Towards Knowledge-Based Personalized Product Description Generation in E-commerce

Quality product descriptions are critical for providing competitive customer experience in an e-commerce platform. An accurate and attractive description not only helps customers make an informed decision but also improves the likelihood of purchase. However, crafting a successful product description is tedious and highly time-consuming. Due to its importance, automating the product description generation has attracted considerable interests from both research and industrial communities. Existing methods mainly use templates or statistical methods, and their performance could be rather limited. In this paper, we explore a new way to generate the personalized product description by combining the power of neural networks and knowledge base. Specifically, we propose a KnOwledge Based pErsonalized (or KOBE) product description generation model in the context of e-commerce. In KOBE, we extend the encoder-decoder framework, the Transformer, to a sequence modeling formulation using self-attention. In order to make the description both informative and personalized, KOBE considers a variety of important factors during text generation, including product aspects, user categories, and knowledge base, etc. Experiments on real-world datasets demonstrate that the proposed method out-performs the baseline on various metrics. KOBE can achieve an improvement of 9.7% over state-of-the-arts in terms of BLEU. We also present several case studies as the anecdotal evidence to further prove the effectiveness of the proposed approach. The framework has been deployed in Taobao, the largest online e-commerce platform in China.Comment: KDD 2019 Camera-ready. Website: https://sites.google.com/view/kobe201

Religiosity, ethics and the spirit of capitalism in HRM

This chapter contributes to the debate on the extent to which religion and religiosity have had any effects on the management of people and employee relations in Asian countries and in particular in East Asia where there has been a revival of religious beliefs after many years of suppression on religious practices. The author observed that studies on the relationship between religious beliefs, organizational behavior, managerial practices and organizational outcomes are very limited and much of the debate over the rise of religiosity and spirituality as a form of personal identity has focused on the effects of religion at the national rather than the organizational and workplace level, and has been concerned with the negative aspects of religious extremism rather than on the positive implications of religious enlightenment on work and employee relations. This chapter addresses this imbalance and argues that the gap is still wider between the theory or what religious teachings promote and the reality or how people are managed in the workplace. The author provides emerging evidence that suggests that Asian ethical work behavior inspired by non-religious beliefs has had significant impact on HRM despite the spread of capitalism and the rise of religiosity, and calls for more empirical research on the topic to deepen our understanding

CHO microRNA engineering is growing up : recent successes and future challenges

microRNAs with their ability to regulate complex pathways that control cellular behavior and phenotype have been proposed as potential targets for cell engineering in the context of optimization of biopharmaceutical production cell lines, specifically of Chinese Hamster Ovary cells. However, until recently, research was limited by a lack of genomic sequence information on this industrially important cell line. With the publication of the genomic sequence and other relevant data sets for CHO cells since 2011, the doors have been opened for an improved understanding of CHO cell physiology and for the development of the necessary tools for novel engineering strategies. In the present review we discuss both knowledge on the regulatory mechanisms of microRNAs obtained from other biological models and proof of concepts already performed on CHO cells, thus providing an outlook of potential applications of microRNA engineering in production cell lines

Transferring Collective Knowledge: Collective and Fragmented Teaching and Learning in the Chinese Auto Industry

Collective knowledge, consisting of tacit group-embedded knowledge, is a key element of organizational capabilities. This study undertakes a multiple-case study of the transfer of collective knowledge, guided by a set of tentative constructs and propositions derived from organizational learning theory. By focusing on the group-embeddedness dimension of collective knowledge, we direct our attention to the source and recipient communities. We identify two sets of strategic choices concerning the transfer of collective knowledge: collective vs. fragmented teaching, and collective vs. fragmented learning. The empirical context of this study is international R&D capability transfer in the Chinese auto industry. From the case evidence, we find the expected benefits of collective teaching and collective learning, and also discover additional benefits of these two strategies, including the creation of a bridge network communication infrastructure. The study disclosed other conditions underlying the choice of strategies of transferring collective knowledge, including transfer effort and the level of group-embeddedness of the knowledge to be taught or re-embedded. The paper provides a group-level perspective in understanding organizational capabilities, as well as a set of refined constructs and propositions concerning strategic choices of transferring collective knowledge. The study also provides a rich description of the best practices and lessons learned in transferring organizational capabilities.http://deepblue.lib.umich.edu/bitstream/2027.42/39804/3/wp420.pd

Application of shape grammar theory to underground rail station design and passenger evacuation

This paper outlines the development of a computer design environment that generates station ‘reference’ plans for analysis by designers at the project feasibility stage. The developed program uses the theoretical concept of shape grammar, based upon principles of recognition and replacement of a particular shape to enable the generation of station layouts. The developed novel shape grammar rules produce multiple plans of accurately sized infrastructure faster than by traditional means. A finite set of station infrastructure elements and a finite set of connection possibilities for them, directed by regulations and the logical processes of station usage, allows for increasingly complex composite shapes to be automatically produced, some of which are credible station layouts at ‘reference’ block plan level. The proposed method of generating shape grammar plans is aligned to London Underground standards, in particular to the Station Planning Standards and Guidelines 5th edition (SPSG5 2007) and the BS-7974 fire safety engineering process. Quantitative testing is via existing evacuation modelling software. The prototype system, named SGEvac, has both the scope and potential for redevelopment to any other country’s design legislation

State-of-the-art in aerodynamic shape optimisation methods

Aerodynamic optimisation has become an indispensable component for any aerodynamic design over the past 60 years, with applications to aircraft, cars, trains, bridges, wind turbines, internal pipe flows, and cavities, among others, and is thus relevant in many facets of technology. With advancements in computational power, automated design optimisation procedures have become more competent, however, there is an ambiguity and bias throughout the literature with regards to relative performance of optimisation architectures and employed algorithms. This paper provides a well-balanced critical review of the dominant optimisation approaches that have been integrated with aerodynamic theory for the purpose of shape optimisation. A total of 229 papers, published in more than 120 journals and conference proceedings, have been classified into 6 different optimisation algorithm approaches. The material cited includes some of the most well-established authors and publications in the field of aerodynamic optimisation. This paper aims to eliminate bias toward certain algorithms by analysing the limitations, drawbacks, and the benefits of the most utilised optimisation approaches. This review provides comprehensive but straightforward insight for non-specialists and reference detailing the current state for specialist practitioners