Hasil untuk "Advertising"

Filippo de Feo

Stochastic optimal control control problems with merely measurable coefficients are not well understood. In this manuscript, we consider fully non-linear stochastic optimal control problems in infinite horizon with measurable coefficients and (local) uniformly elliptic diffusion. Using the theory of $L^p$-viscosity solutions, we show existence of an $L^p$-viscosity solution $v\in W_{\rm loc}^{2,p}$ of the Hamilton-Jacobi-Bellman (HJB) equation, which, in turn, is also a strong solution (i.e. it satisfies the HJB equation pointwise a.e.). We are then led to prove verification theorems, providing necessary and sufficient conditions for optimality. These results allow us to construct optimal feedback controls and to characterize the value function as the unique $L^p$-viscosity solution of the HJB equation. To the best of our knowledge, these are the first results for fully non-linear stochastic optimal control problems with measurable coefficients. We use the theory developed to solve a stochastic optimal control problem arising in economics within the context of optimal advertising.

Anastasiia Soboleva, Andrey Pudovikov, Roman Snetkov et al.

Online advertising platforms often face a common challenge: the cold start problem. Insufficient behavioral data (clicks) makes accurate click-through rate (CTR) forecasting of new ads challenging. CTR for "old" items can also be significantly underestimated due to their early performance influencing their long-term behavior on the platform. The cold start problem has far-reaching implications for businesses, including missed long-term revenue opportunities. To mitigate this issue, we developed a UCB-like algorithm under multi-armed bandit (MAB) setting for positional-based model (PBM), specifically tailored to auction pay-per-click systems. Our proposed algorithm successfully combines theory and practice: we obtain theoretical upper estimates of budget regret, and conduct a series of experiments on synthetic and real-world data that confirm the applicability of the method on the real platform. In addition to increasing the platform's long-term profitability, we also propose a mechanism for maintaining short-term profits through controlled exploration and exploitation of items.

To Eun Kim, João Coelho, Gbemileke Onilude et al.

As conversational search engines increasingly adopt generation-based paradigms powered by Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG), the integration of advertisements into generated responses presents both commercial opportunities and challenges for user experience. Unlike traditional search, where advertisements are clearly delineated, generative systems blur the boundary between informational content and promotional material, raising concerns around transparency and trust. In this work, we propose a modular pipeline for advertisement management in RAG-based conversational systems, consisting of an ad-rewriter for seamless ad integration and a robust ad-classifier for detection. We leverage synthetic data to train high-performing classifiers, which are then used to guide two complementary ad-integration strategies: supervised fine-tuning of the ad-rewriter and a best-of-N sampling approach that selects the least detectable ad-integrated response among multiple candidates. Our evaluation focuses on two core questions: the effectiveness of ad classifiers in detecting diverse ad integration strategies, and the training methods that best support coherent, minimally intrusive ad insertion. Experimental results show that our ad-classifier, trained on synthetic advertisement data inspired by marketing strategies and enhanced through curriculum learning, achieves robust detection performance. Additionally, we demonstrate that classifier-guided optimization, through both fine-tuning and best-of-N sampling, significantly improves ad stealth, enabling more seamless integration. These findings contribute an adversarial co-evolution framework for developing more sophisticated ad-aware generative search systems and robust ad classifiers.

Matt Keon, Aabid Karim, Bhoomika Lohana et al.

Large language models (LLMs) generate fluent text yet often default to safe, generic phrasing, raising doubts about their ability to handle creativity. We formalize this tendency as a Galton-style regression to the mean in language and evaluate it using a creativity stress test in advertising concepts. When ad ideas were simplified step by step, creative features such as metaphors, emotions, and visual cues disappeared early, while factual content remained, showing that models favor high-probability information. When asked to regenerate from simplified inputs, models produced longer outputs with lexical variety but failed to recover the depth and distinctiveness of the originals. We combined quantitative comparisons with qualitative analysis, which revealed that the regenerated texts often appeared novel but lacked true originality. Providing ad-specific cues such as metaphors, emotional hooks and visual markers improved alignment and stylistic balance, though outputs still relied on familiar tropes. Taken together, the findings show that without targeted guidance, LLMs drift towards mediocrity in creative tasks; structured signals can partially counter this tendency and point towards pathways for developing creativity-sensitive models.

