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KD-TSS: Accurate Method for Private Spatial Decomposition JIN Kaizhong, ZHANG Xiaojian, PENG Huili Journal of Frontiers of Computer Science and Technology    2017, 11 (10): 1579-1590.   DOI: 10.3778/j.issn.1673-9418.1608040 KD-Tree-based differentially private spatial decomposition has attracted considerable research attention in recent years. The trade-off between the size of spatial data and Laplace noise directly constrains the accuracy of decomposition. This paper proposes a straightforward method with differential privacy, called SKD-TS (sampling-based KD-Tree) to partition spatial data. To handle the large-scale spatial data, this method employs Bernoulli random sampling technology to obtain the samples. While SKD-Tree still relies on the height of KD-Tree to control the Laplace noise. However, the choice of the height is a serious subtitle: a large height makes excessive noise in the nodes, while a small height leads to the partition too coarse-grained. To remedy the deficiency of SKD-Tree, this paper proposes another method, called KD-TSS (KD-Tree with sampling and SVT) for spatial decomposition. The sparse vector technology (SVT) is used in KD-TSS to judge whether a node of KD-Tree should be split, without depending on the height. SKD-TS and KD-TSS methods are compared with existing methods such as KD-Stand, KD-Hybird on the large-scale real datasets. The experimental results show that the two algorithms outperform their competitors, achieve the accurate decomposition and results of range query. Related Articles | Metrics

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A Survey on Question and Answering Systems MAO Xianling, LI Xiaoming Journal of Frontiers of Computer Science and Technology    2012, 6 (3): 193-207.   DOI: 10.3778/j.issn.1673-9418.2012.03.001 Recently, question and answering systems have attracted lots of attention. Given a question, the goal of question and answering is to return a concise, exact answer. According to the format of data, question and answering can be di-vided into three categories: the structural data based question and answering, the free-text based question and answering, the question-answer pairs based question and answering. This paper describes and summarizes the char-acteristics and related researches of these three categories respectively. Then, it discusses the future work of question and answering. Related Articles | Metrics

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Recommender System: Up to Now ZHU Yangyong, SUN Jing Journal of Frontiers of Computer Science and Technology    2015, 9 (5): 513-525.   DOI: 10.3778/j.issn.1673-9418.1412023 Recommender system is the product of cyber age today. There have been many achievements in research and application. This paper makes a comprehensive survey of the recommender system. It proposes three research phases, and points out the milestone events in each stage of recommender system development. In the age of big data, exploiting recommendation in the perspective of data, this paper classifies the recommender system into seven main classes according to the different data used in recommendation, and analyzes and comments the recommended models used in each classification and their advantages and disadvantages. Exploiting big data in the perspective of recommendation, this paper proposes that making recommendation based on big data is one of the promising research directions. Finally, this paper compares the evaluation metrics of recommendation, and gives future research directions. Related Articles | Metrics

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Quantum computing and quantum computers WU Nan,SONG Fang-min+ Journal of Frontiers of Computer Science and Technology    2007, 1 (1): 1-16.   As a new computing model，quantum computing can in principle exploit quantum mechanical effects to perform computations more rapidly than classical Turing Machine model based on the principles of quantum computing and some important quantum.Meanwhile，the physical implementations of quantum computer are also proposed.Optic photon quantum computer and quantum computer based on Nuclear Magnetic Resonance（NMR），ion traps or harmonic oscillator，etc.，have been realized one by one.Several quantum algorithms appear in recent years.A successful demonstration of Shor’s quantum algorithm is made by using a quantum computing device based on NMR in 2001，and it shows the quantum computer’s great potential power for processing complicated problems.Finally，the developments in the aspect of physical implementation of quantum computer are summarized． Related Articles | Metrics

