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{ "item_title" : "Web and Big Data", "item_author" : [" Jingkuan Song", "Xiaofeng Zhu "], "item_description" : "​KGMA.- Distributed Query Evaluation over Large RDF (Invited Talk).- Classification-based Emoji Recommendation for User Social Networks.- Leveraging Context Information for Joint Entity and Relation Linking.- Community Detection in Knowledge Graph Network with Matrix Factorization Learning.- A Survey of Relation Extraction of Knowledge Graphs.- DSEA.- PEVR: Pose Estimation for Vehicle Re-identification.- The Research of Chinese Ethnical Face Recognition Based on Deep Learning.- Model of Charging Stations Construction and Electric Vehicles Development Prediction.- Boundary Detector Encoder and Decoder with Soft Attention for Video Captioning.", "item_img_path" : "https://covers3.booksamillion.com/covers/bam/3/03/033/981/3030339815_b.jpg", "price_data" : { "retail_price" : "54.99", "online_price" : "54.99", "our_price" : "54.99", "club_price" : "54.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Web and Big Data|Jingkuan Song

Web and Big Data : Apweb-Waim 2019 International Workshops, Kgma and Dsea, Chengdu, China, August 1-3, 2019, Revised Selected Papers

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Overview

​KGMA.- Distributed Query Evaluation over Large RDF (Invited Talk).- Classification-based Emoji Recommendation for User Social Networks.- Leveraging Context Information for Joint Entity and Relation Linking.- Community Detection in Knowledge Graph Network with Matrix Factorization Learning.- A Survey of Relation Extraction of Knowledge Graphs.- DSEA.- PEVR: Pose Estimation for Vehicle Re-identification.- The Research of Chinese Ethnical Face Recognition Based on Deep Learning.- Model of Charging Stations Construction and Electric Vehicles Development Prediction.- Boundary Detector Encoder and Decoder with Soft Attention for Video Captioning.

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Details

  • ISBN-13: 9783030339814
  • ISBN-10: 3030339815
  • Publisher: Springer
  • Publish Date: November 2019
  • Dimensions: 9.21 x 6.14 x 0.27 inches
  • Shipping Weight: 0.42 pounds
  • Page Count: 117

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