Kasra Khaghanizadeh, Mohammad Ghasemi, Abdolali Keshtegar et al.

AbstractThe aim of the present study is to design and develop an innovative ecosystem model for small and medium-sized enterprises in Iran. The design of this innovation ecosystem model can act as a driving factor for involving various actors in the production, design, development and commercialization of innovative products and services in small and medium-sized enterprises. To achieve this goal, the meta-synthesis method was used and, according to previous studies, 1469 articles were selected and interpreted from among various articles. In fact, an interpretation beyond previous studies was obtained and in this method, the findings were combined and a comprehensive view of the phenomenon in question was obtained. Finally, 69 articles were selected using the screening method. The findings show that, according to the combination of studies conducted, the dimensions of the innovation ecosystem model in small and medium-sized enterprises include innovation in inputs, innovation in processes, innovation in outcomes and outputs, social innovations, strategy innovations, and environmental sustainability innovations. In fact, in addition to these dimensions, their indicators and components have also been extracted, which actually play a facilitating role in implementing the desired model. The results show that the innovation ecosystem model, which is the result of extracting indicators and components, can be applied in small and medium-sized enterprises.IntroductionToday, creativity and innovation and the ability to discover new opportunities are among the most essential characteristics of entrepreneurs. Competition in technology and ensuring and continuing life and survival in companies and industries require finding new solutions and methods of dealing with problems that depend greatly on innovation, creation of new products, processes, and approaches. In today's business world, some factors such as continuous and sometimes fundamental changes in technologies, emergence of new demands from customers, short product and service life cycles, disappearance of the boundary between industries and the constant presence of new entrants from different industries and many other factors have created a special space and as a result of these changes, companies are dependent on other companies and institutions to create value for their customers. Considering value creation from an ecosystem perspective is different from the traditional view, which is based on value creation by a specific company and is static. Therefore, to use ecosystems, companies need to change their perspective from a traditional and company-based and static view to an ecosystem view (Fuller et al., 2019). In the innovation ecosystem, key people are connected to many other factors in valuable interactions. One of the reasons for the increasing importance of innovation at the international level is the globalization of markets and the competitive pressure on companies to keep on seeking innovation. Innovation ecosystems connect the way actors, producers, service providers, end users, regulators, and civil society organizations to achieve a collective outcome (Zakobedes & Calleagues, 2017). Ecosystems similar to innovation ecosystems increase the sustainability of organizations and industries and can support their sustainable activities towards sustainable development (Reezner & Calleagues, 2019), because it is likely to have implications for both researchers and policymakers and practitioners (Dedhayer & Calleagues, 2018).Regarding the theoretical gap in the research, it can be said that by reviewing the research, it was found that limited studies have been presented in the field of designing and developing a coherent framework for the innovation ecosystem in small and medium-sized enterprises in the country, although many of these studies were very general or only analyzed the innovation ecosystem from one aspect (Holm & Ankarkrona, 2016). Also, regarding the necessity of conducting this research, it can be said that previous studies have mainly focused on the technological dimension of the ecosystem, which limits the possibility of examining and evaluating complex ecosystems (Chen et al., 2016). On the other hand, a large part of the studies have only examined a few ecosystem actors and the interactions between them, and have not comprehensively examined all stakeholders and the relationships between them (Motoyama & Knowlton, 2017). Today, designing an innovation ecosystem model can be considered as a stimulus to increase the performance of these small and medium-sized industries. In this regard, the present study attempts to, through the study of previous research, address the question of how the innovation ecosystem model in small and medium-sized enterprises is designed and developed using the meta-synthesis model.Theoretical frameworkIn the present era, innovation emerges when the organization seeks to respond to an environment in which it is operating under environmental disturbances, and this has caused managers to focus on organizational transformation in order to adapt and respond to changes in a timely manner and maintain the organization's competitive advantages, and they consider themselves in need of an appropriate leadership style and human capital management to deal with such changes (Veghry and Fileshver, 2024).Small companies may not grow with proper innovation management, but they can still survive. Companies that have planned innovation management well will be able to survive (Zoares Eskoober and Goozman, 2017). On the other hand, businesses also face obstacles, including restrictions and laws on content production and advertising, audience limitations, the impact of political and social crises, the presence of competition, references, government restrictions, unethical behavior of audiences and competitors, and systemic problems such as messaging bugs and lack of financial support, lack of sufficient facilities, and ideological limitations (Kafshdar Toosi, 2024). As Shompiter emphasizes, innovation is a powerful tool for new companies to successfully enter the market and