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Brief Introduction to SMT Solving JIN Jiwei, MA Feifei, ZHANG Jian Journal of Frontiers of Computer Science and Technology    2015, 9 (7): 769-780.   DOI: 10.3778/j.issn.1673-9418.1405041 SMT is the problem of deciding the satisfiability of a first order formula with respect to some theory formulas. It is being recognized as increasingly important due to its applications in different communities, in particular in formal verification, program analysis and software testing. This paper provides a brief overview of SMT and its theories. Then this paper introduces some approaches aiming to improve the efficiency of SMT solving, including eager and lazy approaches and optimum technique which have been proposed in the last ten years. This paper also introduces some state-of-the-art SMT solvers, including Z3, Yices and CVC3/CVC4. Finally, this paper gives a preliminary prospect on the research trends of SMT, which include SMT with quantifier, optimization problems subject to SMT and volume computation for SMT. Related Articles | Metrics

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Review of medical image processing and analyzing software platforms LI Enzhong+ Journal of Frontiers of Computer Science and Technology    2008, 2 (5): 467-477.   DOI: 10.3778/j.issn.1673-9418.2008.05.002 The technology of medical image processing and analyzing can provide more clear and accurate images and more useful quantitative information for the doctor to assist the diagnosis and treatment. The development of algorithms such as segmentation， registration and 3D visualization is the motivation of medical image processing and analyzing， while the software platforms based on these algorithms are the accelerators of medical image processing and analyzing. Many software platforms have been designed for scientific research or providing wieldy assistant tool for certain users. This paper introduces some mainstream platforms， and discusses the advantages and shortcomings of these platforms adequately. Our aim is to spread the applications of medical image processing and analyzing software platform， and motivate the researchers to contribute to the development of the software platforms. Related Articles | Metrics

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Security Issues and Their Countermeasuring Techniques of Machine Learning: A Survey LI Pan, ZHAO Wentao, LIU Qiang, CUI Jianjing, YIN Jianping Journal of Frontiers of Computer Science and Technology    2018, 12 (2): 171-184.   DOI: 10.3778/j.issn.1673-9418.1708038 Machine learning has already become one of the most widely used techniques in the field of computer science, and it has been widely applied in image processing, natural language processing, network security and other fields. However, there has been many security threats that need to be overcome on current machine learning algorithms and training data set, which will affect the security of several practical applications, such as facial detection, malware detection and automatic driving, etc. According to the known security threats, which aim to a variety of machine learning algorithms, such as the support vector machine (SVM) classifier, clustering and deep neural networks, this paper introduces the issues that happen in the training, testing/inference phase of machine learning, which include privacy leaking and attacks of poisoning, evasion, impersonate and inversion based on the adversarial samples. Then, this paper sums up the machine learning adversary model as well as its safety assessment mechanism and concludes a certain number of countermeasures and privacy protection techniques on training and testing processes. Finally, this paper looks forward some correlative problems worthy of further discussion. Related Articles | Metrics

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Survey of location privacy-preserving PAN Xiao+,XIAO Zhen,MENG Xiaofeng Journal of Frontiers of Computer Science and Technology    2007, 1 (3): 268-281.   With blooming of sensor and wireless mobile devices,it is easy to access mobile users’ location information anytime and anywhere. On one hand,Location Based Services（LBS） is becoming more and more valuable and important. On the other hand,location privacy issues raised by such applications have also grasped more and more attention. However,due to the specificity of location information,traditional privacy-preserving techniques in data publish can not be used. The paper analyzes the challenges of location privacy-preserving,and gives a survey of existing work including the system architecture,location anonymity and query processing. Finally,some open issues are given at the end of the paper. Related Articles | Metrics

