Exploring Context and Content Links in Social Media: A Latent Space Method

By Guo-Jun Qi, Charu C. Aggarwal, Qi Tian, Heng Ji, Thomas S. Huang. 2012

156 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Dacheng Tao
2. Luc Van Gool
3. Qi Tian
4. Xiaogang Wang
5. Yi Yang
6. Alan L. Yuille
7. Xilin Chen
8. Jingdong Wang

Citations in the corpus

• Differential Recurrent Neural Networks for Action Recognition (2015, background): “Unfortunately, the conventional LSTMs do not consider the impact of spatio-temporal dynamics corresponding to the given salient motion patterns, when they gate the information that ought to be memorized through time.”
• Multi-Task CNN Model for Attribute Prediction (2015, neutral): “dation, multimedia search and retrieval [5], [13], [14], [20], [30], [35], [36], [38], [43], [49].”
• Recommender Systems (2016, unknown): “A method has been proposed in [487] to leverage latent factor models for application to mining algorithms in the presence of tags.”
• Deep Collaborative Embedding for Social Image Understanding (2019, methodology): “Some methods have recently been proposed to explore images and user-provided tags [1], [2], [3], [4], [5], [6], [7], [8], [9], [10].”
• Accelerated Attributed Network Embedding (2017, background): “Some efforts have been devoted to leveraging network structure and attribute information for seeking a low-rank latent representation [19, 30].”
• Understanding Blooming Human Groups in Social Networks (2015, unknown): “constructed MINets from web-scale data to extract cross-media information [4] and explored the relationship of content and context knowledge from social media networks [5].”
• Image Classification and Retrieval are ONE (2015, background): “As the rapid growth of the Internet [40], large-scale image search attracts more and more attentions in both academic and industrial fields [62].”
• Robust Structured Subspace Learning for Data Representation (2015, background): “From the above objective function, we can see that the predictive functions are robust to outliers and noise and can preserve the local and global structural consistency.”
• Heterogeneous Face Attribute Estimation: A Deep Multi-Task Learning Approach (2017, background): “, automatic filtering of a face database to find person(s) of interest with given attributes; and (ii) social media [7] [8], e.”
• Label Informed Attributed Network Embedding (2017, background): “Attributed networks [18, 28] are ubiquitous in a variety of real-world information systems, such as academic networks and health care systems.”