challenge established companies. Also, established organizations need innovation to maintain their competitive position in the face of new and emerging or “disruptive” technologies (Cresstenson, 2010). Radical innovations are those that are developed by a company and are also innovations that are new to an industry (Reechesten and Salter, 2006). SMEs, known for their centralized management and informal structures, are therefore more prone to innovation. Companies that propose product innovation should focus on new product development or technological improvements, while companies that introduce new organizational methods such as process innovation should focus on knowledge and management culture (Ikermorat and Bardoogan, 2011). However, the most difficult task for SMEs is to realize this idea to meet demand. SMEs must follow several stages until the newly created product becomes marketable. New product development is a process in which new ideas are used in the final product and service. This process consists of six stages. Research and development stage, product design, concept testing, prototype, test marketing, and commercialization or launch. All these processes require resources and budget. Studies show that in Iran, not much research has been done so far on the topic of innovation ecosystem model in small and medium-sized companies and key players, and even practical models and patterns in this field. Considering that today advanced economies have placed innovation as their main factor and driver, developing countries need innovation in services and products to accelerate their growth and development. Considering the economic conditions of the country, many small and medium-sized companies cannot continue their production cycle.MethodologyThis research is applicable in terms of purpose, qualitative in terms of data collection, and with a meta-synthesis approach in terms of research implementation method. This research is based on the seven-step method of Sandelowski and Barroso (2007) in meta-synthesis.Research findingsIn this research, based on articles discovered from reputable journals and databases, 68 articles were fully reviewed and by combining the findings, six dimensions along with their indicators and components were identified for the innovation ecosystem, described below. Based on the results of the meta-synthesis, the dimensions of the innovation ecosystem can be categorized into six main areas, including input innovation, process innovation, strategy innovation, output and outcome innovation, social innovation, and environmental innovation.Conclusion The first dimension is the input innovation dimension, consistent with the research of Liang & Wang (2023) and Block et al., (2023), and based on the research conducted, it is suggested that in order to have an effective input in the field of innovation, its indicators and components need to be calculated in a real sense and in accordance with the environment in which it operates. These indicators and components include crowdfunding, launching a venture capital fund, hiring startup-minded employees, innovation in financing methods, etc. The second dimension is the process innovation dimension, which acts as a strategic role in converting inputs into outputs and, in a way, extracts accurate and correct outputs and actions after a targeted and effective analysis of inputs. The results of this dimension are consistent with the research of Piñera-Salmerón et al., (2023). In this dimension, indicators and components such as the production of artificial intelligence-based services, updating machinery and equipment, setting up a research and development unit, using artificial intelligence capabilities, smartening business processes, continuous product improvement, application of quality tools, redesigning parts and components, etc. are mentioned. The third dimension is innovation in outputs and outcomes, which are actually indicators such as obtaining an electronic trust mark, developing new product versions, setting up spin-off companies, using online sales platforms, developing the export of innovative products, obtaining a knowledge-based mark for products, commercializing innovative products, etc., and is consistent with the research of Jin & Li (2023). The fourth dimension is social innovation, the results of which are consistent with the research of Sampaio & Sebastião (2024), and these studies showed that this dimension facilitates the cooperation of non-governmental sectors and civil society to promote innovation and also influence the innovation process. In fact, social innovation is an environmental factor that plays a decisive role in the adoption of innovation and the production of innovation. The indicators of this dimension include the development of corporate citizenship behavior, the allocation of budget lines to the field of social responsibility, the creation of local networks for the exchange of knowledge and benefits, etc. The fifth dimension is innovation strategies, which is consistent with the research of Agazu & Kero (2024). The components of this dimension include the development of entrepreneurial culture, the development of digital entrepreneurship, co-creation in the production of new products, and the development of gradual innovation, and therefore it is suggested that strategy be considered as a facilitator of the role of the innovation path and the purposefulness of the innovation development process. The sixth dimension is environmental innovation, which includes indicators and components such as green innovation development, green management development, green product development, green marketing development, reduction of environmental pollutants, use of less polluting materials, etc., which is consistent with the research of Kirikkaleli et al., (2023). The three dimensions of social innovation, environmental innovation, and strategic innovation are considered as external environmental dimensions of innovation that affect the internal environment of innovation and in a way stimulate innovation. Any research or management action in the field of innovation ecosystems requires a precise understanding of the six dimensions.

