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- tutorialNovember 2019
Machine Learning on Graphs with Kernels
CIKM '19: Proceedings of the 28th ACM International Conference on Information and Knowledge ManagementPages 2983–2984https://doi.org/10.1145/3357384.3360986Graphs are becoming a dominant structure in current information management with many domains involved, including social networks, chemistry, biology, etc. Many real-world problems require applying machine learning tasks to graph-structured data. Graph ...
- tutorialNovember 2019
Learning-Based Methods with Human-in-the-Loop for Entity Resolution
CIKM '19: Proceedings of the 28th ACM International Conference on Information and Knowledge ManagementPages 2969–2970https://doi.org/10.1145/3357384.3360316This tutorial is intended for researchers and practitioners working in the data integration area and, in particular, entity resolution (ER), which is a sub-area focused on linking entities across heterogeneous datasets. We outline the ideal requirements ...
- abstractNovember 2019
Knowledge-Driven Analytics and Systems Impacting Human Quality of Life
CIKM '19: Proceedings of the 28th ACM International Conference on Information and Knowledge ManagementPages 2989–2990https://doi.org/10.1145/3357384.3358799The advent of artificial intelligence (AI), Internet of Things (IoT), powerful computational hardwares like graphics processing units, affordable sensing devices like smart bands, wearables, smartphones pave ways for large number of useful and ...
- short-paperNovember 2019
Similarity-Aware Network Embedding with Self-Paced Learning
CIKM '19: Proceedings of the 28th ACM International Conference on Information and Knowledge ManagementPages 2113–2116https://doi.org/10.1145/3357384.3358163Network embedding, which aims to learn low-dimensional vector representations for nodes in a network, has shown promising performance for many real-world applications, such as node classification and clustering. While various embedding methods have been ...
- short-paperNovember 2019
Multi-scale Trajectory Clustering to Identify Corridors in Mobile Networks
CIKM '19: Proceedings of the 28th ACM International Conference on Information and Knowledge ManagementPages 2253–2256https://doi.org/10.1145/3357384.3358157Deployment and management of large-scale mobile edge computing infrastructure in 5G networks has created a major challenge for mobile operators. The ability to extract common users' trajectories (i.e., corridors) in mobile networks helps mobile ...
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- short-paperNovember 2019
ED2: A Case for Active Learning in Error Detection
CIKM '19: Proceedings of the 28th ACM International Conference on Information and Knowledge ManagementPages 2249–2252https://doi.org/10.1145/3357384.3358129State-of-the-art approaches formulate error detection as a semi-supervised classification problem. Recent research suggests that active learning is insufficiently effective for error detection and proposes the usage of neural networks and data ...
- short-paperNovember 2019
Adaptive Feature Redundancy Minimization
CIKM '19: Proceedings of the 28th ACM International Conference on Information and Knowledge ManagementPages 2417–2420https://doi.org/10.1145/3357384.3358112Most existing feature selection methods select the top-ranked features according to certain criterion. However, without considering the redundancy among the features, the selected ones are frequently highly correlated with each other, which is ...
- research-articleNovember 2019
Approximation Algorithms for Coordinating Ad Campaigns on Social Networks
CIKM '19: Proceedings of the 28th ACM International Conference on Information and Knowledge ManagementPages 339–348https://doi.org/10.1145/3357384.3358063We study a natural model of coordinated social ad campaigns over a social network, based on models of Datta et al. and Aslay et al. Multiple advertisers are willing to pay the host - up to a known budget - per user exposure, whether that exposure is ...
- research-articleNovember 2019
HeteSpaceyWalk: A Heterogeneous Spacey Random Walk for Heterogeneous Information Network Embedding
CIKM '19: Proceedings of the 28th ACM International Conference on Information and Knowledge ManagementPages 639–648https://doi.org/10.1145/3357384.3358061Heterogeneous information network (HIN) embedding has gained increasing interests recently. However, the current way of random-walk based HIN embedding methods have paid few attention to the higher-order Markov chain nature of meta-path guided random ...
- research-articleNovember 2019
Streamline Density Peak Clustering for Practical Adoptions
CIKM '19: Proceedings of the 28th ACM International Conference on Information and Knowledge ManagementPages 49–58https://doi.org/10.1145/3357384.3358053Since Density Peak Clustering (DPC) algorithm was proposed in 2014, it has drawn lots of interest in various domains. As a clustering method, DPC features superior generality, robustness, flexibility and simplicity. There are however two main roadblocks ...
