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29th ACM International Conference on Multimedia, MM 2021

作者： Hao, Qianxiu Xu, Qianqian Yang, Zhiyong Huang, Qingming Key Laboratory of Intelligent Information Processing Institute of Computing Technology CAS Beijing China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing China Artificial Intelligence Research Center Peng Cheng Laboratory Shenzhen China

ISBN: (纸本)9781450386517

Heterogeneous information networks (HINs) have become a popular tool to capture complicated user-item relationships in recommendation problems in recent years. As a typical instantiation of HINs, meta-path is introduced in search of higher-level representations of user-item interactions. Though remarkable success has been achieved along this direction, existing meta-path-based recommendation methods face at least one of the following issues: 1) existing methods merely adopt simple meta-path fusion rules, which might be insufficient to exclude inconsistent information of different meta-paths that may hurt model performance;2) the representative power is limited by shallow/stage-wise formulations. To solve these issues, we propose an end-to-end and unified embedding-based recommendation framework with graph-based learning. To address 1), we propose a flexible fusion module to integrate meta-path-based similarities into relative similarities between users and items. To address 2), we take advantage of the powerful representative ability of deep neural networks to learn more complicated and flexible latent embeddings. Finally, empirical studies on real-world datasets demonstrate the effectiveness of our proposed method. © 2021 ACM.

关键词： Embeddings

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Design and Development of an Efficient Traceability System for Greek Kiwifruit 10

Design and Development of an Efficient Traceability System f...

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10th International Conference on Information and Communication Technologies in Agriculture, Food and Environment, HAICTA 2022

作者： Margariti, Spiridoula V. Salmas, Dimitris Pachoulas, George Schismenos, Paraskevas Baltzoi, Penelope Fotia, Konstantina Karipidis, Charalampos Tsirogiannis, Ioannis L. Stylios, Chrysostomos Laboratory of Knowledge and Intelligent Computing Department of Informatics and Telecommunications University of Ioannina Kostaki Arta47100 Greece University of Ioannina Department of Agriculture Arta47100 Greece Industrial Systems Institute Athena R.C. Platani PatrasGR26504 Greece

It is vital to establish and use a traceability system in the fresh supply-production chain. It is a consumer requirement, a useful tool for farmers to add value to their products and a single way to ensure the quality of food products. Nowadays, traceability systems incorporate Information and Communication Technologies (ICT), such as IoT, cloud computing and Big Data, aiming to provide cost-effective production and traceability functionalities. IoT and cloud computing cover a range of different technologies that can be used to satisfy traceability requirements and facilitate rational decision making. In this work, we exploit the capabilities of these technologies and propose a smart traceability framework for kiwifruit. We design, develop, and apply the proposed scheme to a Greek kiwifruit farming. The results show that traceability requirements for transparency, safety and quality are satisfied. Moreover, this implementation provides meaningful insights related to intelligent fresh fruit traceability. © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0)

关键词： Internet of things

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Socio-Natural Thought Semantic Link Network: A Method of Semantic Networking in the Cyber Physical Society

Socio-Natural Thought Semantic Link Network: A Method of Sem...

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International Conference on Advanced Information Networking and Applications (AINA)

作者： Hai Zhuge Knowledge Grid Research Group Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China

ISBN: (纸本)9781424466955;9780769540184

Humans have been recognizing, establishing and making use of various relations consciously and unconsciously since the formation of human society. Waving and maintaining various relations accompany everyone's life. Humans' social behaviors create or emphasize relations. Various networks evolve with the development of society. Some relational networks gradually become independent of individuals' life during evolution so that they become a part of knowledge and culture sharable cross generations. The study of social relations trace back to the age of Laozi (576-BC), Confucius (551-479 BC), Thales (624 BC-546 BC) and Socrates (469 BC-399 BC). The formal definition of general relation traces to the invention of set theory in 1874. Humans have intelligence to observe and participate in social processes, to think, and to know the effect of establishing a relation. Humans can also actively select appropriate relations and persons according to requirement, situation and social rules. Machines are obviously limited in these abilities. Various graph-based models have been used to connect resources in the cyber space. Two issues are fundamental: (1) machines know little relation in human society and the nature, data structures in machines are for machines to process not for humans to read, so it is not realistic to expect machines to discover social and natural laws and resolve relevant issues without human instruction; and, (2) machines are hard to know the effect of establishing and making use of relations, and to explain computing result according to society and nature. The cause is that machines do not have any worldview. Connecting various networks and machines with nature, society, and even human minds can create a new world where individuals have semantic images that can enhance mutual understanding. The semantic images can be constructed by a Semantic Link Network SLN consisting of nodes with rich semantics, semantic links between nodes, and rules for reasoning, influe

