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Efficient SPARQL query evaluation via automatic data partitioning

Efficient SPARQL query evaluation via automatic data partiti...

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18th International Conference on database Systems for Advanced Applications, DASFAA 2013

作者： Yang, Tao Chen, Jinchuan Wang, Xiaoyan Chen, Yueguo Du, Xiaoyong School of Information Renmin University of China China Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China MOE China

ISBN: (纸本)9783642374494

The volume of RDF data increases very fast within the last five years, e.g. the Linked Open data cloud grows from 2 billions to 50 billions of RDF triples. With its wonderful scalability, cloud computing platform like Hadoop is a good choice for processing queries over large data sets. Previous works on evaluating SPARQL queries with Hadoop mainly focus on reducing the number of joins through careful split of HDFS files and algorithms for generating Map/Reduce jobs. However, the way of partitioning RDF data could also affect the performance. Specifically, a good partitioning will greatly reduce or even totally avoid cross-node joins and significantly reduce the cost of query evaluation. Based on HadoopDB, this work processes SPARQL queries in a hybrid architecture where Map/Reduce takes charge of the computing tasks and an RDF query engine, RDF-3X, stores the data and evaluates join operations over local data. Based on analysis of query work-loads, we propose a novel algorithm for automatically partitioning RDF data. We also present an approximate solution to physically place the partitions in order to reduce data redundancy. All the proposed approaches are evaluated by extensive experiments over large RDF data sets. © Springer-Verlag 2013.

关键词： Resource Description Framework (RDF)

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Cluster labeling extraction and ranking feature selection for high quality XML pseudo relevance feedback fragments set

Cluster labeling extraction and ranking feature selection fo...

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9th International Conference on Advanced data Mining and Applications, ADMA 2013

作者： Zhong, Minjuan Wan, Changxuan Liu, Dexi Liao, Shumei Luo, Siwen School of Information Technology Jiangxi Key Laboratory of Data and Knowledge Engineering Jiangxi University of Finance and Economics Nanchang China

ISBN: (纸本)9783642539169

In traditional pseudo feedback, the main reason of the topic drift is the low quality of the feedback source. Clustering search results is an effective way to improve the quality of feedback set. For XML data, how to effectively perform clustering algorithm and then identify good xml fragments from the clustering results is a intricate problem. This paper mainly focus on the latter problem. Based on k-mediod clustering results, This work firstly proposes an cluster label extraction method to select candidate relevant clusters. Secondly, multiple ranking features are introduced to assist the related xml fragments identification from the candidate clusters. Top N fragments compose the high quality pseudo feedback set finally. Experimental results on standard INEX test data show that in one hand, the proposed cluster label extraction method could obtain proper cluster key terms and lead to appropriate candidate cluster selection. On the other hand, the presented ranking features are beneficial to the relevant xml fragments identification. The quality of feedback set is ensured. © 2013 Springer-Verlag.

关键词： Clustering algorithms

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Search result diversification based on hierarchical intents 15

Search result diversification based on hierarchical intents

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24th ACM International Conference on Information and knowledge Management, CIKM 2015

作者： Hu, Sha Dou, Zhicheng Wang, Xiaojie Sakai, Tetsuya Wen, Ji-Rong Beijing Key Laboratory of Big Data Management and Analysis Methods China Key Laboratory of Data Engineering and Knowledge Engineering MOE China School of Information Renmin University of China China Waseda University Japan

ISBN: (纸本)9781450337946

A large percentage of queries issued to search engines are broad or ambiguous. Search result diversification aims to solve this problem, by returning diverse results that can fulfill as many different information needs as possible. Most existing intent-aware search result diversification algorithms formulate user intents for a query as a flat list of subtopics. In this paper, we introduce a new hierarchical structure to represent user intents and propose two general hierarchical diversification models to leverage hierarchical intents. Experimental results show that our hierarchical diversification models outperform state-of-the-art diversification methods that use traditional flat subtopics. © 2015 ACM.

关键词： Search engines

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Factor decomposition of regional carbon emissions from energy consumption for China

Factor decomposition of regional carbon emissions from energ...

