Zobrazeno 1 - 10
of 220
pro vyhledávání: '"Wei, Penghui"'
Conversion rate (CVR) estimation aims to predict the probability of conversion event after a user has clicked an ad. Typically, online publisher has user browsing interests and click feedbacks, while demand-side advertising platform collects users' p
Externí odkaz:
http://arxiv.org/abs/2305.08328
Multi-scenario ad ranking aims at leveraging the data from multiple domains or channels for training a unified ranking model to improve the performance at each individual scenario. Although the research on this task has made important progress, it st
Externí odkaz:
http://arxiv.org/abs/2302.02636
To increase brand awareness, many advertisers conclude contracts with advertising platforms to purchase traffic and then deliver advertisements to target audiences. In a whole delivery period, advertisers usually desire a certain impression count for
Externí odkaz:
http://arxiv.org/abs/2302.02592
Correlative Preference Transfer with Hierarchical Hypergraph Network for Multi-Domain Recommendation
Advanced recommender systems usually involve multiple domains (such as scenarios or categories) for various marketing strategies, and users interact with them to satisfy diverse demands. The goal of multi-domain recommendation (MDR) is to improve the
Externí odkaz:
http://arxiv.org/abs/2211.11191
Click-through rate (CTR) prediction is a fundamental technique in recommendation and advertising systems. Recent studies have proved that learning a unified model to serve multiple domains is effective to improve the overall performance. However, it
Externí odkaz:
http://arxiv.org/abs/2206.13108
Current bundle generation studies focus on generating a combination of items to improve user experience. In real-world applications, there is also a great need to produce bundle creatives that consist of mixture types of objects (e.g., items, slogans
Externí odkaz:
http://arxiv.org/abs/2205.14970
This paper focuses on automatically generating the text of an ad, and the goal is that the generated text can capture user interest for achieving higher click-through rate (CTR). We propose CREATER, a CTR-driven advertising text generation approach,
Externí odkaz:
http://arxiv.org/abs/2205.08943
Predicting user response probabilities is vital for ad ranking and bidding. We hope that predictive models can produce accurate probabilistic predictions that reflect true likelihoods. Calibration techniques aim to post-process model predictions to p
Externí odkaz:
http://arxiv.org/abs/2205.07295
Publikováno v:
In Knowledge-Based Systems 25 November 2024 304
Autor:
Huang, Wei, Tian, Yu, Ma, Jing, Wei, Penghui, Du, Chengzhong, Zhang, Xiaodan, Chen, Fuxiang, Lin, Yuanxiang, Zhu, Yang, Kang, Dezhi
Publikováno v:
In Chemical Engineering Journal 15 October 2024 498