to ad platforms. Indeed, Facebook is employing optimization algorithms that exploit user data to decide which users should see what ads; which means ad platforms are performing an algorithmic-driven micro-targeting. Hence, when setting restrictions, legislators should take into account both the traditional advertiser-driven micro-targeting as well as algorithmic-driven micro-targeting performed by ad platforms

    Display Advertising with Real-Time Bidding (RTB) and Behavioural Targeting

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    The most significant progress in recent years in online display advertising is what is known as the Real-Time Bidding (RTB) mechanism to buy and sell ads. RTB essentially facilitates buying an individual ad impression in real time while it is still being generated from a user’s visit. RTB not only scales up the buying process by aggregating a large amount of available inventories across publishers but, most importantly, enables direct targeting of individual users. As such, RTB has fundamentally changed the landscape of digital marketing. Scientifically, the demand for automation, integration and optimisation in RTB also brings new research opportunities in information retrieval, data mining, machine learning and other related fields. In this monograph, an overview is given of the fundamental infrastructure, algorithms, and technical solutions of this new frontier of computational advertising. The covered topics include user response prediction, bid landscape forecasting, bidding algorithms, revenue optimisation, statistical arbitrage, dynamic pricing, and ad fraud detection

    Display Advertising with Real-Time Bidding (RTB) and Behavioural Targeting

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    The most significant progress in recent years in online display advertising is what is known as the Real-Time Bidding (RTB) mechanism to buy and sell ads. RTB essentially facilitates buying an individual ad impression in real time while it is still being generated from a user’s visit. RTB not only scales up the buying process by aggregating a large amount of available inventories across publishers but, most importantly, enables direct targeting of individual users. As such, RTB has fundamentally changed the landscape of digital marketing. Scientifically, the demand for automation, integration and optimisation in RTB also brings new research opportunities in information retrieval, data mining, machine learning and other related fields. In this monograph, an overview is given of the fundamental infrastructure, algorithms, and technical solutions of this new frontier of computational advertising. The covered topics include user response prediction, bid landscape forecasting, bidding algorithms, revenue optimisation, statistical arbitrage, dynamic pricing, and ad fraud detection
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