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A Hybrid Method of Domain Lexicon Construction for Opinion Targets Extraction Using Syntax and Semantics

Journal of Computer Science & Technology 2016年第3期31卷 595-603页

作者： Chun Liao Chong Feng Sen Yang He-Yan Huang Department of Computer Science and Technology Beijing Institute of Technology Beijing 100081 China Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications Beijing Institute of Technology Beijing 100081 China

Opinion targets extraction of Chinese microblogs plays an important role in opinion mining. There has been a significant progress in this area recently, especially the method based on conditional random field （CRF）. However, this method only takes lexicon-related features into consideration and does not excavate the implied syntactic and semantic knowledge. We propose a novel approach which incorporates domain lexicon with groups of syntactical and semantic features. The approach acquires domain lexicon through a novel way which explores syntactic and semantic information through Part- of-Speech, dependency structure, phrase structure, semantic role and semantic similarity based on word embedding. And then we combine the domain lexicon with opinion targets extracted from CRF with groups of features for opinion targets extraction. Experimental results on COAE2014 dataset show the outperformance of the approach compared with other well-known methods on the task of opinion targets extraction.

关键词： domain lexicon opinion targets extraction syntactic structure semantic role word embedding

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Singleton detection for coreference resolution via multi-window and multi-filter CNN 1

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13th China Workshop on Machine Translation, CWMT 2017

作者： Li, Kenan Huang, Heyan Guo, Yuhang Jian, Ping School of Computer Science and Technology Beijing Institute of Technology Beijing China Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Application 5 South Zhongguancun Street Beijing100081 China Beijing Advanced Innovation Center for Imaging Technology Capital Normal University Beijing100048 China

ISBN: (数字)9789811071348

ISBN: (纸本)9789811071331

Mention detection is the first and a key stage in most of coreference resolution systems. Singleton mentions are the ones which appear only once and are not mentioned in the following texts. Singleton mentions always affect the performance of coreference resolution systems. To remove the singleton ones from the automatically predicted mentions, we propose a novel singleton detection method based on multi-window and multi-filter convolutional neural network (MMCNN). The MMCNN model can detect singleton mentions with less use of hand-designed features and more sentence information. Experiments show that our system outperforms all the existing singleton detection systems. © Springer Nature Singapore Pte Ltd. 2017.

关键词： Convolution

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Identifying suspected cybermob on Tieba 15th

Identifying suspected cybermob on Tieba

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15th China National Conference on Chinese Computational Linguistics, CCL 2016 and 4th International Symposium on Natural language processing Based on Naturally Annotated Big Data, NLP-NABD 2016

作者： Shi, Shumin Zhou, Xinyu Zhao, Meng Huang, Heyan School of Computer Science and Technology Beijing Institute of Technology Beijing100081 China Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications Beijing China

ISBN: (纸本)9783319476735

This paper describes an approach to identify suspected cybermob on social media. Many researches involve making predictions of group emotion on Internet (such as quantifying sentiment polarity), but this paper instead focuses on the origin of information diffusion, namely back to its makers and contributors. According our previous findings that have shown, at the level of Tieba’s contents, the negative information or emotions spread faster than positive ones, we centre on the maker of negative message in this paper, so-called cybermobs who post aggressive, provocative or insulting remarks on social websites. We explore the different characteristics between suspected cybermobs and general netizens and then extract relative unique features of suspected cybermobs. We construct real system to identify suspected cybermob automatically using machine learning method with above features, including other common features like user/content-based ones. Empirical results show that our approach can detect suspected cybermob correctly and efficiently as we evaluate it with benchmark models, and apply it to actual cases. © Springer International Publishing AG 2016.

关键词： Artificial intelligence

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Privacy-preserving anomaly detection across multi-domain for software defined networks 7th

Privacy-preserving anomaly detection across multi-domain for...

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7th International Conference on the Theory, Technologies and applications of Trusted Systems, INTRUST 2015

作者： Bian, Huishan Zhu, Liehuang Shen, Meng Wang, Mingzhong Xu, Chang Zhang, Qiongyu Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications School of Computer Science Beijing Institute of Technology Beijing China Nanjing China University of the Sunshine Coast Queensland Australia

ISBN: (纸本)9783319315492

Software Defined Network (SDN) separates control plane from data plane and provides programmability which adds rich function for anomaly detection. In this case, every organization can manage their own network and detect anomalous traffic data using SDN architecture. Moreover, detection of malicious traffic, such as DDoS attack, would be dealt with much higher accuracy if these organizations shared their data. Unfortunately, they are unwilling to do so due to privacy consideration. To address this contradiction, we propose an efficient and privacy-preserving collaborative anomaly detection scheme. We extend prior work on SDN-based anomaly detection method to guarantee accuracy and privacy at the same time. The implementation of our design on simulated data shows that it performs well for network-wide anomaly detection with little overhead. © Springer International Publishing Switzerland 2016.