Qingjun Li, Zhongxin Kang, Huilin Zheng et al.

With the rapid advancement of digitization, the duty of the digital economic climate in advertising regional economic growth is ending up being progressively noticeable. Nonetheless, there is relatively little research study on how the digital economic situation specifically impacts regional environment-friendly and high-quality financial growth (RGED). This study utilizes provincial panel data from 2013 to 2020 in China to empirically assess the effect of the digital economic environment and validates its effect with a fixed impacts model. The study has produced four unique and important findings for: firstly, the effect of the digital economic climate on RGED exhibits nonlinear qualities; Second of all, RGED is significantly influenced by the “∩ - formed” effect of the advancement of the digital economic situation and the degree of industrial digitization; Finally, the influence of digital framework and digital industrialization on RGED exhibits a considerable “U-shaped” pattern; Fourth, the digital economic situation indirectly advertises the growth of RGED by enhancing human funding and updating commercial structure. These conclusions offer beneficial plan support for relevant financial entities to achieve RGED. First published online 05 June 2025

Afzal Ahmed, Muhammad Raees

In today's businesses, marketing has been a central trend for growth. Marketing quality is equally important as product quality and relevant metrics. Quality of Marketing depends on targeting the right person. Technology adaptations have been slow in many fields but have captured some aspects of human life to make an impact. For instance, in marketing, recent developments have provided a significant shift toward data-driven approaches. In this paper, we present an advertisement model using behavioral and tracking analysis. We extract users' behavioral data upholding their privacy principle and perform data manipulations and pattern mining for effective analysis. We present a model using the agent-based modeling (ABM) technique, with the target audience of rapid transit system users to target the right person for advertisement applications. We also outline the Overview, Design, and Details concept of ABM.

Bhong Mahesh, Nirsanametla Yadaiah, Gudainiyan Jitendra et al.

This research examines the synergistic impacts of hybrid nanofillers, particularly silica nanoparticles (SiO2) and multi-walled carbon nanotubes (MWCNTs), in polyethene (PE) network nanocomposites. The nanocomposites are methodically arranged and characterized for predominant mechanical and electrical execution. Tensile tests uncover a significant upgrade in mechanical properties, with test C showing a tensile quality of 83.2 MPa, flexible modulus of 3.6 GPa, and stretching at a break of 11.8%. Electrical conductivity estimations demonstrate an outstanding change, with test C coming to 1.1×10 −4 S/m Comparative investigation with related works exhibits the competitive points of interest of the crossover nanocomposites, adjusting with later improvements within the field. Morphological examination through checking and transmission electron microscopy affirms the successful scattering and interconnectivity of cross-breed nanofillers inside the polymer network. Affectability examinations emphasize the significance of preparing parameters in fitting nanocomposite properties, whereas recreation studies give hypothetical bits of knowledge into microstructural angles impacting by and large execution. This study contributes to the advancing scene of hybrid nanocomposite materials, advertising a promising road for the improvement of progressed materials with improved multifunctionality.

