Category-Specific CNN for Visual-aware CTR Prediction at JD.com

As one of the largest B2C e-commerce platforms in China, JD com also powers a leading advertising system, serving millions of advertisers with fingertip connection to hundreds of millions of customers. In our system, as well as most e-commerce scenarios, ads are displayed with images.This makes visual-aware Click Through Rate (CTR) prediction of crucial importance to both business effectiveness and user experience. Existing algorithms usually extract visual features using off-the-shelf Convolutional Neural Networks (CNNs) and late fuse the visual and non-visual features for the finally predicted CTR. Despite being extensively studied, this field still face two key challenges. First, although encouraging progress has been made in offline studies, applying CNNs in real systems remains non-trivial, due to the strict requirements for efficient end-to-end training and low-latency online serving. Second, the off-the-shelf CNNs and late fusion architectures are suboptimal. Specifically, off-the-shelf CNNs were designed for classification thus never take categories as input features. While in e-commerce, categories are precisely labeled and contain abundant visual priors that will help the visual modeling. Unaware of the ad category, these CNNs may extract some unnecessary category-unrelated features, wasting CNN's limited expression ability. To overcome the two challenges, we propose Category-specific CNN (CSCNN) specially for CTR prediction. CSCNN early incorporates the category knowledge with a light-weighted attention-module on each convolutional layer. This enables CSCNN to extract expressive category-specific visual patterns that benefit the CTR prediction. Offline experiments on benchmark and a 10 billion scale real production dataset from JD, together with an Online A/B test show that CSCNN outperforms all compared state-of-the-art algorithms

Analyzing Granger causality in climate data with time series classification methods

Attribution studies in climate science aim for scientifically ascertaining the influence of climatic variations on natural or anthropogenic factors. Many of those studies adopt the concept of Granger causality to infer statistical cause-effect relationships, while utilizing traditional autoregressive models. In this article, we investigate the potential of state-of-the-art time series classification techniques to enhance causal inference in climate science. We conduct a comparative experimental study of different types of algorithms on a large test suite that comprises a unique collection of datasets from the area of climate-vegetation dynamics. The results indicate that specialized time series classification methods are able to improve existing inference procedures. Substantial differences are observed among the methods that were tested

KEER2022

Avanttítol: KEER2022. DiversitiesDescripció del recurs: 25 juliol 202

Can Upward Brand Extensions be an Opportunity for Marketing Managers During the Covid-19 Pandemic and Beyond?

Early COVID-19 research has guided current managerial practice by introducing more products across different product categories as consumers tried to avoid perceived health risks from food shortages, i.e. horizontal brand extensions. For example, Leon, a fast-food restaurant in the UK, introduced a new range of ready meal products. However, when the food supply stabilised, availability may no longer be a concern for consumers. Instead, job losses could be a driver of higher perceived financial risks. Meanwhile, it remains unknown whether the perceived health or financial risks play a more significant role on consumers’ consumptions. Our preliminary survey shows perceived health risks outperform perceived financial risks to positively influence purchase intention during COVID-19. We suggest such a result indicates an opportunity for marketers to consider introducing premium priced products, i.e. upward brand extensions. The risk-as�feelings and signalling theories were used to explain consumer choice under risk may adopt affective heuristic processing, using minimal cognitive efforts to evaluate products. Based on this, consumers are likely to be affected by the salient high-quality and reliable product cue of upward extension signalled by its premium price level, which may attract consumers to purchase when they have high perceived health risks associated with COVID-19. Addressing this, a series of experimental studies confirm that upward brand extensions (versus normal new product introductions) can positively moderate the positive effect between perceived health risks associated with COVID-19 and purchase intention. Such an effect can be mediated by affective heuristic information processing. The results contribute to emergent COVID-19 literature and managerial practice during the pandemic but could also inform post-pandemic thinking around vertical brand extensions

Behind the search box: the political economy of a global Internet industry

With the rapid proliferation of the Web, the search engine constituted an increasingly vital tool in everyday life, and offered technical capabilities that might have lent themselves under different circumstances to a sweeping democratization of information provision and access. Instead the search function was transformed into the most profitable large-scale global information industry. This dissertation examines the evolution of search engine technologies within the context of the commercialization and commodification of the Internet. Grounded in critical political economy, the research details how capital has progressively shifted information search activities further into the market, transforming them into sites of profit-making and poles of capitalist growth. It applies historical and political economic analysis by resorting to an extensive array of sources including trade journals, government documents, industry reports, and financial and business newspapers. The first chapter situates the development of the search engine within the wider political economy of the Internet industry. The second shows how the technology of search was reorganized to enable profitable accumulation. The third and fourth chapters focus on another primary concern of political economy: the labor structures and labor processes that typify this emergent industry. These pivot around familiar compulsions: profit-maximization and management control. The search industry is famous for the almost incredible perks it affords to a select group of highly paid, highly skilled engineers and managers. However, the same industry also relies not only a large number of low-wage workers but also an unprecedented mass of unwaged labor. Google and other search engines also have found means of re-constructing the practices of a seemingly bygone industrial era of labor control: corporate paternalism and scientific management. Today, the search engine industry sits at the “magnetic north pole” of economic growth – the Internet. This vital function of search is controlled disproportionately by US digital capital, mainly Google. US dominance in search seems to carry forward the existing, deeply unbalanced, international information order; however, this US-led industry actually faces jarring oppositions within a changing and conflicted global political economy. Chapter Five investigates two of the most important and contested zones: China, whose economic growth has been unsurpassed throughout the entire period spanned by this study of the search engine’s development, and which has nurtured a highly successful domestic Internet industry, including a search engine company, Baidu; and Europe, US’s long-time ally, where units of capital both European and non-European are struggling with one another. By situating search within these contexts, this chapter sheds light on the ongoing reconfiguration of international information services, and on the geopolitical-economic conflicts that are altering the dynamics of information-intensive transnational capitalism. There is a well-developed critical scholarship in political economy that foregrounds the role of information in contemporary capitalist development. This dissertation contributes to and expands this research by looking at search to uncover the capital logics that undergird and shape contemporary information provision