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Density based Collective Spatial keyword Query

Density based Collective Spatial Keyword Query

第8届语义知识与网络国际会议(2012 Eighth International Conference on Semanties,Knowledge and Grids )(SKG2012)

作者： Li Zhang Xiaoping Sun Hai Zhuge Knowledge Grid Lab Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China

Geographic objects with descriptive text are gaining in prevalence in many web services such as Google *** keyword query which combines both the location information and textual description stands out in recent *** works mainly focus on finding top-k Nearest Neighbours where each node has to match the whole querying keywords.A collective query has been proposed to retrieve a group of objects nearest to the query object such that the group's keywords cover query's keywords and has the shortest inner-object *** the previous method does not consider the density of data objects in the spatial *** practice,a group of dense data objects around a query point will be more interesting than those sparse data *** distance of data objects of a group cannot reflect the density of the *** overcome this shortage,we proposed an approximate algorithm to process the collective spatial keyword query based on density and inner *** empirical study shows that our algorithm can effectively retrieve the data objects in dense areas.

关键词： Indexes Spatial databases Approximation algorithms Clustering algorithms Communities Query processing Semantics

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Exploring Patent Transformation Event: Forecasting Patent Transfer Time 26

Exploring Patent Transformation Event: Forecasting Patent Tr...

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26th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2023

作者： Huo, Jinchen Liu, Weidong Li, Yang Cao, Yan Institute of Scientific and Technical Information of China China College of Computer Science Inner Mongolia University China Natl. Loc. Jt. Eng. Research Center of Intelligent Information Processing Technology for Mongolian China Inner Mongolia Key Laboratory of Social Computing and Data Processing China Inner Mongolia Engineering Laboratory for Big Data Analysis Technology China

ISBN: (纸本)9798350331684

As the largest source of technical information around the world, patents are regarded as an essential crystallization and carrier of knowledge and technological innovation. Patent transformation is conducive not only to enhancing economic efficiency, but also to improving productivity and the rational utilization of resources. There is an imbalance between high patent ownership and low transformation rates. We try to predict the occurrence of transformation events from the patent assignment. However, there are some challenges in predicting patent transformation: (1) how to capture transformation features of patents, especially combined with the transfer time factor. (2) how to predict patent transfer time effectively. To address these challenges, a Patent Transfer Time Forecasting Model (PTTFM) is proposed. The model includes: (1) extraction of time-varying features of patents. (2) the patent transfer time is forecast using a Neural Temporal Point Process. By testing the model on patents under different classifications, the experimental results are obtained to show that the proposed model is applicable to predict the timing of patent assignment within a certain time frame, especially one month. Our work may facilitate patent transformation while interpretability is ensured for transformation events. © 2023 IEEE.

关键词： Forecasting

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A new population diversity model in swarm intelligence

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Journal of information and Computational Science 2009年第4期6卷 1891-1898页

作者： Feng, Jiqiang Xie, Weixin Xu, Chen Huang, Jianjun Key Lab. for Intelligent Information Processing Shenzhen University Shenzhen 518060 China Institute of Intelligent Computing Science Shenzhen University Shenzhen 518060 China

Many researchers of swarm intelligence (SI) algorithms take their ideas from physical and biological systems. This approach, however, is mostly qualitative and many ideas remain vague and ill-defined. In this paper, a mathematical framework based on probability theory is presented that enables us to analyze one important aspect of SI algorithms: the population diversity. Firstly the population density is defined for the population in the SI algorithms. The population diversity is then discussed from the point of view of the normal distribution in statistics. We show that there is a close connection between the distribution and population diversity and that the essential structure of population diversity is quite similar to that of the distribution. A detailed construction of the population diversity model is then given that is based on probability distributions and the convergence of the model is theoretically discussed for single peak value case. The paper concludes with a generic numerical example that validates the population diversity model. © 2009 Binary information Press.

关键词： Normal distribution

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Research on patent recommendation method based on graph neural network 26

Research on patent recommendation method based on graph neur...

