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Dynamic Web services discovery based on similarity computation

Journal of Harbin Institute of Technology(New Series) 2010年第1期17卷 119-122页

作者：陈江锋 State Key Lab.of Software Development Environment Beihang University

A new approach for dynamic Web services discovery based on similarity computation in the treatment of massive Web information resource is put forward. Firstly, three kinds of service description information, textual, semantic and structural information, were modeled to compute the similarity of services. Then a novel dynamic Web services discovery mechanism was provided and the experiment on it was carried out. Results show that the new approach achieves considerable performance on precision and efficiency metrics for dynamic Web services discovery.

关键词： Web services ontology VSM graph isomorphism

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An improved algorithm for finding community structure in networks with an application to IPv6 backbone network

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中国高等学校学术文摘·计算机科学 2007年第4期1卷 459-467页

作者： GUO Yingxin XU Ke State Key Lab of Software Development Environment Beihang UniversityBeijing 100083China

The discovery of community structure in a large number of complex networks has attracted lots of interest in recent *** category of algorithms for detecting community structure,the divisive algorithms,has been proposed and improved *** this paper,we propose an improved divisive algorithm,the basic idea of which is to take more than one parameters into consideration to describe the networks from different points of *** its basic idea appears to be a little simple,it is shown experimentally that it outperforms some other algorithms when it is applied to the networks with a relatively obscure community *** also demonstrate its effectiveness by applying it to IPv6 backbone *** communities detected by our algorithm indicate that although underdeveloped compared with IPv4 network,IPv6 network has already exhibited a preliminary community ***,our algorithm can be further extended and adapted in the *** fact,it suggests a simple yet possibly efficient way to improve algorithms.

关键词： community divisive algorithm IPv6 network

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A high order collaboration and real time formal model for automatic testing of safety critical systems

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Frontiers of Computer Science 2015年第4期9卷 495-510页

作者： Jianghua LV ShUong MA Xianjun LI Jiangong SONG State Key Lab of Software Development Environment School of Computer Science Beihang University Beijing 100191 China

The need for safety critical systems （SCS） is both important and urgent, and their evaluation and verification are test-dependent. SCS are usually complex and very large, so manual testing of SCS are infeasible in practice, and develop- ing automatic test approaches for SCS has become an impor- tant trend. This paper defines a formal semantics model for automatic test of SCS, called AutTMSCS, which describes behaviors in SCS testing. The model accommodates the high order collaboration in real time and temporariness of SCS testing. Testing tasks, test equipment and products under test are abstracted and architected in three layers, and a method for automatic testing is given. Based on extended label tran- sition system （LTS）, the convergency and correctness of the model are proved to demonstrate the computability of the model, indicating that the testing process of SCS can be au- tomatic.

关键词： safety critical systems (SCS) test automatictest equipment collaboration high order calculus LTS realtime

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Towards structural web services discovery

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Journal of Harbin Institute of Technology(New Series) 2008年第3期15卷 297-301页

作者：陈江锋 State Key Lab. of Software Development Environment Beihang University

A syntactic and structural matching mechanism for service discovery was put forward, which tries to exploit the underlying semantics of web services to enhance tbe traditional syntactic service discovery. We commit WSDL （Web Service Description Language） as service description language. The syntactic matching mechanism is based on the textual similarity among WSDL documents using VSM （ Vector Space Model）. The structural information is extracted from WSDL document tree or the invocation sequence of a series of services which can be viewed as the problem of graph isomorphism. Then we combine the syntactic and structural similarity linearly to calculate the service similarity. Finally we provide a novel web services discovery framework named SG^＊ to find the exact services meeting the users＇ goals based on service similarity.

关键词： web services service discovery VSM

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Ontology-based Unified Model for Heterogeneous Threat Intelligence Integration and Sharing 11

Ontology-based Unified Model for Heterogeneous Threat Intell...

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2017 11th IEEE International Conference on Anti-counterfeiting,Security,and Identification(ASID)

作者： Yishuai Zhao Bo Lang Ming Liu State Key Lab of Software Development Environment Beihang University

ISBN: (纸本)9781538605349;9781538605332

Threat intelligence contains valuable information for cyber security;however, usually the intelligence is from multiple sources and is described with different data formats and schemas, which not only leads to the inefficiency of intelligence integration and analysis, but also makes threat intelligence sharing difficult. Therefore, the unified representation of the threat intelligence becomes a crucial challenge. This paper presents an ontologybased unified model for describing the multi-source and heterogeneous threat intelligence. In our model, we first propose the cyber security ontology and the unified model. Hence, the threat intelligence from different sources can be mapped to our unified model to achieve unified representation, which makes threat intelligence sharing and analysis more efficient. Furthermore, we propose and implement an intelligence integration framework based on our unified intelligence model and the open source intelligence collection tool Intel MQ. The feasibility and effectiveness of our model is verified by the performance of this framework.

关键词： ontology threat intelligence unified model intelligence integration

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An automatic testing framework applied on LIW and implementation

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Journal of Theoretical and Applied Information Technology 2012年第2期46卷 648-653页

作者： Yin, Jie Yu, Dan Ma, Shilong State Key Lab. of Software Development Environment Beihang University Beijing 100191 Beijing China

software is an important component of Large Information Weapon (LIW). We propose a data-driven distributed automatic testing framework, which is based on the analysis of LIW testing requirements, and it supports the whole process of distributed software test. The main components of the framework consist of distributed test designing environment, execution and control environment and test results show environment. We present a set of GUI scripting language specification for automatic testing, the script language with object-oriented features. Unlike the previous GUI automatic testing scripting language, this specification records the information of the node where the test cases will be running. As an application of the framework, we develop an automatic testing system (DMATS). DMATS has been put into practices in XXX-business electronic system, and it is proved the feasibility of the framework. © 2005 - 2012 JATIT & LLS. All rights reserved.

