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context-aware Semantic Type Identification for Relational Attributes

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Journal of Computer Science & Technology 2023年第4期38卷 927-946页

作者：丁玥郭雨荷卢卫李海翔张美慧李晖潘安群杜小勇 Key Laboratory of Data Engineering and Knowledge Engineering of Ministry of Education Renmin University of China Beijing 100872China School of Information Renmin University of ChinaBeijing 100872China Tencent(Beijing)Technology Company Limited Beijing 100080China School of Computer Science and Technology Beijing Institute of TechnologyBeijing 100081China College of Computer Science and Technology Guizhou UniversityGuiyang 550025China Tencent(Shenzhen)Technology Company Limited Shenzhen 518057China

Identifying semantic types for attributes in relations,known as attribute semantic type(AST)identification,plays an important role in many data analysis tasks,such as data cleaning,schema matching,and keyword search in ***,due to a lack of unified naming standards across prevalent information systems(*** islands),AST identification still remains as an open *** tackle this problem,we propose a context-aware method to figure out the ASTs for relations in this *** transform the AST identification into a multi-class classification problem and propose a schema context aware(SCA)model to learn the representation from a collection of relations associated with attribute values and schema *** on the learned representation,we predict the AST for a given attribute from an underlying relation,wherein the predicted AST is mapped to one of the labeled *** improve the performance for AST identification,especially for the case that the predicted semantic types of attributes are not included in the labeled ASTs,we then introduce knowledge base embeddings(***)to enhance the above representation and construct a schema context aware model with knowledge base enhanced(SCA-KB)to get a stable and robust *** experiments based on real datasets demonstrate that our context-aware method outperforms the state-of-the-art approaches by a large margin,up to 6.14%and 25.17%in terms of macro average F1 score,and up to 0.28%and 9.56%in terms of weighted F1 score over high-quality and low-quality datasets respectively.

关键词： attribute semantic type(AST)identification context-aware semantic embedding knowledge base embedding

A Deep Learning Based Approach for context-aware Multi-Criteria Recommender Systems

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Computer Systems Science & Engineering 2023年第1期44卷 471-483页

作者： Son-Lam VU Quang-Hung LE Faculty of Information Technology Quy Nhon UniversityQuy Nhon CityVietnam

Recommender systems are similar to an informationfiltering system that helps identify items that best satisfy the users’demands based on their pre-ference ***-aware recommender systems(CARSs)and multi-criteria recommender systems(MCRSs)are extensions of traditional recommender *** have integrated additional contextual information such as time,place,and so on for providing better ***,the majority of CARSs use ratings as a unique criterion for building ***,MCRSs utilize user preferences in multiple criteria to better generate *** to now,how to exploit context in MCRSs is still an open *** paper proposes a novel approach,which relies on deep learning for context-aware multi-criteria recommender *** apply deep neural network(DNN)mod-els to predict the context-aware multi-criteria ratings and learn the aggregation *** conduct experiments to evaluate the effect of this approach on the real-world dataset.A significant result is that our method outperforms other state-of-the-art methods for recommendation effectiveness.

关键词： Recommender systems context-aware multi-criteria deep learning deep neural network

Relevant Visual Semantic context-aware Attention-Based Dialog

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Computers, Materials & Continua 2023年第8期76卷 2337-2354页

作者： Eugene Tan Boon Hong Yung-Wey Chong Tat-Chee Wan Kok-Lim Alvin Yau National Advanced IPv6 Centre Universiti Sains MalaysiaPenangMalaysia Lee Kong Chian Faculty of Engineering and Science(LKCFES) Universiti Tunku Abdul RahmanSungai LongSelangorMalaysia