Ayana Adilova, Pakizar Shamoi

The analysis of aesthetic assessment is a complex and subjective task that has attracted researchers for a long time. The subjective nature of aesthetic preferences presents a significant challenge in defining and quantifying what makes images visually appealing. The current paper addresses this gap by introducing a novel methodology for quantifying and predicting aesthetic preferences in the case of interior design images. Our study combines fuzzy logic with image processing techniques. Firstly, a dataset of interior design images was collected from social media platforms, focusing on essential visual attributes such as color harmony, lightness, and complexity. Then, these features were integrated using a weighted average to compute a general aesthetic score. Our methodology considers personal color tastes when determining the overall aesthetic appeal. Initially, user feedback was collected on primary colors such as red, brown, and others to gauge their preferences. Subsequently, the image’s five most prevalent colors were analyzed to determine the preferred color scheme based on pixel count. The color scheme preference and the aesthetic score are then passed as inputs to the fuzzy inference system to calculate an overall preference score. This score represents a comprehensive measure of the user’s preference for a particular interior design, considering their color choices and general aesthetic appeal. The Two-Alternative Forced Choice (2AFC) method validated the methodology, resulting in a notable hit rate of 0.68. This study can help in fields such as art, design, advertising, or multimedia content creation, where aesthetic analysis and preference prediction are crucial. In the case of interior design, this study can help designers and professionals better understand and meet people’s preferences, especially in a world that relies heavily on digital media.

Azadeh Asadian, Dariush Matlabi, Fahimeh Babalhavaeji et al.

1. IntroductionAll efforts of business managers are to achieve productivity. In such a way that the need to increase productivity in organizations for more profitability is inevitable and every year a lot of money is spent on how to increase productivity and promote their business. One of the important and fundamental prerequisites for achieving a business model is its components and indicators in a standardized format. The changes that have come from the internet space have made knowledge flow and be exploited in a faster way in the departments of an organization. In the meantime the knowledge brokers can help to correct and improve the flow of knowledge and fill the information gap between producers and users of knowledge, thereby helping to increase the productivity of organizations and businesses.2. Literature ReviewKnowledge brokers provide the act of creating, sharing and using knowledge in an organization or between organizations. One of the ways to correct and improve the flow of knowledge is to use knowledge brokers who fill the gap between producers and knowledge users. The unique possibilities of the Internet have led to the emergence of a new form of business, which is now known as Internet business. These businesses have been created by entrepreneurial people with new ideas who have a creative and talented mind. Osterwalder's business model is known as the most common and broad business model canvas. This model is the provider of a common language for describing, visualizing, evaluating, and changing the business model. Productivity is called a method, a concept and an attitude about work and life, and in fact, they look at it as a culture and a worldview. Productivity is the effective and efficient use of inputs or resources for production by providing outputs. The background check shows that so far, many researches have been done in the field of knowledge brokers and internet businesses and the relationship between business and productivity inside and outside the country. On the other hand, studies show that many researches have been conducted abroad on the role and functions of knowledge brokers. This is despite the fact that none of them have analyzed the components and indicators of the internet business model for knowledge brokers with the approach of increasing productivity.3. Methodology The current research is applied in terms of purpose and mixed and exploratory in terms of approach. The research has been done in three stages: to identify the components and indicators of knowledge-based internet business for knowledge brokers using the meta-combination method, to determine the level of agreement of experts using the fuzzy Delphi method, and to determine the importance of each of the components and the calculated indicators were used using the survey-analytical method. In the first stage, the statistical population was 