关键词： Specifications

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ARCosmetics:a real-time augmented reality cosmetics try-on system

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Frontiers of Computer Science 2023年第4期17卷 15-28页

作者： Shan AN Jianye CHEN Zhaoqi ZHU Fangru ZHOU Yuxing YANG Yuqing MA Xianglong LIU Haogang ZHU Tech.&Data Center *** Inc.Beijing 100176China State Key Lab of Software Development Environment Beihang UniversityBeijing 100191China

A virtual cosmetics try-on system provides a realistic try-on experience for consumers and helps them efficiently choose suitable *** this article,we propose a real-time augmented reality virtual cosmetics try-on system for smartphones(ARCosmetics),taking speed,accuracy,and stability into consideration at each step to ensure a better user experience.A novel and very fast face tracking method utilizes the face detection box and the average position of facial landmarks to estimate the faces in continuous frames.A dynamic weight Wing loss is introduced to assign a dynamic weight to every landmark by the estimated error during *** balances the attention between small,medium,and large range error and thus increases the accuracy and *** also designed a weighted average method to utilize the information of the adjacent frame for landmark refinement,guaranteeing the stability of the generated *** experiments conducted on a large 106-point facial landmark dataset and the 300-VW dataset demonstrate the superior performance of the proposed method compared to other state-of-the-art *** also conducted user satisfaction studies further to verify the efficiency and effectiveness of our ARCosmetics system.

关键词： facial landmark localization face tracking stabilization augmented reality virtual try-on

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MULTI-PRETEXT ATTENTION NETWORK FOR FEW-SHOT LEARNING WITH SELF-SUPERVISION

MULTI-PRETEXT ATTENTION NETWORK FOR FEW-SHOT LEARNING WITH S...

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2021 IEEE International Conference on Multimedia and Expo, ICME 2021

作者： Li, Hainan Tao, Renshuai Li, Jun Qin, Haotong Ding, Yifu Wang, Shuo Liu, Xianglong State Key Lab of Software Development Environment Beihang University China

ISBN: (纸本)9781665438643

Few-shot learning is an interesting and challenging study, which enables machines to learn from few samples like humans. Existing studies rarely exploit auxiliary information from large amount of unlabeled data. Self-supervised learning is emerged as an efficient method to utilize unlabeled data. Existing self-supervised learning methods always rely on the combination of geometric transformations for the single sample by augmentation, while seriously neglect the endogenous correlation information among different samples that is the same important for the task. In this work, we propose a Graph-driven Clustering (GC), a novel augmentation-free method for self-supervised learning, which does not rely on any auxiliary sample and utilizes the endogenous correlation information among input samples. Besides, we propose Multi-pretext Attention Network (MAN), which exploits a specific attention mechanism to combine the traditional augmentation-relied methods and our GC, adaptively learning their optimized weights to improve the performance and enabling the feature extractor to obtain more universal representations. We evaluate our MAN extensively on miniImageNet and tieredImageNet datasets and the results demonstrate that the proposed method outperforms the state-of-the-art (SOTA) relevant methods. © 2021 IEEE

关键词： Convolutional neural networks

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Two-branch Objectness-centric Open World Detection 3

Two-branch Objectness-centric Open World Detection

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3rd International Workshop on Human-Centric Multimedia Analysis, HCMA 2022, held in conjunction with the ACM Multimedia 2022

作者： Wu, Yan Zhao, Xiaowei Ma, Yuqing Wang, Duorui Liu, Xianglong State Key Lab of Software Development Environment Beihang University China

ISBN: (纸本)9781450394925

In recent years, with the development of deep learning, object detection has made great progress and has been widely used in many tasks. However, the previous models are all performed on closed sets, while there are many unknown categories in the real open world. Directly applying a model trained on known categories to the unknown classes will lead to misclassification. In this paper, we propose a two-branch objectness-centric open world object detection framework consisting of the bias-guided detector and the objectness-centric calibrator to effectively capture the objectness of both known and unknown instances and make the accurate prediction for known classes. The bias-guided detector trained with the known labels can predict the classes and boxes for known classes accurately. While the objectness-centric calibrator can localize the instances of any class, and does not affect the classification and regression of known classes. In the inference stage, we use the objectness-centric affirmation to confirm the results for known classes and predict the unknown instances. Comprehensive experiments conducted on the open world object detection benchmark validate the effectiveness of our method compared to state-of-the-art open world object detection approaches. © 2022 ACM.

关键词： Object detection

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A word co-occurrence matrix based method for relevance feedback

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Journal of Computational Information Systems 2011年第1期7卷 17-24页

作者： Chen, Zilong Lu, Yang State Key Lab. of Software Development Environment Beihang University Beijing 100191 China School of Software and Microelectronics Peking University Beijing 100191 China

In most information retrieval models, keyword frequency plays a major role. However, these models are less context dependent, the main disadvantage is that they don't have a deeper understanding of the documents. The traditional relevance feedback techniques assume that terms in documents are independent;they do not consider the term dependencies and the semantic relations among documents. In this paper, we propose a Word Co-occurrence Matrix based Method for relevance feedback. Firstly, the definition of word co-occurrence matrix is given. Unlike other studies about word association, we consider the influence of the inter word distance and co-windows ratio. So we think that this matrix can simply represents the document semantic relations and then we calculate the similarity between documents according to this matrix. In the feedback process, this similarity score will be combined with the initial score to improve the retrieval effectiveness. Experiments with TREC dataset demonstrate the effectiveness of this method. © 2011 Binary Information Press.

关键词： Semantics

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