Beijing Language and Culture University
Beijing, China

Beijing Language and Culture University , colloquially known in Chinese as Yuyan Xueyuan , has the main aim of teaching the Chinese language and culture to foreign students. However, it also takes Chinese students specializing in foreign languages and other relevant subjects of humanities and social science, and trains teachers of Chinese as a foreign language. It used to be the only institute of this kind in China. After the push for massification of higher education starting in the 90's, nowadays many other universities in almost every major city in China have a similar offer. Thus bachelor, master or post-doc degrees in, "Teaching Chinese to Foreigners", as well as bachelor and master degrees in several foreign languages are no longer only to be found at BLCU. Beijing Language and Culture University is often called "Little United Nations" in China because of its very large amount of international students from various countries. Wikipedia.

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Huang Y.,Beijing Language and Culture University
Intelligent Data Analysis | Year: 2017

Mining richly structured heterogeneous datasets represents a key emerging challenge for data mining. When traditional clustering methods are applied, heterogeneous networks consisting of multiple entities must first be converted to homogeneous networks consisting of entities of only one type, causing information loss. This paper proposes a three-phase general framework to directly handle the information contained in extended star-structured heterogeneous data. First, entity resolution of objects of all types is conducted based on their attribute values. Then, central objects are clustered in terms of their relation strengths. Finally, groups of attribute objects are detected according to the clustering assignment of their connected central objects. A numerical example is provided to illustrate the modeling idea and working principle of the proposed method, and experiments on a real-world dataset show the effectiveness of the three proposed algorithms. © 2017 - IOS Press and the authors. All rights reserved.

Sun L.,Beijing Language and Culture University
International Conference on Signal Processing Proceedings, ICSP | Year: 2017

Given object instances belonging to the same class, a novel topic model is proposes to learn the part-based object model by a semi-supervised manner. The proposed model, called segment-layout topic model, automatically partitions the instances into several subclasses, discovers the component segments in each instance as the possible parts, and learns the part-based model for each subclass. Unlike the defined parts by high-level object knowledge, the segments focus on the low-level visual features and are easier to be found from the object instances. An iterative process is further proposed to implement model learning. Finally, the proposed method is examined by the experiment of object detection, and is compared with other supervised or semi-supervised methods. © 2016 IEEE.

Wang L.,Beijing Language and Culture University
CIE 2016: 46th International Conferences on Computers and Industrial Engineering | Year: 2016

Alliance and partner-like relationship have continued to become more and more popular across a broader boundary spanning of firms, industries and nationalities in the environment of increasing globalization and the demands of a networked, fast-paced economy. More and more companies depend on the complimentary resources and capability in the supply chain network to enhance their innovation competence. This article summarized different view inter-firm relationship and its impact on performance. Based on the case analysis of Company A, this article reveals how to integrate recourses in the business ecosystem to realize localized researching of production equipment.

Liu G.,Beijing Language and Culture University
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2017

Assignment reduction is a special reduction type of attribute reduction. It is first studied in decision tables and the reduction approaches are then extended to ordered decision systems. This paper continues to consider such a reduction type in relation decision systems. We propose a new discernibility matrix. Based on the matrix, we give the corresponding reduction algorithm. As special case, we derive respectively the assignment reduction algorithms for decision tables and ordered decision systems. © Springer International Publishing AG 2017.

Liu G.,Beijing Language and Culture University | Zhu K.,Beijing Language and Culture University
Knowledge-Based Systems | Year: 2014

The aim of the paper is to clarify mathematical relationship among three types of rough approximation pairs. We propose subsystem-based definition of generalized rough sets and consider three different types of generalized rough approximation pairs from the viewpoint of three definitions, namely, the element, granule, and subsystem-based definitions. This paper investigates these three types of generalized rough sets with respect to arbitrary binary relations. The topologies induced by granule-based generalized rough sets are introduced. Finally, we give a characterization of granule-based generalized rough sets. © 2014 Elsevier B.V. All rights reserved.

Liu G.,Beijing Language and Culture University
Knowledge-Based Systems | Year: 2010

For two universal sets U and V, we define the concept of solitary set for any binary relation from U to V. Through the solitary sets, we study the further properties that are interesting and valuable in the theory of rough sets. As an application of crisp rough set models in two universal sets, we find solutions of the simultaneous Boolean equations by means of rough set methods. We also study the connection between rough set theory and Dempster-Shafer theory of evidence. In particular, we extend some results to arbitrary binary relations on two universal sets, not just serial binary relations. We consider the similar problems in fuzzy environment and give an example of application of fuzzy rough sets in multiple criteria decision making in the case of clothes. © 2009 Elsevier B.V. All rights reserved.