10,617 documents related to the research subject, out of which 65 documents were selected and studied further. In the second stage, in order to confirm the components and indicators calculated from the first stage, the fuzzy Delphi method and a questionnaire (with a 5-point Likert scale) were used in two stages. The statistical population in the second stage was 20 PhD graduates and subject specialists with more than 5 years of experience in the fields of knowledge management, technology management, and business. The snowball method was chosen and 10 of them responded to the questionnaire. In the third stage, in order to determine the priority and importance of the calculated components and indicators, a survey-analytical method was used. The statistical population of the research in the third stage was the number of 155 technology and knowledge brokers under the supervision of the Presidential Vice President for Science and Technology, Iran's National Fan Market and the Nano Technology Exchange Network, who were selected by census method.4. Results The results of data analysis show the number of 149 indicators under 30 components for Internet business for knowledge brokers in the form of nine components of Osterwalder's business model.5. Discussion The results show that knowledge brokers can create an information network between researchers by holding structured joint workshops in a client-oriented and problem-oriented manner, holding seminars and online webinars, etc., and establishing proper communication between the main customers of their business through virtual communication channels. Since the ultimate goal of designing a business model is to create sufficient value for customers, knowledge brokers can attract and retain their customers by providing value propositions such as facilitating decisions and policies through the acquired knowledge. Considering that every business model requires a number of key activities; knowledge brokers can provide their desired services to customers through key activities such as knowledge monitoring and evaluation, etc. One of the goals of every business and organization is to create partnerships with colleagues and key partners; based on this, knowledge brokers can achieve success in their business by establishing partnerships with influential investors, governmental and non-governmental supporting organizations, and influential governmental and non-governmental social organizations. The cost structure in any business is one of its main pillars and you should pay enough attention to its arrangement. This section usually contains two sections of fixed and variable costs. Knowledge brokers can manage the wages of human resources, administrative costs and provision of workplaces and the costs of providing equipment and depreciation in the fixed costs department and managing the wages of experts and researchers for sharing knowledge. Marketing, advertising and holding events and costs of development and maintenance of technology infrastructure in the variable costs department to achieve cost management in their business. The resources needed to run a successful business are called key resources. At first, it is believed that only the initial capital is enough to start a business, but the fact is that before starting any business, identifying key resources is of particular importance. Value proposition, communication with the customer, communication channels, how to communicate with the customer, making money, are all related to key resources. Knowledge brokers can start and maintain their business through key resources such as human, financial, physical and intellectual resources. In order to obtain profit, expenses must be deducted from income. In a business, if we consider the customer part as its heart, the income streams are the arteries of a business. Knowledge brokers through a variety of income models such as receiving commissions/fees from communicating between users and knowledge producers, advertising and receiving charges or royalties in providing consulting services and pricing mechanisms such as considering a base price for knowledge services, price dynamics based on the level of knowledge used and price dynamics based on advertisements, they can manage their business income flow.6. Conclusion Since every business needs components and indicators to be implemented in the form of a business model, it shows the architecture of a company to create, market, deliver value and earn a stable and profitable income; statistics of internet business components and indicators for knowledge brokers can help to reduce the information gap between researchers, policymakers and decision-makers, governance structures and institutions and supply and demand sector structures and institutions and lead to an increase in interest and be successful in business.