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3rd International Conference on Energy and Environmental Protection, ICEEP 2014

作者： Qi, Ya-Wei School of Information Technology Jiangxi Key Laboratory of Data and Knowledge Engineering Jiangxi University of Finance and Economics Nanchang China

ISBN: (纸本)9783038351375

This paper calculates the carbon emissions from energy consumption of 30 provinces in China through 2000-2010, and research correlation of factors such as regional economic gap and regional characteristics of carbon emissions in the process of regional economic coordinated development. The LMDI decomposition model is used to decompose the growth rate of China's carbon emissions into 4 types of driving factors, i.e. GDP, industrial pollutants emission intensity, industrial structure and imbalance of regional economic development, to analyze influence of scale effect, technical effect, industrial structure effect and regional spatial structure effect on carbon emissions in the process of China's regional economic development. The results show that: The scale effect is determinants of carbon emissions increasing. The technical effect is the most important force to inhibit the increment of carbon emissions. Industrial structure effect and regional spatial structure effect on carbon emissions are not yet stable, but have a certain pull impact on increasing carbon emissions. © (2014) Trans Tech Publications, Switzerland.

关键词： Energy utilization

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JUFE at INEX 2011 Snippet Retrieval Track

JUFE at INEX 2011 Snippet Retrieval Track

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Lecture Notes in Computer Science

作者： Liu, Dexi Wan, Changxuan Liao, Guoqiong Zhong, Minjuan Liu, Xiping School of Information Technology Jiangxi Key Laboratory of Data and Knowledge Engineering Jiangxi University of Finance and Economics Nanchang China

ISBN: (纸本)9783642357336

Jiangxi University of Finance and Economics (JUFE) submitted 8 runs to the Snippet Retrieval Track at INEX *** report describes an XML snippet retrieval method based on Average Topic Generalization (ATG) model used by JUFE. The basic idea of the ATG is that different element in an XML document plays different role and hence should has distinguishing importance. The ATG model sets a weight automatically to each element according to its tag or path in the XML document. Then, the BM25EW model based on the ATG is proposed to retrieve and rank the relevant elements in an XML document collection. All windows in the most relevant elements are scored and those windows with higher scores are extracted as snippets. By comparing with the runs under different strategies, the performance are discussed and analyzed in detail. © Springer-Verlag Berlin Heidelberg 2012.

关键词： XML

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Research on government information sharing model using blockchain technology 10

Research on government information sharing model using block...

引用

10th International Conference on Information Technology in Medicine and Education, ITME 2019

作者： Zhang, Yiwei Deng, Sanhong Zhang, Yue Kong, Jia School of Information Management Nanjing University Jiangsu Key Laboratory of Data Engineering and Knowledge Service. Nanjing China

ISBN: (纸本)9781728139173

Research Purpose: The distributed, traceable and security of blockchain technology are applicable to the construction of new government information resource models, which could eliminate the barn effect and trust in government information sharing, as well as promoting the transformation of government affairs from management to service, it is also of great significance to the sharing of government information and construction of service-oriented e-government. Propose Methods: By analyzing the current problems of government information sharing, combined with literature research, this paper proposes the theoretical framework and advantages of blockchain technology applied to government information management and sharing, expounds the blockchain-based solution, it also constructs a government information sharing model based on blockchain, and gives implementation strategies at the technical and management levels. Results and Conclusion: The government information sharing model based on the blockchain solution and the transparency of government information can be used as a research framework for information interaction analysis between the government and users. It can also promote the construction and development of information sharing for Chinese government, as well as providing unified information sharing solution at the departmental and regional levels for e-government. © 2019 IEEE.

关键词： Blockchain

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OEE-CFC: A dataset for Open Event Extraction from Chinese Financial Commentary

OEE-CFC: A Dataset for Open Event Extraction from Chinese Fi...

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2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024

作者： Wan, Qizhi Wan, Changxuan Hu, Rong Liu, Dexi Xu, Wenwu Xu, Kang Zou, Meihua Liu, Tao Yang, Jie Xiong, Zhenwei School of Computer and Artificial Intelligence Jiangxi University of Finance and Economics Jiangxi Key Laboratory of Data and Knowledge Engineering China

ISBN: (纸本)9798891761681

To meet application needs, event extraction has shifted from simple entities to unconventional entities serving as event arguments. However, current corpora with unconventional entities as event arguments are limited in event types and lack rich multi-events and shared arguments. Financial commentary not only describes the basic elements of an event but also states the background, scope, manner, condition, result, and tool used for the event, as well as the tense, intensity, and emotions of actions or state changes. Therefore, it is not suitable to develop event types that include only a few specific roles, as these cannot comprehensively capture the event's semantics. Also, there are affluent complex entities serving as event arguments, multiple events, and shared event arguments. To advance the practicality of event extraction technology, this paper first develops a general open event template from the perspective of understanding the meaning of events, aiming to comprehensively reveal useful information about events. This template includes 21 event argument roles, divided into three categories: core event roles, situational event roles, and adverbial roles. Then, based on the constructed event template, Chinese financial commentaries are collected and manually annotated to create a corpus OEE-CFC supporting open event extraction. This corpus includes 17,469 events, 44,221 arguments, 3,644 complex arguments, and 5,898 shared arguments. Finally, based on the characteristics of OEE-CFC, we design four types of prompts, and two models for event argument extraction are developed, with experiments conducted on the prompts. © 2024 Association for Computational Linguistics.