- research-articleNovember 2019
Reinforcement Learning with Sequential Information Clustering in Real-Time Bidding
CIKM '19: Proceedings of the 28th ACM International Conference on Information and Knowledge ManagementPages 1633–1641https://doi.org/10.1145/3357384.3358027Display advertising is a billion dollar business which is the primary income of many companies. In this scenario, real-time bidding optimization is one of the most important problems, where the bids of ads for each impression are determined by an ...
- research-articleNovember 2019
Online Kernel Selection via Tensor Sketching
CIKM '19: Proceedings of the 28th ACM International Conference on Information and Knowledge ManagementPages 801–810https://doi.org/10.1145/3357384.3358019Online kernel selection is a more complex problem compared with offline kernel selection, which intermixes training and selection at each round and requires a sublinear regret and low computational complexities. But existing online kernel selection ...
- research-articleNovember 2019
New Online Kernel Ridge Regression via Incremental Predictive Sampling
CIKM '19: Proceedings of the 28th ACM International Conference on Information and Knowledge ManagementPages 791–800https://doi.org/10.1145/3357384.3358004Online kernel ridge regression via existing sampling approaches, which aim at approximating the kernel matrix as accurately as possible, is independent of learning and has a cubic time complexity with respect to the sampling size for updating ...
- research-articleNovember 2019
Robust Embedded Deep K-means Clustering
CIKM '19: Proceedings of the 28th ACM International Conference on Information and Knowledge ManagementPages 1181–1190https://doi.org/10.1145/3357384.3357985Deep neural network clustering is superior to the conventional clustering methods due to deep feature extraction and nonlinear dimensionality reduction. Nevertheless, deep neural network leads to a rough representation regarding the inherent ...
- research-articleNovember 2019
CoRide: Joint Order Dispatching and Fleet Management for Multi-Scale Ride-Hailing Platforms
- Jiarui Jin,
- Ming Zhou,
- Weinan Zhang,
- Minne Li,
- Zilong Guo,
- Zhiwei Qin,
- Yan Jiao,
- Xiaocheng Tang,
- Chenxi Wang,
- Jun Wang,
- Guobin Wu,
- Jieping Ye
CIKM '19: Proceedings of the 28th ACM International Conference on Information and Knowledge ManagementPages 1983–1992https://doi.org/10.1145/3357384.3357978How to optimally dispatch orders to vehicles and how to trade off between immediate and future returns are fundamental questions for a typical ride-hailing platform. We model ride-hailing as a large-scale parallel ranking problem and study the joint ...
- research-articleNovember 2019
Privacy Preserving Approximate K-means Clustering
CIKM '19: Proceedings of the 28th ACM International Conference on Information and Knowledge ManagementPages 1321–1330https://doi.org/10.1145/3357384.3357969Privacy preserving computation is of utmost importance in a cloud computing environment where a client often requires to send sensitive data to servers offering computing services over untrusted networks. Eavesdropping over the network or malware at the ...
- research-articleNovember 2019
Batch Mode Active Learning for Semantic Segmentation Based on Multi-Clue Sample Selection
CIKM '19: Proceedings of the 28th ACM International Conference on Information and Knowledge ManagementPages 831–840https://doi.org/10.1145/3357384.3357968Large labeled datasets are required for training a powerful semantic segmentation model. However, it is very expensive to construct pixel-wise annotated images. In this work, we propose a general batch mode active learning algorithm for semantic ...
- research-articleNovember 2019
Author Set Identification via Quasi-Clique Discovery
CIKM '19: Proceedings of the 28th ACM International Conference on Information and Knowledge ManagementPages 771–780https://doi.org/10.1145/3357384.3357966Author identification based on heterogeneous bibliographic networks, which is to identify potential authors given an anonymous paper, has been studied in recent years. However, most of the existing works merely consider the relationship between authors ...
- research-articleNovember 2019
Hashing Graph Convolution for Node Classification
CIKM '19: Proceedings of the 28th ACM International Conference on Information and Knowledge ManagementPages 519–528https://doi.org/10.1145/3357384.3357922Convolution on graphs has aroused great interest in AI due to its potential applications to non-gridded data. To bypass the influence of ordering and different node degrees, the summation/average diffusion/aggregation is often imposed on local receptive ...
- research-articleNovember 2019
Identifying Facet Mismatches In Search Via Micrographs
CIKM '19: Proceedings of the 28th ACM International Conference on Information and Knowledge ManagementPages 1663–1672https://doi.org/10.1145/3357384.3357911E-commerce search engines are the primary means by which customers shop for products online. Each customer query contains multiple facets such as product type, color, brand, etc. A successful search engine retrieves products that are relevant to the ...