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20212026
most citedCBNet: A Plug-and-Play Network for Segmentation-Based Scene Text Detection

18 citations · 34 across the 23 of their papers we have counts for

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Showing 2022Show all

7 papers · 1 filter

cs.CV2022★ 18 cited

CBNet: A Plug-and-Play Network for Segmentation-Based Scene Text Detection

Xi Zhao, Wei Feng, Zheng Zhang +5

Recently, segmentation-based methods are quite popular in scene text detection, which mainly contain two steps: text kernel segmentation and expansion. However, the segmentation pr…

cs.IR2022

PCDF: A Parallel-Computing Distributed Framework for Sponsored Search Advertising Serving

Han Xu, Hao Qi, Kunyao Wang +8

Traditional online advertising systems for sponsored search follow a cascade paradigm with retrieval, pre-ranking,ranking, respectively. Constrained by strict requirements on onlin…

cs.IR2022

Gating-adapted Wavelet Multiresolution Analysis for Exposure Sequence Modeling in CTR prediction

Xiaoxiao Xu, Zhiwei Fang, Qian Yu +7

The exposure sequence is being actively studied for user interest modeling in Click-Through Rate (CTR) prediction. However, the existing methods for exposure sequence modeling brin…

cs.IR2022★ 2 cited

On the Adaptation to Concept Drift for CTR Prediction

Congcong Liu, Yuejiang Li, Fei Teng +5

Click-through rate (CTR) prediction is a crucial task in web search, recommender systems, and online advertisement displaying. In practical application, CTR models often serve with…

cs.IR2022★ 9 cited

IA-GCN: Interactive Graph Convolutional Network for Recommendation

Yinan Zhang, Pei Wang, Congcong Liu +7

Recently, Graph Convolutional Network (GCN) has become a novel state-of-art for Collaborative Filtering (CF) based Recommender Systems (RS). It is a common practice to learn inform…

cs.IR2022

Rethinking Position Bias Modeling with Knowledge Distillation for CTR Prediction

Congcong Liu, Yuejiang Li, Jian Zhu +4

Click-through rate (CTR) Prediction is of great importance in real-world online ads systems. One challenge for the CTR prediction task is to capture the real interest of users from…

cs.IR2022

Alleviating Cold-start Problem in CTR Prediction with A Variational Embedding Learning Framework

Xiaoxiao Xu, Chen Yang, Qian Yu +7

We propose a general Variational Embedding Learning Framework (VELF) for alleviating the severe cold-start problem in CTR prediction. VELF addresses the cold start problem via alle…