关键词： Semantics

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TYG: A tag-as-you-go online annotation tool for web browsing and navigation

TYG: A tag-as-you-go online annotation tool for web browsing...

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6th International Conference on knowledge Science, engineering and Management, KSEM 2013

作者： Hu, He Du, Xiaoyong School of Information Renmin University of China Beijing 100872 China Key Laboratory of Data Engineering and Knowledge Engineering MOE Beijing 100872 China

ISBN: (纸本)9783642397868

We present TYG (Tag-as-You-Go) in this paper, a chrome browser extension for personal knowledge annotation on standard web pages. We investigate an approach to combine a K-Medoid-style clustering algorithm with the user input to achieve semi-automatic web page annotation. The annotation process supports user-defined tagging schema and comprises an automatic mechanism that is built upon clustering techniques, which can group similar html nodes into clusters corresponding to the user specification. TYG is a prototype system illustrating the proposed approach. Experiments with TYG show that our approach can achieve both efficiency and effectiveness in real world annotation scenarios. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Websites

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Task Offloading Optimization Based on Position Prediction in Pedestrian- Robot Mixed Traffic Flows 8

Task Offloading Optimization Based on Position Prediction in...

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8th IEEE International Conference on Computer and Communications, ICCC 2022

作者： Zheng, Dawen Wang, Lusheng Kai, Caihong Peng, Min Key Laboratory of Knowledge Engineering with Big Data Ministry of Education School of Computer Science and Information Engineering Hefei University of Technology Hefei China

ISBN: (纸本)9781665450515

Service robots play an increasingly important role in people's daily life. The density of pedestrians is large and the movement is irregular in pedestrian-robot mixed traffic flows. Robots are prone to collision with pedestrians, and the tasks to be offloaded are closely related to pedestrians. How to analyze the tasks of robots and select the appropriate roadside unit is an important issue. In this paper, the social force model is used to predict the positions of pedestrians and robots, taking into account the influence of various forces to avoid collisions. A task offloading resource optimization algorithm with position prediction is proposed. According to the predicted information, the size and position distribution of all tasks in the scenario are obtained, and then the neural network trained beforehand based on deep Q-Iearning is used to generate a task offloading strategy. The simulation results show that the running time of the proposed algorithm is very short, and the resource allocation required for task offloading is completed in advance based on the predicted information before robots arriving the corresponding positions. Besides, the algorithm significantly reduces the task offloading delay. © 2022 IEEE.

关键词： Edge computing

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Meta-path Enhanced knowledge Graph Convolutional Network for Recommender Systems 12

Meta-path Enhanced Knowledge Graph Convolutional Network for...

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12th IEEE International Conference on Big knowledge, ICBK 2021

作者： Wang, Ru Wu, Meng Ji, Shengwei Hefei University of Technology Key Laboratory of Knowledge Engineering With Big Data Ministry of Education School of Computer Science and Information Engineering Hefei China

ISBN: (纸本)9781665438582

knowledge Graph (KG) is a directed heterogeneous information network that contains a large number of entities and relations, which is widely used as effective side information in rec-ommender systems. Moreover, in recommender systems, the Graph Convolutional Network (GCN) model is introduced to mine the relatedness between entities in a KG because of its efficiency in extracting spatial features on topological graphs. The knowledge Graph Convolutional Network (KGCN) model up-dates the embedding of a currently positioned entity by aggregating the information of adjacent entities selected randomly. Never-theless, it has two limititations: 1) the information of neighbors se-lected randomly cannot accurately represent the current entity in the KG;2) the model is hard to converge as graph features (i.e. The spatial relation features and semantic information features of en-tities in the KG) grow. To solve these limitations, in this paper, a meta-path (i.e., a sequence of artificially constructed relationships) is introduced into the selection of neighbors in the KGCN model to enhance the representation of each entity. Furthermore, two construction methods of the meta-path - constructing a meta-path based on the same relation (KGCN-SP) and the characteris-tics of KG (KGCN-MP) -are proposed. The experiments based on three real-world datasets demonstrate that the neighbor selection based on the meta-path is able to collect more accurate infor-mation from a KG and improve the recommendation performance effectively. © 2021 IEEE.

关键词： knowledge graph

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