关键词： Humans Societies Libraries Hypertext systems Spatial databases intelligent networks Information processing Computers Set theory Machine intelligence

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Automatic Life Event Tree Generation for Older Adults 1

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24th International Conference on Human-Computer Interaction, HCII 2022

作者： Gui, Fang Wu, Xi Hu, Min Yang, Jiaoyun School of Computer Science and Information Engineering Hefei University of Technology Hefei China Key Laboratory of Knowledge Engineering with Big Data of Ministry of Education Hefei University of Technology Hefei China National Smart Eldercare International S&T Cooperation Base Hefei University of Technology Hefei China Laboratory of Affective Computing and Advanced Intelligent Machine Hefei University of Technology Hefei China Intelligent Interconnected Systems Laboratory of Anhui Province Hefei University of Technology Hefei China

ISBN: (数字)9783031179020

ISBN: (纸本)9783031179013

Studies have shown that learning personal stories could help provide individualized eldercare services. However, personal stories are often disordered because of the scattered collection, including informal interviews or daily interactions, which brings difficulties in acquiring valuable information quickly. One solution to this problem is to extract events from personal stories and automatically organize them in chronological order. Events extracted by current methods from social media or news corpus are mainly organized in a linear structure. These works usually focus on the event time and ignore the consistency of event contents when organizing events. This paper aims to organize events into a tree structure based on an event network, with stem nodes representing key event topics and branch nodes representing detailed events. Social workers or caregivers can clarify the life experience of the older adults quickly through the event tree and have a preliminary understanding of them. The experiments show that the event tree generated by our method has a better performance in consistency than current event organization methods. A survey study shows that our method achieves the highest logical coherence for the event tree branches compared with other algorithms. © 2022, Springer Nature Switzerland AG.

关键词： Trees (mathematics)

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Completeness of Query Operations on Resource Spaces

Completeness of Query Operations on Resource Spaces

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International Conference on Semantics, knowledge and Grid (SKG)

作者： Hai Zhuge Hai Zhuge Erlin Yao Erlin Yao China Knowledge Grid Research Group Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

A great variety of languages can be designed by different people for different purposes to operate resource spaces. Two fundamental issues are: can we design more operations in addition to existing operations? and, how many operations are sufficient or necessary? This paper solves these problems by investigating the theoretical basis for determining how complete a selection capability is provided in a resource operation sublanguage independent of any host language. The result is very useful to the design and analysis of operating languages.

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A computing Model for Concept Fusing and Document Classification

A Computing Model for Concept Fusing and Document Classifica...

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International Conference on Semantics, knowledge and Grid (SKG)

作者： Nan Zhang Nan Zhang Chao He Chao He China Knowledge Grid Research Group Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

Effective document classification is a long-pursued goal in knowledge management. This paper proposes a novel hybrid approach of semantic representation and statistical measurements. Document is divided into content segments first. By Formal Concept Analysis (FCA), their semantic links with standard concept identifiers are built up whose weights are calculated statistically. In this way, effective concept fusing and document classification can be achieved. In addition, a semantic overlay for specific documents will be constructed via concept fusing. Experiments show our approach is feasible and effective.

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The knowledge Grid and Its Methodology

The Knowledge Grid and Its Methodology

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International Conference on Semantics, knowledge and Grid (SKG)

作者： Hai Zhuge China Knowledge Grid Research Group Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China

In the human, society, interconnection environment and systems methodology perspectives, this paper answers the following questions: What are the knowledge Grid and its distinguished features? What are its methodology... 详细信息

关键词： Humans Social network services Environmental economics Biological system modeling Peer to peer computing Grid computing Man machine systems IP networks Semantic Web knowledge management

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Automatizing the broken bar detection process via Short Time Fourier Transform and two-dimensional Piecewise Aggregate Approximation representation

Automatizing the broken bar detection process via Short Time...