The existing dataset for visual dialog comprises multiple rounds of questions and a diverse range of image ***,it faces challenges in overcoming visual semantic limitations,particularly in obtaining sufficient context from visual and textual aspects of *** paper proposes a new visual dialog dataset called Diverse History-Dialog(DS-Dialog)to address the visual semantic limitations faced by the existing ***-Dialog groups relevant histories based on their respective Microsoft Common Objects in context(MSCOCO)image categories and consolidates them for each ***,each MSCOCO image category consists of top relevant histories extracted based on their semantic relationships between the original image caption and historical *** relevant histories are consolidated for each image,and DS-Dialog enhances the current dataset by adding new context-aware relevant history to provide more visual semantic context for each *** new dataset is generated through several stages,including image semantic feature extraction,keyphrase extraction,relevant question extraction,and relevant history dialog *** DS-Dialog dataset contains about 2.6 million question-answer pairs,where 1.3 million pairs correspond to existing VisDial’s question-answer pairs,and the remaining 1.3 million pairs include a maximum of 5 image features for each VisDial image,with each image comprising 10-round relevant question-answer ***,a novel adaptive relevant history selection is proposed to resolve missing visual semantic information for each ***-Dialog is used to benchmark the performance of previous visual dialog models and achieves better performance than previous ***,the proposed DSDialog model achieves an 8% higher mean reciprocal rank(MRR),11% higher R@1%,6% higher R@5%,5% higher R@10%,and 8% higher normalized discounted cumulative gain(NDCG)compared to ***-Dialog also achieves approximately 1 point improvement o

关键词： Visual dialog context-aware relevant history computer vision natural language processing

context-aware Social Media User Sentiment Analysis

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Tsinghua Science and Technology 2020年第4期25卷 528-541页

作者： Bo Liu Shijiao Tang Xiangguo Sun Qiaoyun Chen Jiuxin Cao Junzhou Luo Shanshan Zhao the School of Computer Science and Engineering Southeast UniversityNanjing 211189China the Key Laboratory of Computer Network and Information of Ministry of Education of China Nanjing 211189China Microsoft Research Asia Suzhou 215000China the School of Cyber Science and Engineering Southeast UniversityNanjing 211189China the Department of Computer Science and Creative Technologies University of the West of EnglandBristolBS161QYUK

The user-generated social media messages usually contain considerable multimodal *** messages are usually short and lack explicit sentiment ***,we can understand the sentiment associated with such messages by analyzing the context,which is essential to improve the sentiment analysis ***,majority of the existing studies consider the impact of contextual information based on a single data *** this study,we propose a novel model for performing context-aware user sentiment *** model involves the semantic correlation of different modalities and the effects of tweet context *** on our experimental results obtained using the Twitter dataset,our approach is observed to outperform the other existing methods in analysing user sentiment.

关键词： social media sentiment analysis multimodal data context-aware topic model

context-aware location discovery exchange in a ubiquitous environment

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The Journal of China Universities of Posts and Telecommunications 2012年第6期19卷 73-78页

作者： LIU Qi GAO Feng Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science & Technology School of Information Science and Technology Shijiazhuang Tiedao University

It becomes challenging in order to represent, discover and exchange location information in a ubiquitous environment due to dynamic movement and interaction between mobile nodes inside. In this paper, a new method is presented in order to make location information context-aware so that organizing the format of location information and maintaining the communication between direct connected nodes in a ubiquitous environment is enabled. The structure of a contextual location information repository and a context information communication protocol is manipulated to implement the proposed features. According to the simulation results in network simulator version2 （NS2）, the new method has depicted good discovery success ~nd consumed efficient service discovery bandwidth. Other network traffic, i.e. transmission control protocol, （TCP） has been simulated in the scenarios but the new location-aware method has shown its robustness with continuous context discovery process.

关键词： context-aware ubiquitous computing location-aware service discovery

FCT: a fully-distributed context-aware trust model for location based service recommendation

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Science China(Information Sciences) 2017年第8期60卷 101-116页

作者： Zhiquan LIU Jianfeng MA Zhongyuan JIANG Yinbin MIAO School of Computer Science and Technology Xidian University School of Cyber Engineering Xidian University

With the popularity of location based service(LBS), a vast number of trust models for LBS recommendation(LBSR) have been proposed. These trust models are centralized in essence, and the trusted third party may collude with malicious service providers or cause the single-point failure problem. This work improves the classic certified reputation(CR) model and proposes a novel fully-distributed context-aware trust(FCT)model for LBSR. Recommendation operations are conducted by service providers directly and the trusted third party is no longer required in our FCT model. Besides, our FCT model also supports the movements of service providers due to its self-certified characteristic. Moreover, for easing the collusion attack and value imbalance attack, we comprehensively consider four kinds of factor weights, namely number, time decay, preference and context weights. Finally, a fully-distributed service recommendation scenario is deployed, and comprehensive experiments and analysis are conducted. The results indicate that our FCT model significantly outperforms the CR model in terms of the robustness against the collusion attack and value imbalance attack, as well as the service recommendation performance in improving the successful trading rates of honest service providers and reducing the risks of trading with malicious service providers.