关键词： Denial-of-service attack

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When Factorization Meets Heterogeneous Latent Topics： An Interpretable Cross-Site Recommendation Framework

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Journal of Computer Science & Technology 2015年第4期30卷 917-932页

作者：辛欣林钦佑魏骁驰黄河燕 Beijing Engineering Research Center of High Volume Language Information Processing & Cloud Computing School of Computer Science Beijing Institute of Technology Beijing 100081 China Microsoft Research Asia Beijing 100080 China

Data sparsity is a well-known challenge in recommender systems. Previous studies alleviate this problem by incorporating the information within the corresponding social media site. In this paper, we solve this challenge by exploring cross-site information. Specifically, we examine： 1） how to effectively and efficiently utilize cross-site ratings and content features to improve recommendation performance and 2） how to make the recommendation interpretable by utilizing content features. We propose a joint model of matrix factorization and latent topic analysis. Heterogeneous content features are modeled by multiple kinds of latent topics. In addition, the combination of matrix factorization and latent topics makes the recommendation result interpretable. Therefore, the above two issues are simultaneously solved. Through a real-world ***, where user behaviors in three social media sites are collected, we demonstrate that the proposed model is effective in improving recommendation performance and interpreting the rationale of ratings.

关键词： collaborative filtering recommender system topic analysis

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EchoLoc: Accurate Device-Free Hand Localization Using COTS Devices

EchoLoc: Accurate Device-Free Hand Localization Using COTS D...

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International Conference on Parallel processing (ICPP)

作者： Huijie Chen Fan Li Yu Wang School of Computer Science Beijing Institute of Technology Beijing Engineering Research Center for High Volume Language Information Processing and Cloud Computing Applications Beijing China Department of Computer Science College of Computing and Informatics University of North Carolina at Charlotte Charlotte NC USA

ISBN: (纸本)9781509028245

Hand tracking systems are becoming increasingly popular as a fundamental HCI approach. The trajectory of moving hand can be estimated through smoothing the position coordinates collected from continuous localization. Therefore, hand localization is a key component of any hand tracking systems. This paper presents EchoLoc, which locates the human hand by leveraging the speaker array in Commercial Off-The-Shelf (COTS) devices (i.e., a smart phone plugged with a stereo speaker). EchoLoc measures the distance from the hand to the speaker array via the Time Of Flight (TOF) of the chirp. The speaker array and hand yield a unique triangle, therefore, the hand can be localized with triangular geometry. We prototype EchoLoc on iOS as an application, and find it is capable of localization with the average resolution within five centimeters of 73% and three centimeters of 48%.

关键词： Parallel processing

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Enhancing participant selection through caching in mobile crowd sensing

Enhancing participant selection through caching in mobile cr...

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International Workshop on Quality of Service

作者： Hanshang Li Ting Li Fan Li Weichao Wang Yu Wang Department of Computer Science University of North Carolina at Charlotte Charlotte NC USA Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications Beijing China School of Computer Science Beijing Institute of Technology Beijing China

With the rapid increasing of smart phones and their embedded sensing technologies, mobile crowd sensing (MCS) becomes an emerging sensing paradigm for performing large-scale sensing tasks. One of the key challenges of large-scale mobile crowd sensing systems is how to effectively select the minimum set of participants from the huge user pool to perform the tasks and achieve certain level of coverage. In this paper, we introduce a new MCS architecture which leverages the cached sensing data to fulfill partial sensing tasks in order to reduce the size of selected participant set. We present a newly designed participant selection algorithm with caching and evaluate it via extensive simulations with a real-world mobile dataset.

关键词： Sensors Mobile communication Memory Algorithm design and analysis Smart phones Probabilistic logic Data models

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Joint Optimization of Flow Latency in Routing and Scheduling for Software Defined Networks

Joint Optimization of Flow Latency in Routing and Scheduling...

