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IEEE Transactions on Knowledge and Data Engineering （TKDE） - 论文列表

点击这里查看 IEEE Transactions on Knowledge and Data Engineering 的JCR分区、影响因子等信息
卷期号： 28
发布时间： July
卷期年份： 2016
卷期官网： https://ieeexplore.ieee.org/xpl/tocresult.jsp?isnumber=7484370&issue_denial=true&userType=&issue_login=true
本期论文列表
A Novel Recommendation Model Regularized with User Trust and Item Ratings

Aggregating Crowdsourced Quantitative Claims: Additive and Multiplicative Models

Aspect-Level Influence Discovery from Graphs

CMiner: Opinion Extraction and Summarization for Chinese Microblogs

Entropy Optimized Feature-Based Bag-of-Words Representation for Information Retrieval

Improved Practical Matrix Sketching with Guarantees

Improving Construction of Conditional Probability Tables for Ranked Nodes in Bayesian Networks

Inverted Linear Quadtree: Efficient Top K Spatial Keyword Search

K-Subspaces Quantization for Approximate Nearest Neighbor Search

Label Distribution Learning

Large Margin Distribution Learning with Cost Interval and Unlabeled Data

Learning to Find Topic Experts in Twitter via Different Relations

Microblog Dimensionality Reduction—A Deep Learning Approach

Mining User-Aware Rare Sequential Topic Patterns in Document Streams

Online Subgraph Skyline Analysis over Knowledge Graphs

Personalized Influential Topic Search via Social Network Summarization

Proxies for Shortest Path and Distance Queries

Resolving Multi-Party Privacy Conflicts in Social Media

Scalable Semi-Supervised Learning by Efficient Anchor Graph Regularization

SEDEX: Scalable Entity Preserving Data Exchange

Stock Selection with a Novel Sigmoid-Based Mixed Discrete-Continuous Differential Evolution Algorithm

The Gamma Matrix to Summarize Dense and Sparse Data Sets for Big Data Analytics

Using Hashtag Graph-Based Topic Model to Connect Semantically-Related Words Without Co-Occurrence in Microblogs

Listwise Learning to Rank by Exploring Structure of Objects

OMASS: One Memory Access Set Separation

Correction to “Inference of Regular Expressions for Text Extraction from Examples”