France Sandra, Zakrizevska-Belogrudova Maija, Rutka Lucija

The aim of the research is to study and clarify the level of professional burnout, personality traits, their interrelationships, and the impact of personality traits on professional burnout in the advertising industry to make recommendations to advertising company managers.

Mengyun Shi, Claire Cardie, Serge Belongie

Consumers are exposed to advertisements across many different domains on the internet, such as fashion, beauty, car, food, and others. On the other hand, fashion represents second highest e-commerce shopping category. Does consumer digital record behavior on various fashion ad images reveal their fashion taste? Does ads from other domains infer their fashion taste as well? In this paper, we study the correlation between advertisements and fashion taste. Towards this goal, we introduce a new dataset, Fashionpedia-Ads, which asks subjects to provide their preferences on both ad (fashion, beauty, car, and dessert) and fashion product (social network and e-commerce style) images. Furthermore, we exhaustively collect and annotate the emotional, visual and textual information on the ad images from multi-perspectives (abstractive level, physical level, captions, and brands). We open-source Fashionpedia-Ads to enable future studies and encourage more approaches to interpretability research between advertisements and fashion taste.

Yohay Kaplan, Naama Krasne, Alex Shtoff et al.

Verizon Media (VZM) native advertising is one of VZM largest and fastest growing businesses, reaching a run-rate of several hundred million USDs in the past year. Driving the VZM native models that are used to predict event probabilities, such as click and conversion probabilities, is OFFSET - a feature enhanced collaborative-filtering based event-prediction algorithm. In this work we focus on the challenge of predicting click-through rates (CTR) when we are aware that some of the clicks have short dwell-time and are defined as accidental clicks. An accidental click implies little affinity between the user and the ad, so predicting that similar users will click on the ad is inaccurate. Therefore, it may be beneficial to remove clicks with dwell-time lower than a predefined threshold from the training set. However, we cannot ignore these positive events, as filtering these will cause the model to under predict. Previous approaches have tried to apply filtering and then adding corrective biases to the CTR predictions, but did not yield revenue lifts and therefore were not adopted. In this work, we present a new approach where the positive weight of the accidental clicks is distributed among all of the negative events (skips), based on their likelihood of causing accidental clicks, as predicted by an auxiliary model. These likelihoods are taken as the correct labels of the negative events, shifting our training from using only binary labels and adopting a binary cross-entropy loss function in our training process. After showing offline performance improvements, the modified model was tested online serving VZM native users, and provided 1.18% revenue lift over the production model which is agnostic to accidental clicks.

Hutnyk Liudmyla

The goal of the research. Introduction into scientific circulation of printed film posters from collection of the Fine Arts Department of the Institute of Book Studies of the V. I. Vernadskyi National Library of Ukraine as visual information sources for studying the Ukrainian-Polish cultural relations of the 1960s-1980s. Methodology. The method of systematization was used to work out the collection of polonika in the fond of Ukrainian printed film posters of the V. I. Vernadskyi National Library of Ukraine. The historical and cultural method is used to study the history of the Polish cinema, the activities of film organizations and joint projects of Polish filmmakers in cooperation with artists from other countries. Art criticism analysis is used for figurative and stylistic characteristics of film posters dedicated to the Polish cinema. Scientific novelty. Separated from the collection of Ukrainian printed film posters of the Fine Arts Department of the Institute of Book Studies of the V. I. Vernadskyi National Library of Ukraine, collection of posters on the Polish subjects, for the first time, became the object of study in the context of studies of the existence of the Polish cinema in the second half of the 1950s - early 1980s in Ukraine. Conclusions. A remarkable revival of the Soviet-Polish cultural cooperation in the early 1960s and the active arrival of new Polish films in Ukrainian distribution led to the emergence of such a phenomenal phenomenon as polonika in domestic printed film posters. Posters made by Ukrainian artists in the second half of the 20th century are now perceived as peculiar artifacts, original sheets of fine publications on the history of the Polish cinema art of the corresponding period, as documentary sources of cinematographic biographies and national film production in Poland. They represent a wide genre and thematic direction of Polish films advertised and promoted in Ukraine in the late 1950s - early 1980s and at the same time are important visual and informational sources for the study of the Ukrainian-Polish cultural and artistic relations. A detailed analysis of individual samples of film posters clearly demonstrates the specifics of this type of poster graphics and illustrates the peculiarities of creative experiments of Ukrainian artists in artistic advertising of Polish films.

Ankit Gangwal, Shubham Singh, Riccardo Spolaor et al.

Bluetooth technology has enabled short-range wireless communication for billions of devices. Bluetooth Low-Energy (BLE) variant aims at improving power consumption on battery-constrained devices. BLE-enabled devices broadcast information (e.g., as beacons) to nearby devices via advertisements. Unfortunately, such functionality can become a double-edged sword at the hands of attackers. In this paper, we primarily show how an attacker can exploit BLE advertisements to exfiltrate information from BLE-enable devices. In particular, our attack establishes a communication medium between two devices without requiring any prior authentication or pairing. We develop a proof-of-concept attack framework on the Android ecosystem and assess its performance via a thorough set of experiments. Our results indicate that such an exfiltration attack is indeed possible though with a limited data rate. Nevertheless, we also demonstrate potential use cases and enhancements to our attack that can further its severeness. Finally, we discuss possible countermeasures to prevent such an attack.