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Survey of Information-Centric Networking XIA Chunmei, XU Mingwei Journal of Frontiers of Computer Science and Technology    2013, 7 (6): 481-493.   DOI: 10.3778/j.issn.1673-9418.1303025 Network requirements are evolved from data communications between two hosts to accessing a large amount of information through networks. The current Internet uses address-centric network communication model, which is suitable for the communications between hosts but not efficient in the communications between hosts and networks. Given this fact, information-centric networking (ICN) becomes the hot spot to meet the new requirements. Firstly, this paper presents the basic idea of ICN, analyzes the features of ICN, and classifies different ICN approaches, including the following aspects: naming, resolving, routing and caching. Secondly, this paper summarizes the five key technologies in ICN which are naming, resolving, routing, distribution and caching, and then analyzes and evaluates the existing ICN schemes. Finally, several key issues in ICN are discussed and future directions are pointed out. Related Articles | Metrics

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Mutual Information Based Modeling and Completion of Correlations in Knowledge Graphs XIA Wei, WANG Shanlei, YIN Zidu, YUE Kun Journal of Frontiers of Computer Science and Technology    2018, 12 (7): 1064-1074.   DOI: 10.3778/j.issn.1673-9418.1709092 The completion of missing relationships between entities in knowledge graph (KG) is the topic with great attention in the field of KG research. With the rapid development of Web2.0, the association between entities reflected by the user-generated data (UGD) is complementary to the knowledge described in KG. In the knowledge reasoning method based on KG path, there are sparse or wrong entity relations and poor connectivity, which leads to the inaccurate relationship extracted from entities. For this problem, this paper proposes a method for complementing KG by using correlation between entities in UGD. Firstly, based on the UGD, this paper uses mutual information to calculate the relationship between entity nodes and build the entity association graph (EAG), and then proposes a superposition method to quantify the potential correlation between non-adjacent entities in the EAG, so the association impact values are obtained. Finally, the multiple correlation effects between non-adjacent entity nodes are superposed to determine whether there is a strong correlation between the entities. By adding the edges between non-adjacent entity nodes with associations, KG completion can be fulfilled. The experimental results based on real data sets show the efficiency and effectiveness of the proposed KG completion. Related Articles | Metrics

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Mutation Testing: Principal, Optimization and Application CHEN Xiang, GU Qing Journal of Frontiers of Computer Science and Technology    2012, 6 (12): 1057-1075.   DOI: 10.3778/j.issn.1673-9418.2012.12.001 Mutation is a fault-based testing technique. This topic is widely researched for over 40 years. This paper summarizes previous research work into three modules: principal, optimization and application. In the principal module, this paper firstly introduces two fundamental hypotheses, secondly illustrates the traditional process of mutation analysis and gives definitions for the important concepts, lastly summarizes equivalent mutant detection techniques into static detection and dynamic detection categories. In the optimization module, this paper illustrates mutant selection optimization and mutant execution optimization. In the application module, this paper introduces three classical applications: test suite adequacy evaluation, test case generation and regression testing. Finally, this paper draws a conclusion and forecasts some potential future research work. Related Articles | Metrics

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A Review on Surface Defect Detection LUO Jing, DONG Tingting, SONG Dan, XIU Chunbo Journal of Frontiers of Computer Science and Technology    2014, 8 (9): 1041-1048.   DOI: 10.3778/j.issn.1673-9418.1405007 Surface defect detection based on machine vision has been widely used in the various fields, which is important for ensuring the product quality during automatic production. However, there are some challenges on the surface inspection, such as low contrast, shape similarity between defect regions and non-defect regions, tiny defect detection, inspection speed and accuracy. So, this paper gives the recent advances in surface defect detection. The surface defect detection is categorized into three types: statistics, spectrum and model approach. Then this paper compares several typical approaches in detail, including feature extraction, detecting algorithms and the performance of the algorithms, and analyzes the effectiveness of the algorithms deeply. Finally, this paper summarizes the challenge and future trend. Related Articles | Metrics