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International Conference on Computer Communications and Networks (ICCCN)

作者： Meng Shen Liehuang Zhu Mingwei Wei Qiongyu Zhang Mingzhong Wang Fan Li Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Beijing Institute of Technology Beijing P. R. China Faculty of Arts and Business University of the Sunshine Coast Queensland Australia

ISBN: (纸本)9781509022809

Software Defined Networks (SDNs) decouple control plane from data plane and enable fine-grained traffic management by a logically centralized controller. Reducing the flow latency is of great importance in traffic management, which benefits both service providers and end users. Routing design and flow scheduling are typical ways to improve the flow transmission efficiency. However, existing studies usually consider them separately, due to the complexity of joint consideration. In this paper, we combine the routing and scheduling together and propose a latency-aware routing scheme with bandwidth assignment, which can efficiently reduce the flow latency with a moderate complexity. In the routing design, we utilize the global flow information to reduce both the latency of the newly arrived flow and its interference with existing flows in the network. Given flow forwarding paths determined by routing, the flow scheduling dynamically reallocates the bandwidth to all flows so as to further reduce the total flow latency. Experimental results show that our scheme outperforms the scheme currently available in OpenFlow, with an improvement of up to 60% on flow efficiency and a higher percentage of flows that meet their deadlines.

关键词： Routing Bandwidth Processor scheduling Complexity theory Scheduling Switches Software

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Enhanced null message algorithm for hybrid parallel simulation systems with large disparity in time step

Enhanced null message algorithm for hybrid parallel simulati...

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International Workshop/Symposium on Distributed Simulation and Real-Time applications (DS-RT)

作者： Bin Wang Yanlong Zhai Zishuo Wang Han Zhang Duzheng Qing Beijing Engineering Research Center of Massive Language Information Processing and Cloud Computing Applications Bijing Institute of Technology Beijing China Science and Technology on Special System Simulation Laboratory Beijing Simulation Center China

ISBN: (纸本)9781509035069

Modeling and simulation has received significant attention over the years for its ability to understand and transform real world systems. With the increasing of complexity and scale of the simulated systems, more computational power is required. Parallel discrete event simulation(PDES) is an important technology to integrate parallel computing into modeling and simulation. Time synchronization algorithm is the core of PDES, which determines the correctness and efficiency of the simulation. Traditional conservative synchronization algorithms, such as Chandy-Misra-Bryant(CMB) null message algorithm, use null message to synchronize the state and avoid deadlock among logical processes(LPs). But hybrid simulation systems contains both continuous models and discrete models, continuously changing states is typically modeled using time steps in hybrid simulation system. Therefore, hybrid systems with large disparity in time step are very common in real simulation systems. However, current conservative synchronization algorithm has not been fully investigated for this type of simulation systems and will generate massive synchronization messages. This paper proposed an enhanced null message algorithm for hybrid simulation systems with large disparity in time step. It extended the CMB algorithm by adding simulation time in null message request messages. This could significantly reduce the number of synchronization messages. Experimental results showed that our synchronization algorithm outperforms the CMB algorithm by reducing a great number of synchronization messages.

关键词： Synchronization Computational modeling Atmospheric modeling Adaptation models System recovery Ports (Computers) Complex systems

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Certificate-aware encrypted traffic classification using Second-Order Markov Chain

Certificate-aware encrypted traffic classification using Sec...

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International Workshop on Quality of Service

作者： Meng Shen Mingwei Wei Liehuang Zhu Mingzhong Wang Fuliang Li Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Beijing Institute of Technology Beijing P. R. China Faculty of Arts and Business University of the Sunshine Coast Queensland Australia College of Information Science and Engineering Northeastern University P. R. China

With the prosperity of network applications, traffic classification serves as a crucial role in network management and malicious attack detection. The widely used encryption transmission protocols, such as the Secure Socket Layer/Transport Layer Security (SSL/TLS) protocols, leads to the failure of traditional payload-based classification methods. Existing methods for encrypted traffic classification suffer from low accuracy. In this paper, we propose a certificate-aware encrypted traffic classification method based on the Second-Order Markov Chain. We start by exploring reasons why existing methods not perform well, and make a novel observation that certificate packet length in SSL/TLS sessions contributes to application discrimination. To increase the diversity of application fingerprints, we develop a new model by incorporating the certificate packet length clustering into the Second-Order homogeneous Markov chains. Extensive evaluation results show that the proposed method lead to a 30% improvement on average compared with the state-of-the-art method, in terms of classification accuracy.

关键词： Markov processes Protocols Servers Ciphers Ports (Computers) Encryption

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