As a leading form of intellectual property, patents undergird our knowledge economy. The products with a high and multisourced content, such as smartphones, can touch hundreds of thousands of patents, directly or indirectly. Having a viable market for patent trading is, therefore, essential. It is also difficult, owing to the many facets the patents and their limitations have and to the frequently nontransparent descriptions of these. Patent recommenders are in order, if only to help buyers identify patterns relevant to their pursuits. In the opening paper of this issue, Qi Wang, Wei Du, Jian Ma, and Xiuwu Liao present a novel design of such a recommendation mechanism. It is grounded in the heterogeneous information networks, suitable for representing a rich semantics of objects and their interrelationships. These allow mining the implicit relationships among patents based on the expressive real-world context and patent content represented by such networks. Such design offers major advantages over the prior art in patent recommenders, as shown by the authors’ experiments. These recommenders would make a valuable front end to the patent trading platforms. Two subsequent papers in the issue deal with social networking sites (SNS). Ashish Kumar, Jari Salo, and Hongxiu Li present a study of social commerce platforms grafted on an SNS. User engagement is the key to success here, and it is the subject of the authors’ research. The authors identify four stages of users’ interaction with such a platform and measure the users’ engagement in each of these, using clickstream data. They are able to model the antecedents of the engagement on each stage, which leads to the recommendations that the authors are able to offer to the operators of the increasingly used social commerce platforms. The commercial aspect of SNS is also the research target in the next paper, by Freya De Keyzer, Nathalie Dens, and Patrick De Pelsmacker. These researchers study the differential effects of electronic word-of-mouth (eWOM), such as consumer reviews and product-related messages, in the SNS context. More specifically, the authors aim to determine how the relationships among the consumers active on an SNS, and the consumers’ relationship to the site, impact the effect of the eWOM. The specific preconditions for effective eWOM in the SNS context are identified, and the recommendations for the platforms follow. Taken together with the preceding paper, we have an aggregate contribution to our knowledge of social commerce. Medical services inexorably see the growth of their online consultation component, out of necessity, out of the inherent advantages to patients (who do not have to be patient in seeking