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26th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2023

作者： Zhang, Enchao Liu, Weidong Liu, Shi Cao, Yan Institute of Scientific and Technical Information of China China College of Computer Science Inner Mongolia University China Natl. Loc. Jt. Eng. Research Center of Intelligent Information Processing Technology for Mongolian China Inner Mongolia Key Laboratory of Social Computing and Data Processing China Inner Mongolia Engineering Laboratory for Big Data Analysis Technology China

ISBN: (纸本)9798350331684

Intellectual property transactions have shown a strong growth momentum in recent years, but the patent transaction market has been plagued by the matching degree of consumers and sellers, resulting in frequent problems such as low patent transformation efficiency and poor transaction quality. This paper proposes a method of recommending patents to consumers by experts to improve the environment of patent transactions. Through the analysis of the past transaction information of the patent, the effective path information of the target is extracted. The graph neural network is used to describe the characteristics and semantics among experts, patents and consumers, and then capture the potential weight among them through the common attention mechanism, and then dynamically integrate them to predict the occurrence of recommendation behavior. The paper makes reasonable use of social information and expert information in the transaction, which significantly improves the rationality and accuracy of expert recommendation. © 2023 IEEE.

关键词： Patents and inventions

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Salient object extraction for user-targeted video content association

Salient object extraction for user-targeted video content as...

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作者： Li, Jia Yu, Han-Nan Tian, Yong-Hong Huang, Tie-Jun Gao, Wen Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Graduate University Chinese Academy of Sciences Beijing 100049 China School of EE and CS Peking University Beijing 100871 China

The increasing amount of videos on the Internet and digital libraries highlights the necessity and importance of interactive video services such as automatically associating additional materials (e.g., advertising logos and relevant selling information) with the video content so as to enrich the viewing experience. Toward this end, this paper presents a novel approach for user-targeted video content association (VCA). In this approach, the salient objects are extracted automatically from the video stream using complementary saliency maps. According to these salient objects, the VCA system can push the related logo images to the users. Since the salient objects often correspond to important video content, the associated images can be considered as content-related. Our VCA system also allows users to associate images to the preferred video content through simple interactions by the mouse and an infrared pen. Moreover, by learning the preference of each user through collecting feedbacks on the pulled or pushed images, the VCA system can provide user-targeted services. Experimental results show that our approach can effectively and efficiently extract the salient objects. Moreover, subjective evaluations show that our system can provide content-related and user-targeted VCA services in a less intrusive way. © 2010 Zhejiang University and Springer-Verlag Berlin Heidelberg.

关键词： Digital libraries

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New image coding scheme with hierarchical representation and adaptive interpolation

New image coding scheme with hierarchical representation and...

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2011 IEEE Visual Communications and Image processing, VCIP 2011

作者： Zhang, Xinfeng Xiong, Ruiqin Ma, Siwei Gao, Wen Institute of Digital Media Peking University Beijing 100871 China Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Graduate University Chinese Academy of Sciences Beijing 100049 China

ISBN: (纸本)9781457713200

In this paper, we propose a new image coding scheme which combines the advantage of hierarchical (i.e. multi-resolution) representation, adaptive interpolation and rate-distortion optimization capability of block-based coding. We divide the coding process into two layers by partitioning the image pixels into four groups with chessboard structure. In the first layer, pixels in one of these partitions are encoded and reconstructed using the state-of-the-art coding scheme. In the second layer, directional adaptive interpolation is employed to predict and code the pixels in the remaining three partitions. Joint mode decision is performed for the co-located macroblocks of these three partitions. Skip mode is introduced to save coding bits for blocks where the interpolation process works very well. Experimental results demonstrate that the proposed coding scheme achieves very promising performance. © 2011 IEEE.

关键词： Image coding

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Flexible navigation in smartphones and tablets using scalable storyboards 13

Flexible navigation in smartphones and tablets using scalabl...

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3rd ACM International Conference on Multimedia Retrieval, ICMR 2013

作者： Zheng, Shuai Herranz, Luis Jiang, Shuqiang Key Lab. of Intelligent Information Processing Chinese Academy of Sciences Beijing 100190 China Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China School of Software Engineering Beijing Jiaotong University Beijing 100044 China

ISBN: (纸本)9781450320337

In this demo paper we present a multiscale browsing interface for handheld devices, in which the user can interactively change the scale of the storyboard to easily adjust the amount of information desired. Conventional and hierarchical storyboards provide one or very few possible lengths. In contrast, scalable storyboards allow the number of images and the storyboard itself to be adapted to the device constraints (e.g. aspect ratio, resolution) and navigation state with much finer granularity. Several levels and modes, including segment of interest, are provided for more intuitive and convenient navigation. © 2013 Authors.