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A review of FEM and trend of development GU Chengzhong+, WU Xinyue Journal of Frontiers of Computer Science and Technology    2008, 2 (3): 248-259.   This paper summarizes the development of search in mesh generation for finite element computation in last ten years. Firstly， the principle of meshing is researched. Secondly， the main research fields， such as mapping methods， grid-based approach， point distribution and triangulation approach， topology decomposition approach， geometry decomposition approach， sweeping approach， are discussed and classified. Uniting instances， it analyses systematically the principle， characteristics and scopes of these methods. Thirdly， the front edge is narrated and hexahedral mesh is reviewed. Finally， this paper prospects the trend FEM. Related Articles | Metrics

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Depth Camera in Computer Vision and Computer Graphics: An Overview XIANG Xueqin, PAN Zhigeng, TONG Jing Journal of Frontiers of Computer Science and Technology    2011, 5 (6): 481-492.   An increasing number of applications depend on accurate and fast 3D scene analysis, such as geometry reconstruction, collision prevention, mixed reality, and gesture recognition. The acquisition of a range map by image- based analysis or laser scan techniques is still time-consuming and expensive. Emerged as an alternative device to measure distance, depth camera enjoys some advances, e.g., lower price and higher photo speed, that have not be made in traditional 3D measuring systems. Recently, significant improvements have been made in order to achieve low-cost and compact depth camera devices that have the potential to revolutionize many fields of research, including computer vision, computer graphics and human computer interaction (HCI). These technologies are also starting to attract many researchers working for academic or commercial purposes. This paper gives an overview of recent developments in depth camera technology and discusses the current state of the integration of this technology into various related applications in computer vision and computer graphics. Related Articles | Metrics

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A survey of Low-rate Denial-of-Service attacks HE Yanxiang 1,2, LIU Tao 1+, CAO Qiang 1, XIONG Qi 1, HAN Yi 1 Journal of Frontiers of Computer Science and Technology    2008, 2 (1): 1-19.   Low-rate denial-of-service attack is a novel category of attacks that are aimed at exploiting the adaptive behavior exhibited by several network and system protocols. Different from traditional DoS attacks， this kind of attacks can make serious destroy on the victims by using periodically non-suspicious low-rate attack streams. Since they have been brought forward， these new attacks have caused special concern； the problems of detecting and defending towards them have gradually become important research issues in the network security area. In the paper， theoretical analyses， modeling and simulations of various LDoS attacks are presented， the difficulties of defending and current solutions are discussed. At the end of the paper， several problems which need further researches are put forward， in order to provide reference to the future research work on the defending of this kind of attacks. Related Articles | Metrics

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Review of Deep Learning Applied to Time Series Prediction LIANG Hongtao, LIU Shuo, DU Junwei, HU Qiang, YU Xu Journal of Frontiers of Computer Science and Technology    2023, 17 (6): 1285-1300.   DOI: 10.3778/j.issn.1673-9418.2211108 The time series is generally a set of random variables that are observed and collected at a certain frequency in the course of something??s development. The task of time series forecasting is to extract the core patterns from a large amount of data and to make accurate estimates of future data based on known factors. Due to the access of a large number of IoT data collection devices, the explosive growth of multidimensional data and the increasingly demanding requirements for prediction accuracy, it is difficult for classical parametric models and traditional machine learning algorithms to meet high efficiency and high accuracy requirements of prediction tasks. In recent years, deep learning algorithms represented by convolutional neural networks, recurrent neural networks and Trans-former models have achieved fruitful results in time series forecasting tasks. To further promote the development of time series prediction technology, common characteristics of time series data, evaluation indexes of datasets and models are reviewed, and the characteristics, advantages and limitations of each prediction algorithm are experimentally compared and analyzed with time and algorithm architecture as the main research line. Several time series prediction methods based on Transformer model are highlighted and compared. Finally, according to the problems and challenges of deep learning applied to time series prediction tasks, this paper provides an outlook on the future research trends in this direction. Reference | Related Articles | Metrics