the doctor’s advice in an office setting), and out of the opportunity to the physicians. The last aspect is the focus on the next paper, by Jia Li, Jie Tang, Ling Jiang, David C. Yen, and Xuan Liu. The researchers deploy the focus of signaling theory as well as use econometric analysis to seek out the antecedents to the physicians’ economic success in the e-consultation market. The research is deepened by the inclusion of both the online and offline reputation signals and by the consideration of the interaction among several types of signals. With all the

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编者介绍

作为知识产权的主要形式，专利支撑着我们的知识经济。智能手机等内容多、内容多的产品，可以直接或间接触及数十万项专利。因此，拥有一个可行的专利交易市场至关重要。由于专利及其局限性的许多方面以及对这些方面的经常不透明的描述，这也很困难。专利推荐人是为了帮助买家识别与他们的追求相关的模式。在本期的开篇论文中，王琦、杜威、马健和廖修武提出了这种推荐机制的新颖设计。它基于异构信息网络，适合表示对象及其相互关系的丰富语义。这些允许基于此类网络所代表的富有表现力的现实世界上下文和专利内容来挖掘专利之间的隐含关系。如作者的实验所示，这种设计在专利推荐器中提供了优于现有技术的主要优势。这些推荐人将成为专利交易平台的宝贵前端。该问题的后续两篇论文涉及社交网站 (SNS)。Ashish Kumar、Jari Salo 和 Hongxiu Li 展示了一项关于嫁接在 SNS 上的社交商务平台的研究。用户参与是这里成功的关键，也是作者研究的主题。作者确定了用户与此类平台交互的四个阶段，并使用点击流数据衡量用户在每个阶段的参与度。他们能够模拟每个阶段参与的前因，这导致了作者能够向越来越多地使用的社交商务平台的运营商提供的建议。SNS 的商业方面也是 Freya De Keyzer、Nathalie Dens 和 Patrick De Pelsmacker 的下一篇论文的研究目标。这些研究人员研究了电子口碑 (eWOM) 在 SNS 环境中的不同影响，例如消费者评论和产品相关信息。更具体地说，作者旨在确定活跃在 SNS 上的消费者之间的关系以及消费者与网站的关系如何影响 eWOM 的效果。确定了在 SNS 上下文中有效 eWOM 的特定先决条件，然后对平台提出了建议。结合前面的论文，我们对社交商务知识做出了综合贡献。医疗服务无情地看到他们的在线咨询组件的增长，出于必要，出于对患者的固有优势（他们不必在办公室环境中耐心寻求医生的建议），并且出于医生的机会. 最后一个方面是下一篇论文的重点，作者是 Jia Li、Jie Tang、Ling Jiang、David C. Yen 和 Xuan Liu。研究人员部署了信号理论的重点，并使用计量经济学分析来寻找医生在电子咨询市场上取得经济成功的先决条件。通过包含在线和离线声誉信号以及考虑几种类型信号之间的相互作用，该研究得到了深化。随着所有 医疗服务无情地看到他们的在线咨询组件的增长，出于必要，出于对患者的固有优势（他们不必在办公室环境中耐心寻求医生的建议），并且出于医生的机会. 最后一个方面是下一篇论文的重点，作者是 Jia Li、Jie Tang、Ling Jiang、David C. Yen 和 Xuan Liu。研究人员部署了信号理论的重点，并使用计量经济学分析来寻找医生在电子咨询市场上取得经济成功的先决条件。通过包含在线和离线声誉信号以及考虑几种类型信号之间的相互作用，该研究得到了深化。随着所有 医疗服务无情地看到他们的在线咨询组件的增长，出于必要，出于对患者的固有优势（他们不必在办公室环境中耐心寻求医生的建议），并且出于医生的机会. 最后一个方面是下一篇论文的重点，作者是 Jia Li、Jie Tang、Ling Jiang、David C. Yen 和 Xuan Liu。研究人员部署了信号理论的重点，并使用计量经济学分析来寻找医生在电子咨询市场上取得经济成功的先决条件。通过包含在线和离线声誉信号以及考虑几种类型信号之间的相互作用，该研究得到了深化。随着所有 出于对患者（在办公室环境中寻求医生建议时不必耐心）的固有优势，以及对医生的机会。最后一个方面是下一篇论文的重点，作者是 Jia Li、Jie Tang、Ling Jiang、David C. Yen 和 Xuan Liu。研究人员部署了信号理论的重点，并使用计量经济学分析来寻找医生在电子咨询市场上取得经济成功的先决条件。通过包含在线和离线声誉信号以及考虑几种类型信号之间的相互作用，该研究得到了深化。随着所有 出于对患者（在办公室环境中寻求医生建议时不必耐心）的固有优势，以及对医生的机会。最后一个方面是下一篇论文的重点，作者是 Jia Li、Jie Tang、Ling Jiang、David C. Yen 和 Xuan Liu。研究人员部署了信号理论的重点，并使用计量经济学分析来寻找医生在电子咨询市场上取得经济成功的先决条件。通过包含在线和离线声誉信号以及考虑几种类型信号之间的相互作用，该研究得到了深化。随着所有 David C. Yen 和刘轩。研究人员部署了信号理论的重点，并使用计量经济学分析来寻找医生在电子咨询市场上取得经济成功的先决条件。通过包含在线和离线声誉信号以及考虑几种类型信号之间的相互作用，该研究得到了深化。随着所有 David C. Yen 和刘轩。研究人员部署了信号理论的重点，并使用计量经济学分析来寻找医生在电子咨询市场上取得经济成功的先决条件。通过包含在线和离线声誉信号以及考虑几种类型信号之间的相互作用，该研究得到了深化。随着所有