Anna Pillar, Kyrill Poelmans, Martha Larson

Deep learning holds great promise for detecting discriminatory language in the public sphere. However, for the detection of illegal age discrimination in job advertisements, regex approaches are still strong performers. In this paper, we investigate job advertisements in the Netherlands. We present a qualitative analysis of the benefits of the 'old' approach based on regexes and investigate how neural embeddings could address its limitations.

Hauke Petersen, János Brodbeck, Thomas C. Schmidt et al.

The IPv6 over Bluetooth Low Energy (BLE) standard defines the transfer of IP data via BLE connections. This connection-oriented approach provides high reliability but increases packet delays and requires substantial overhead to manage BLE connections. To overcome these drawbacks we present the design and implementation of IPv6 over BLE advertisements, a standard-compliant connection-less approach. We deploy our proposal on low-power IoT hardware and comparatively measure key network performance metrics in a public testbed. Our results show that IP over BLE advertisements offers network performance characteristics complementary to IP over connection-based BLE, trading lower reliability for shorter~latency.

Alexandra Iacob, Bogdan Cautis, Silviu Maniu

Motivated by scenarios of information diffusion and advertising in social media, we study an influence maximization problem in which little is assumed to be known about the diffusion network or about the model that determines how information may propagate. In such a highly uncertain environment, one can focus on multi-round diffusion campaigns, with the objective to maximize the number of distinct users that are influenced or activated, starting from a known base of few influential nodes. During a campaign, spread seeds are selected sequentially at consecutive rounds, and feedback is collected in the form of the activated nodes at each round. A round's impact (reward) is then quantified as the number of newly activated nodes. Overall, one must maximize the campaign's total spread, as the sum of rounds' rewards. In this setting, an explore-exploit approach could be used to learn the key underlying diffusion parameters, while running the campaign. We describe and compare two methods of contextual multi-armed bandits, with upper-confidence bounds on the remaining potential of influencers, one using a generalized linear model and the Good-Turing estimator for remaining potential (GLM-GT-UCB), and another one that directly adapts the LinUCB algorithm to our setting (LogNorm-LinUCB). We show that they outperform baseline methods using state-of-the-art ideas, on synthetic and real-world data, while at the same time exhibiting different and complementary behavior, depending on the scenarios in which they are deployed.

Ehsan Nowroozi, Abhishek, Mohammadreza Mohammadi et al.

Malicious advertisement URLs pose a security risk since they are the source of cyber-attacks, and the need to address this issue is growing in both industry and academia. Generally, the attacker delivers an attack vector to the user by means of an email, an advertisement link or any other means of communication and directs them to a malicious website to steal sensitive information and to defraud them. Existing malicious URL detection techniques are limited and to handle unseen features as well as generalize to test data. In this study, we extract a novel set of lexical and web-scrapped features and employ machine learning technique to set up system for fraudulent advertisement URLs detection. The combination set of six different kinds of features precisely overcome the obfuscation in fraudulent URL classification. Based on different statistical properties, we use twelve different formatted datasets for detection, prediction and classification task. We extend our prediction analysis for mismatched and unlabelled datasets. For this framework, we analyze the performance of four machine learning techniques: Random Forest, Gradient Boost, XGBoost and AdaBoost in the detection part. With our proposed method, we can achieve a false negative rate as low as 0.0037 while maintaining high accuracy of 99.63%. Moreover, we devise a novel unsupervised technique for data clustering using K- Means algorithm for the visual analysis. This paper analyses the vulnerability of decision tree-based models using the limited knowledge attack scenario. We considered the exploratory attack and implemented Zeroth Order Optimization adversarial attack on the detection models.

Ujun Jeong, Kaize Ding, Huan Liu

The growing use of social media has led to drastic changes in our decision-making. Especially, Facebook offers marketing API which promotes business to target potential groups who are likely to consume their items. However, this service can be abused by malicious advertisers who attempt to deceive people by disinformation such as propaganda and divisive opinion. To counter this problem, we introduce a new application named FBAdTracker. The purpose of this application is to provide an integrated data collection and analysis system for current research on fact-checking related to Facebook advertisements. Our system is capable of monitoring up-to-date Facebook ads and analyzing ads retrieved from Facebook Ads Library.