关键词： trust model fully-distributed context-aware location based service service recommendation

context-aware Using Carrier Phase for Adaptive MEMS IMU / GNSS Filtering in Deep Urban Navigation

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Journal of Harbin Institute of Technology(New Series) 2013年第2期20卷 45-49页

作者： Hua Liu Tong Liu Hang Guo School of Automation Beijing Institute of Technology Academy of Space Technology Nanchang University

context-aware is becoming standard on the most mobile navigation devices. The performance of MEMS IMU / GNSS gains significant benefits from context information in terms of improvement of filter 's adaptive capability. A context-aware algorithm using differential carrier phase was proposed to recognize a mobile MEMS IMU / GNSS equipped vehicle's stationary,slow moving or fast moving status. The corresponding context error in awarding was analyzed and consequently conducted two fading factors based on the analysis. The factors were applied in the system's adaptive filter with targeting applications in deep urban where severe multipath presents. The dense urban field test shows that the false alarm of proposed context-aware algorithm is less than 5% and the adaptive filtering can achieve around 15% improvement in terms of 1σ in two-dimension position accuracy.

关键词： MEMS IMU GNSS context-aware Adaptive Filtering

context-aware Animation Data Description and Interaction Method Based on Sketch

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Journal of Beijing Institute of Technology 2019年第1期28卷 8-16页

作者： Fang Liu Zhaoxu Sun Cuixia Ma Hongan Wang Institute of Software Chinese Academy of Sciences

In this paper,an interactive method is proposed to describe computer animation data and accelerate the process of animation ***,a semantic model and a resource description framework(RDF)are utilized to analyze and describe the relationships between animation ***,a novel context model which is able to keep the context-awareness was proposed to facilitate data organization and *** our context model,all the main animation elements in a scene are operated as a *** sketch is utilized as the main interactive method to describe the relationships between animation data,edit the context model and make some other user ***,a context-aware computer animation data description system based on sketch is generated and it also works well in animation generation process.

关键词： animation data description sketch interactive animation context-aware

A novel context-aware RPL algorithm based on a triangle module operator

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Frontiers of Information Technology & Electronic Engineering 2021年第12期22卷 1583-1597页

作者： Yanan CAO Hao YUAN Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission Tianjin Normal UniversityTianjin 300387China Chinese People's Liberation Army Unit 61846 Zhuozhou 072750China

For the use in low-power and lossy networks(LLNs)under complex and harsh communication conditions,the routing protocol for LLNs(RPL)standardized by the Internet Engineering Task Force is specially *** improve the performance of LLNs,we propose a novel context-aware RPL algorithm based on a triangle module operator(CAR-TMO).A novel composite context-aware routing metric(CA-RM)is designed,which synchronously evaluates the residual energy index,buffer occupancy ratio of a node,expected transmission count(ETX),delay,and hop count from a candidate parent to the ***-RM considers the residual energy index and buffer occupancy ratio of the candidate parent and its preferred parent in a recursive manner to reduce the effect of upstream parents,since farther paths are ***-RM comprehensively uses the sum,mean,and standard deviation values of ETX and delay of links in a path to ensure a better ***,in CAR-TMO,the membership function of each routing metric is ***,a comprehensive membership function is constructed based on a triangle module operator,the membership function of each routing metric,and a comprehensive context-aware objective function.A novel mechanism for calculating the node rank and the mechanisms for preferred parent selection are ***,theoretical analysis and simulation results show that CAR-TMO outperforms several state-of-the-art RPL algorithms in terms of the packet delivery ratio and energy efficiency.

关键词： Triangle module operator Membership function context-aware Routing protocol for low-power and lossy networks(RPL) Routing metrics