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Mathematic methods of biological process WANG Fei,TANG Yin,XI Yan-ping,LU Ru-qian Journal of Frontiers of Computer Science and Technology    2007, 1 (1): 17-38.   Research within bioinformatics is classified into two categories，one is static biological problem to do research at cell and molecule level，the other，which is called biological process，is dynamic biological problem to research dynamic evolvement of these static characters.A main mathematical approach of the former is to find efficient algorithms，whereas it of the latter is to give mathematic model to simulate and analyze biological process.Three mathematic models，differential equation，Bayesian networks and process algebra，are surveyed and discussed from the view of biological process． Related Articles | Metrics

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Software Engineering Data Mining: A Survey YU Shusi, ZHOU Shuigeng, GUAN Jihong Journal of Frontiers of Computer Science and Technology    2012, 6 (1): 1-31.   DOI: 10.3778/j.issn.1673-9418.2012.01.001 With the rapid enlargement of software scale, to retrieve manually the relevant information of software development and maintenance is becoming more and more difficult. Data mining technology can help to discover useful information from software engineering data automatically, which thus speeds up the process of software de-velopment. This paper surveys the state of the art techniques of software engineering data mining. First, it presents basic concepts and technical challenges of software engineering data mining. Then, it discusses the details of data mining at different phases of software engineering, including motivation, problems, procedures and approaches, specifically, it emphasizes the methods of data pre-processing and representation. Finally, it gives a vision of future development of software engineering data mining technology. Related Articles | Metrics

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A Survey on MapReduce Optimization Technologies HUANG Shan, WANG Botao, WANG Guoren, YU Ge, LI Jiajia Journal of Frontiers of Computer Science and Technology    2013, 7 (10): 865-885.   DOI: 10.3778/j.issn.1673-9418.1307035 As a parallel programming model for big data processing, MapReduce is getting more and more attractions from academia and industry for its good scalability, availability and fault tolerance. There exist a lot of optimization technologies focusing on the application limitations of MapReduce. This paper firstly introduces the MapReduce framework, then compares the research work on MapReduce optimization technologies including column storage, index, join, iteration calculation, scientific calculation, and scheduling algorithms respectively. Finally, this paper analyzes the challenges and figures out the trends of this area. Related Articles | Metrics

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Super-Resolution Image Reconstruction with Iterative Back Projection Algorithm GUO Weiwei 1, ZHANG Pinzheng 2+ Journal of Frontiers of Computer Science and Technology    2009, 3 (3): 321-329.   DOI: 10.3778/j.issn.1673-9418.2009.03.010 An image super-resolution reconstruction method， which combines the frequency domain motion estimation and iterative back projection （IBP） algorithm， has been proposed. Based on the frequency domain phase difference among the low resolution images， the motion parameters between the reference LR image and other LR images are estimated. Combining the IBP algorithm and the estimated motion parameters， the super-resolution image is iteratively reconstructed. Experimental results demonstrate that the proposed method is effective. Related Articles | Metrics

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RFID complex event processing techniques GU Yu,YU Ge+,ZHANG Tiancheng Journal of Frontiers of Computer Science and Technology    2007, 1 (3): 255-267.   With the development of RFID technology,RFID is being applied ubiquitously in every field. With throughly processing and analyzing RFID data,more complex events and implicit knowledge could be discovered to effectively support advanced applications such as event monitoring and pre-warning. Due to the speciality of RFID,it is insufficient to take use of the state of art active database and data stream techniques for high-performance RFID event detection and processing. The paper analyzes the characteristics of RFID data,makes a survey of the newest technology over RFID complex event processing,and explores the new problems to be solved urgently,including RFID data cleaning,data-centric event detection techniques,event-centric event detection techniques and complex event processing systems,and finally gives an outlook of the research issues in the future. Related Articles | Metrics