关键词： Aspect ratio

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Online Bayesian multiple kernel bipartite ranking 32

Online Bayesian multiple kernel bipartite ranking

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32nd Conference on Uncertainty in Artificial Intelligence 2016, UAI 2016

作者： Du, Changying Du, Changde Long, Guoping He, Qing Li, Yucheng Beijing100190 China Key Lab of Intelligent Information Processing of CAS Institute of Computing Technology CAS Beijing100190 China Key Laboratory of Optical Astronomy National Astronomical Observatories CAS Beijing100012 China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9781510827806

Bipartite ranking aims to maximize the area under the ROC curve (AUC) of a decision function. To tackle this problem when the data appears sequentially, existing online AUC maximization methods focus on seeking a point estimate of the decision function in a linear or predefined single kernel space, and cannot learn effective kernels automatically from the streaming data. In this paper, we first develop a Bayesian multiple kernel bipartite ranking model, which circumvents the kernel selection problem by estimating a posterior distribution over the model weights. To make our model applicable to streaming data, we then present a kernelized online Bayesian passive-aggressive learning framework by maintaining a variational approximation to the posterior based on data augmentation. Furthermore, to efficiently deal with large-scale data, we design a fixed budget strategy which can effectively control online model complexity. Extensive experimental studies confirm the superiority of our Bayesian multi-kernel approach.

关键词： Budget control

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DMSS:An Attention-Based Deep Learning Model for High-Quality Mass Spectrometry Prediction

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Big Data Mining and Analytics 2024年第3期7卷 577-589页

作者： Yihui Ren Yu Wang Wenkai Han Yikang Huang Xiaoyang Hou Chunming Zhang Dongbo Bu Xin Gao Shiwei Sun Key Lab of Intelligent Information Processing Institute of Computing TechnologyChinese Academy of SciencesBeijing 100190Chinaand with University of Chinese Academy of SciencesBeijing 100049China Syneron Technology Guangzhou 510000China College of Information and Electrical Engineering China Agricultural UniversityBeijing 100083China Computer Science Program ComputerElectrical and Mathematical Sciences and Engineering DivisionKing Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Kingdom of Saudi Arabia Insitute of Computing Technology Chinese Academy of SciencesBeijing 100190China with Western Institute of Computing Technology Chongqing 400000China

Accurate prediction of peptide spectra is crucial for improving the efficiency and reliability of proteomic analysis,as well as for gaining insight into various biological *** this study,we introduce Deep MS Simulator(DMSS),a novel attention-based model tailored for forecasting theoretical spectra in mass *** has undergone rigorous validation through a series of experiments,consistently demonstrating superior performance compared to current methods in forecasting theoretical *** superior ability of DMSS to distinguish extremely similar peptides highlights the potential application of incorporating our predicted intensity information into mass spectrometry search engines to enhance the accuracy of protein *** findings contribute to the advancement of proteomics analysis and highlight the potential of the DMSS as a valuable tool in the field.

关键词： mass spectrometry proteomics machine learning deep learning

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Cross-Layer Power Allocation Scheme for Two-Way Amplify-and-Forward Relaying System

Cross-Layer Power Allocation Scheme for Two-Way Amplify-and-...

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2016 8th IEEE International Conference on Communication Software and Networks(ICCSN 2016)

作者： Quan Yuan Yanjun Hu Hui Zhi Mengmeng He Key Lab of Intelligent Computing and Signal Processing Ministry of Education School of Electronics and Information Engineering Anhui University

Two-way relaying can considerably improve spectral efficiency in relay-assisted bidirectional ***,most existing works focus on physical layer to exploit its resource *** benefits and flexible structures of two-way relaying on datalink layer are much less *** in this paper,the cross-layer optimization for amplify-and-forward(AF)two-way relaying system is studied and an optimal power allocation scheme is *** goal is to find the optimal power allocation factors to maximize the weighted sum effective capacity of two sources in the physical layer while guaranteeing the statistical delay quality-of-service(QoS)requirement for each source in the datalink *** statistical delay Qo S requirement is characterized by the QoS exponentq,which is the only requested information exchanged between the physical layer and the datalink layer in our cross-layer design based *** integrating the concept of effective capacity,the cross-layer optimization problem is equivalent to a weighted sum effective capacity maximization *** problem is formulated into a convex optimization problem,and an algorithm is presented to solve this *** results show that proposed optimal power allocation scheme can achieve better weighted sum effective capacity than equal power allocation scheme and direct transmission scheme,and the relay transmission combined with direct links can get the max weighted sum effective capacity.

关键词： two-way relaying quality-of-service(Qo S) cross-layer optimization power allocation effective capacity

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