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摘要： The month’s sharpest science shots, selected byNature’s photo team.

关键词： accounting   artificial intelligence   business   business consultancy   computer science   consulting   consumer services   corporate   general news   human resources consulting   humanities   Humu   industrial news   internet search engines   labor   Laszlo Bock   machine learning   online service providers   personnel   political   sciences   technology  

关键词： accounting   artificial intelligence   business   business consultancy   computer science   consulting   consumer services   corporate   general news   human resources consulting   humanities   Humu   industrial news   internet search engines   labor   Laszlo Bock   machine learning   online service providers   personnel   political   sciences   technology  

关键词： 生态话语分析   特朗普就职演说   国际关系   国际生态意义  

摘要： 2017年,美国第45任总统特朗普于华盛顿发表就职演说。其演说作为一种国际话语不仅影响着美国民众的认知,同时也在塑造着美国的外交国际关系。文章在及物性系统下对特朗普就职演说进行生态话语分析,挖掘其隐含的意识形态,并揭示其国际生态意义。

关键词： 非洲留学生   计算机科学与技术   人才培养  

摘要： 随着“一带一路”倡议的推进,来华学习计算机科学与技术专业的非洲留学生数量呈现上升趋势。通过分析非洲留学生的状况特点,提出了一套与之相适应的人才培养模式。以培养实践应用型人才为目标,采用分层次教学的形式因材施教,强化案例教学提升授课质量,设置专业导师制引导中非学生互利互助。实践证明该模式可提升国际化计算机科学与技术专业非洲本土人才的培养质量。

关键词： Logic gates   Computer science   Electronic mail   Feature extraction   Knowledge based systems   Medical diagnosis   Resource description framework   Knowledge base   KB integration   instance alignment   ontology matching   entity resolution   interpretability  

摘要： Over the past few years, knowledge bases (KBs) like DBPedia, Freebase, and YAGO have accumulated a massive amount of knowledge from web data. Despite their seemingly large size, however, individual KBs often lack comprehensive information on any given domain. For example, over 70 percent of people on Freebase lack information on place of birth. For this reason, the complementary nature across different KBs motivates their integration through a process of aligning instances. Meanwhile, since application-level machine systems, such as medical diagnosis, have heavily relied on KBs, it is necessary to provide users with trustworthy reasons why the alignment decisions are made. To address this problem, we propose a new paradigm, explainable instance alignment (XINA), which provides user-understandable explanations for alignment decisions. Specifically, given an alignment candidate, XINA replaces existing scalar representation of an aggregated score, by decision- and explanation-vector spaces for machine decision and user understanding, respectively. To validate XINA, we perform extensive experiments on real-world KBs and show that XINA achieves comparable performance with state-of-the-arts, even with far less human effort.

关键词： 信息时代   计算机科学技术   应用  

摘要： 随着信息全球化的快速发展,人们的生活和工作越来越智能化。其中,计算机科学技术在现代社会的生产和生活中占有非常重要的地位,公众的学习和生活与计算机科学技术密不可分。文章阐述了计算机科学技术的发展历史和发展特点,对于计算机科学技术在信息时代的发展战略进行了重点分析,并对计算机科学技术在各领域的应用展开了有效讨论,目的是促进信息技术和计算机科学技术更好更快的发展。

关键词： Predictive models   Data models   Measurement   Microsoft Windows   Advertising   Tools   Computer science   Retargeting   conversion prediction   predictability   market model   digital marketing   E-commerce  

摘要： As 98 percent of shoppers do not make a purchase on the first visit, we study the problem of predicting whether they would come back for a purchase later (i.e., conversion prediction). This problem is important for strategizing "retargeting", for example, by sending coupons for customers who are likely to convert. For this goal, we study the following two problems, prediction of market and predictability of customer. First, prediction of market aims at identifying a conversion rate for a given product and its customer behavior modeling, which is an important analytics metric for retargeting process. Compared to existing approaches using either of customer or product-level conversion pattern, we propose a joint modeling of both patterns based on the well-studied buying decision process. Second, we can observe customer-specific behaviors after showing retargeting ads, to predict whether this specific customer follows the market model (high predictability) or not (low predictability). For the former, we apply the market model, and for the latter, we propose a new customer-specific prediction based on dynamic ad behavior features. To evaluate the effectiveness of our methods, we perform extensive experiments on the simulated dataset generated based on a set of real-world web logs and retargeting campaign logs. The evaluation results show that conversion predictions and predictability by our approach are consistently more accurate and robust than those by existing baselines in dynamic market environment.