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Survey of Evolutionary Testing XIE Xiaoyuan 1, XU Lei 1, XU Baowen 1,2+,NIE Changhai 1, SHI Liang 3 Journal of Frontiers of Computer Science and Technology    2008, 2 (5): 449-466.   DOI: 10.3778/j.issn.1673-9418.2008.05.001 Evolutionary Testing （ET）， as a very promising technique for automatic testing， can generate effec-tive test cases for many test objects successfully. ET converts the task of test case generation into an optimization problem， and uses Genetic Algorithm（GA） to search for the desired solutions with very little cost. The input domain of system under test is the search space of GA. With a complete automation， this search process can be more efficient. Besides as a result of both the guidance and the randomicity， the search can overcome the shortcoming of complex search domain and avoid a blind search of simple random testing. In recent years， more and more researches have been focused on ET， and have made it being applied successfully in many areas. This paper introduces the application of ET in structural testing， functional testing， temporal performance testing and object-oriented testing. From summarizing the main ET methods in those applications， it analyzes and compares each method’s advantages and shortcomings， in order to provide some valuable advices for studying and selecting proper ET methods. Additionally the paper concludes the performance optimization techniques of ET， and finally it presents ET’s prospect and the future research for ET. Related Articles | Metrics

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Software Knowledge Graph Building Method for Open Source Project LI Wenpeng, WANG Jianbin, LIN Zeqi, ZHAO Junfeng, ZOU Yanzhen, XIE Bing Journal of Frontiers of Computer Science and Technology    2017, 11 (6): 851-862.   DOI: 10.3778/j.issn.1673-9418.1609026 Software reuse is a solution to reduce the duplication of efforts during software development and improve the efficiency and quality of the process. Open source projects’ source code, mailing lists, issue reports, Q&A documents and other software resources contain software knowledge with complex structure and rich semantic association on a large scale. How to obtain and organize software knowledge and retrieve it effectively in the process of software reuse have become urgent problems. In order to solve these problems, this paper constructs software knowledge graph, whose goal is to organize and manage the structural knowledge of a software project, and provides software knowledge graph based knowledge retrieval. The contributions of this paper are as follows: Providing the extraction principles and methods of software knowledge entities, and extracting software knowledge entities from four different kinds of software resources respectively; Providing the methods of building the relationships between software knowledge entities; Providing two software knowledge retrieval mechanisms, and displaying the retrieval       results by the combination of word list and graph visualization; Designing the implementation framework of software knowledge graph. On the basic of the work above, this paper designs and implements a software knowledge graph building tool for open source project. Instances prove that software knowledge graph can help developers to better retrieve and use knowledge. Related Articles | Metrics

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Optimization for Inter-VMs Communication on KVM with Para-Virtualized I/O Model DING Shengge, MA Ruhui, LIANG Alei, GUAN Haibing Journal of Frontiers of Computer Science and Technology    2011, 5 (12): 1114-1120.   This paper presents a para-virtualized network model to optimize inter-VMs communication performance, which is designed as a shared-memory-based channel crossing barriers to reduce data copies in virtualization systems. The implementation of kernel-based virtual machine (KVM) with para-virtualized I/O device emulation can simplify I/O operation and reduce traps which incur switches between root and non-root modes in KVM. It provides an efficient I/O path and this communication channel is transparent to guest applications while the front-end driver has a standard interface for kernel. This method can achieve performance nearly at inter-processes communication level. The test results on prototype show that the throughput and latency of inter-VMs communication are improved. Related Articles | Metrics

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Survey of Metamorphic Testing DONG Guowei 1,2, XU Baowen 1,2+, CHEN Lin 1,2, NIE Changhai 1,2, WANG Lulu 1,2 Journal of Frontiers of Computer Science and Technology    2009, 3 (2): 130-143.   DOI: 10.3778/j.issn.1673-9418.2009.02.002 Metamorphic testing （MT） is a technique that tests software by checking relationships among several executions， so it is very practical and effective for program with oracle problem. This technique has been used in various fields， and great developments have been made in MT process optimization and combination with other testing methods since 1998. The current investigation of MT is surveyed， and some research directions for it are presented， which are the research of MT sufficiency， the effective metamorphic relation constructing technology， the effective original testing case selecting technology， the research of MT for new type software and the development of MT tools， etc. Related Articles | Metrics