Liu G.,Beijing Language and Culture University
Information Sciences | Year: 2013

This paper studies covering-based rough sets by means of characteristic functions of sets. We consider covering-based rough sets from both constructive and axiomatic approaches. The relationship among four types of covering-based rough sets is discussed. We also outline the topologies induced by different covering approximations. © 2013 Elsevier Inc. All rights reserved.

Liu G.,Beijing Language and Culture University
Information Sciences | Year: 2013

Axiomatic approaches are important for understanding the concepts of rough set theory. The properties of the approximation operators constructed in rough set theory are determined by a binary relation. A linkage, in the form of a necessary and sufficient condition, between the constructive approach and an axiomatic system is established in this paper. Various classes of rough set algebras are characterized by different sets of axioms. With no restriction on the cardinality of the universal set, we use only one axiom to describe the approximation generated by the reflexive, symmetric, and transitive relations, respectively. In addition, we characterize lower and upper approximations of the Pawlak rough set with only one axiom. We also study a similar problem in the context of fuzzy sets. © 2012 Elsevier Inc. All rights reserved.

Liu G.,Beijing Language and Culture University | Sai Y.,Shandong University of Finance and Economics
Information Sciences | Year: 2010

This paper studies the classes of rough sets and fuzzy rough sets. We discuss the invertible lower and upper approximations and present the necessary and sufficient conditions for the lower approximation to coincide with the upper approximation in both rough sets and fuzzy rough sets. We also study the mathematical properties of a fuzzy rough set induced by a cyclic fuzzy relation. © 2010 Elsevier Inc. All rights reserved.

News Article | February 23, 2017

​​Welocalize, global leader in innovative translation and localization solutions, is a sponsor and exhibitor at the upcoming Localization World 2017 conference taking place at Marco Polo Shenzhen, Shenzhen, China on February 28 – March 02, 2017. Welocalize executives and localization experts will be on hand at booth #14 in the main exhibit space. The Welocalize team will host a series of discussions supporting the LocWorld33 theme of “Continuous Delivery” with emphasis on how global brands and local Asian companies can develop scalable language strategies to grow globally and reach new cultural markets. “Asia is a very important market to Welocalize and as sponsors and exhibitors of Localization World 2017 Shenzhen, we look forward to meeting with new and existing clients and learning about their global challenges and opportunities,” said Erin Wynn, chief customer officer at Welocalize. “We bring a broad range of services in support of the customer journey from patent translations through digital marketing and social media campaigns. It is this experience and expertise that puts us at the forefront of any discussion relating to globalization and localization.” Welocalize will participate in the preconference session, “Attracting and Developing Talent: A LocWorld Initiative” on February 28. The session focuses on the challenges of educating professionally trained staff in localization to address the talent shortage facing the industry. Welocalize Business Development Manager Ann Chen will join presenters from Beijing Language and Culture University and Larsen Globalization Ltd. Welocalize will also host the exclusive LocLeaders Forum 2017 Asia on February 28 at the Four Seasons Hotel in Shenzhen. This hosted dinner and special panel discussion is a unique opportunity for clients and localization professionals to participate in open discussion on the latest trends in globalization including go-to-market strategies, language quality, machine translation, post-editing, talent, software localization and developing multilingual digital marketing campaigns. Olga Beregovaya, language automation expert and VP of Technology Solutions at Welocalize will moderate a discussion with guest panelists on the topic of localization engagement models, including expert insights into the latest technological innovations. For more information and to register for LocLeaders Shenzhen, visit For more information about Localization World Shenzhen 2017, visit Welocalize, Inc., founded in 1997, offers innovative language services to help global brands reach audiences around the world in more than 175 languages. We provide translation and localization services, talent management, language tools, automation and technology, quality and program management. Our range of managed language services include machine translation, digital marketing, validation and testing, interpretation, staffing and enterprise translation management technologies. We specialize in consumer, technology, manufacturing, learning, oil and gas, travel and hospitality, marketing and advertising, finance, legal and life sciences industry language solutions. With more than 1000 full-time employees worldwide, Welocalize maintains offices in the United States, United Kingdom, Germany, Ireland, Spain, Italy, Romania, Poland, Japan and China.

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