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作者： Georgoulas, George Karvelis, Petros Stylios, Chysostomos D. Tsoumas, Ioannis P. Antonino-Daviu, Jose Alfonso Climente-Alarcon, Vicente Laboratory of Knowledge and Intelligent Computing Department of Computer Engineering TEI of Epirus Artas Kostakioi47100 Greece Larges Drives R and D Department Siemens Industry Sector - Drive Technologies Nuremberg Germany Instituto de Ingeniería Energética Universitat Politècnica de València Valencia Spain

ISBN: (纸本)9781479956982

This work presents an automated approach for detecting broken rotor bars in induction machines using the stator current during startup operation. The currents are analyzed using the well-known Short Time Fourier Transform (STFT) producing a two-dimensional time-frequency representation. This representation contains information regarding the presence of a characteristic transient component but requires further processing before it can be fed into a standard classification algorithm. In this work, this part is performed using the two dimensional extension of Piecewise Aggregate Approximation (PAA) that can deal with the two dimensional representation of STFT. The results (with both simulated and experimental data) suggest that the method can be used for the automatic detection of broken bars and even for determining the fault severity. Moreover, its low computational burden makes it ideal for its future use in online, unsupervised systems, as well as in portable condition monitoring devices. © 2014 IEEE.

关键词： Condition monitoring

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Topic discovery of clusters from documents with geographical location

Topic discovery of clusters from documents with geographical...

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作者： Zhang, Li Sun, Xiaoping Zhuge, Hai Knowledge Grid Lab Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China Nanjing University of Posts and Telecommunications Nanjing Jiangsu China State Key Laboratory of Software Engineering Wuhan University Wuhan Hubei China University of Chinese Academy of Sciences Beijing China

As smart phones with GPS become popular, more and more textual documents with geographical locations are published on the Web. Keyword-based location services like vehicle navigation, tour planning, nearby object querying, and location pattern discovering of spatial objects are becoming popular and important. However, processing both text and geographical locations brings more challenges to information-retrieval techniques. In this paper, we focus on the problem of finding textual topics of clusters containing spatial objects with text descriptions. The key is how to combine clustering techniques with topic-retrieval models to integrate both geo-location information and text information. We investigated methods that combine clustering methods with the Latent Dirichlet Allocation model to discover topics of clusters of documents with geo-locations. Six different methods of combination are investigated, each having outputs with different meanings, which can be further leveraged to answer different types of queries over spatial documents. Experiments are conducted on both synthetic and real data. The results show that the combination of the probabilistic topic model with clustering algorithms is an efficient and effective way to discover meaningful clusters in different facets and levels of documents with textual and geographical information. © 2015 John Wiley & Sons, Ltd.

关键词： Cluster analysis

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Multiscale Bilateral Attention Fusion Network for Pansharpening

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第11期5卷 5828-5843页

作者： Guo, Zhongyuan Li, Jiawei Lei, Jia Liu, Jinyuan Zhou, Shihua Wang, Bin Kasabov, Nikola K. Dalian University Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian116622 China University of the Science and Technology Beijing School of Computer and Communication Engineering Beijing100083 China Dalian University of Technology School of Mechanical Engineering Dalian116024 China Auckland University of Technology Knowledge Engineering and Discovery Research Institute Auckland1061 New Zealand University of Ulster Intelligent Systems Research Center LondonderryBT48 7JL United Kingdom Bulgarian Academy of Sciences IICT Sofia1000 Bulgaria

High-resolution multispectral (HRMS) images combine spatial and spectral information originating from panchromatic (PAN) and reduced-resolution multispectral (LRMS) images. Pansharpening performs well and is widely used to obtain HRMS images. However, most pansharpening approaches determine the ratio of PAN and LRMS images through direct interpolation, which may introduce artifacts and distort the color of the fused results. To address this issue, an unsupervised progressive pansharpening framework, MSBANet, is proposed, which adopts a multistage fusion strategy. Each stage contains an attention interactive extraction module (AIEM) and a multiscale bilateral fusion module (MBFM). The AIEM extracts spatial and spectral features from input images and captures the correlations between features. The MBFM can efficiently integrate information from the AIEM and improve MSBANet context awareness. We design a hybrid loss function that enhances the ability of the fusion network to store spectral and texture details. In qualitative and quantitative experimental studies on four datasets, MSBANet outperformed state-of-the-art pansharpening techniques. The code will be released. © 2024 IEEE.

关键词： Data mining

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