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Survey on Visualization of Medical Big Data WANG Yi, REN Shuxia Journal of Frontiers of Computer Science and Technology    2017, 11 (5): 681-699.   DOI: 10.3778/j.issn.1673-9418.1609014 With the development of the Internet+, medical big data is showing explosive growth which has multitudinous data types and complex relationships. The general data visualization method is difficult to demonstrate medical big data effectively, the medical big data visualization technology faces the huge challenge. This paper outlines the origin, characteristics and research progress of medical big data, introduces the related concepts and research status of visualization of medical big data. The existing visualization methods of medical big data are studied and divided into 2 types, which give a comprehensive description of the characteristics, legend and common visualization methods of medical big data by using a table. Future research focuses and problems of visualization of medical big data are analyzed and also have important reference value in research methods and universal application of visualization of medical big data. Related Articles | Metrics

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Knowledge concepts and measures in views of information-knowledge-intelligence ecosystem ZHONG Yixin + Journal of Frontiers of Computer Science and Technology    2007, 1 (2): 129-137.   The concepts， categorization and representation of knowledge in views of the macro and micro ecosystem of information-knowledge-intelligence are presented， and the quantitative measures for various categories of knowledge are established. It is seen that the measures of knowledge are closely related to that of comprehensive information to certain extent. The relationship between the knowledge measures and the measures of comprehensive information， may provide a sound base for further invastigation of the theory of knowledge as well as the unified theory of information， knowledge and intelligence. Related Articles | Metrics

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A survey of research on XML compression techniques LUO Jizhou+, LI Jianzhong Journal of Frontiers of Computer Science and Technology    2008, 2 (3): 225-234.   There is much redundant information in XML data because of its self-describing characteristic. How to compress XML data so as to improve the efficiency of the management of XML data is a new trend of research. Since 2001， a lot of research results of XML compression techniques have been obtained. Survey in this paper is the research work on XML compression techniques， including storage oriented XML compression techniques， query oriented XML compression techniques and application oriented XML compression techniques. The existing problems in the current research work and the new research issues are also discussed. At the end of this paper， many significant references are listed for the researchers. Related Articles | Metrics

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Ontology－based semantic search over relational data-bases WANG Shan1，2,ZHANG Jun1，2，3+,PENG Zhao－hui1，2,ZHAN Jiang1，2,DU Xiao－yong1，2 Journal of Frontiers of Computer Science and Technology    2007, 1 (1): 59-78.   Taking the economics ontology as an example，the authors study the principles and methods of SemSORD in detail and present a novel SemSORD prototype called Si－SEEKER based on keyword search over relational databases.In the end，the emerging research on SemSORD is proposed． Related Articles | Metrics

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Towards Management as a Service LI Ying 1+, HUANG Gang 2, LIU Tiancheng 1, YANG Jie 1, LIU Zhao 2 Journal of Frontiers of Computer Science and Technology    2008, 2 (4): 346-355.   DOI: 10.3778/j.issn.1673-9418.2008.04.002 For incarnating the Web as the dominant application style of the Internet， the Web itself is becoming an unlimited platform for almost all business in the Internet. Such a phenomenon is called Web as the platform， which brings opportunities and challenges to information technology. In this position paper， the management issue of the Web， one of the key technical challenges of the Web as the platform， is explored. At first， the management requirements induced by the features of the Web are summarized. Then， the “Management as a Service” is proposed as a solution to the Web management issue. Followed by identified technical challenges， the PKUAS service-oriented management is introduced as a case study to illustrate how to make “Management as a Service” feasible. Related Articles | Metrics

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