miscellaneous-2

Marketing

3260 papers • 126 benchmarks • 313 datasets

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Most implemented papers

Estimation and Inference of Heterogeneous Treatment Effects using Random Forests

S. Athey, Stefan Wager•Tue Oct 13 2015

This is the first set of results that allows any type of random forest, including classification and regression forests, to be used for provably valid statistical inference and is found to be substantially more powerful than classical methods based on nearest-neighbor matching.

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A Survey of Information Cascade Analysis: Models, Predictions, and Recent Advances

Xovee Xu, Goce Trajcevski, Fan Zhou, Kunpeng Zhang•Thu Dec 31 2020

This article presents a comprehensive review and categorization of information popularity prediction methods, from feature engineering and stochastic processes, through graph representation, to deep learning-based approaches.

205 0

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Learning to Expand Audience via Meta Hybrid Experts and Critics for Recommendation and Advertising

Yongchun Zhu, Fuzhen Zhuang, Juan Cao, Ruobing Xie, Leyu Lin, Yudan Liu, Xiaobo Hao, Kaikai Ge, Xu Zhang•Sun May 30 2021

A novel two-stage framework named Meta Hybrid Experts and Critics (MetaHeac) which has been deployed in WeChat Look-alike System and shows superior effectiveness for both content marketing campaigns in recommender systems and advertising campaigns in advertising platforms.

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Structure Learning of Probabilistic Graphical Models: A Comprehensive Survey

Yang Zhou•Mon Nov 28 2011

This paper presents a comprehensive survey of the existing structure learning algorithms for graphical models, and provides additional insights into the properties of the model, including the conditional independence properties.

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Maximum likelihood estimation of a finite mixture of logistic regression models in a continuous data stream

M. Kaptein, P. Ketelaar•Tue Feb 27 2018

This paper proposes a method for estimating a finite mixture of logistic regression models which can be used to cluster customers based on a continuous stream of responses, and introduces oFMLR, which allows segments to be identified in data streams or extremely large static datasets.

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A deep one-shot network for query-based logo retrieval

P. Roy, A. Bhunia, U. Pal, A. Bhunia, S. Ghose, Abhirup Das•Sat Nov 03 2018

An easy-to-implement query-based logo detection and localization system by employing a one-shot learning technique using off the shelf neural network components and achieving superior performance in Flickr logos-32 and TopLogos-10 dataset over different existing baseline methods.

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Maximum Relevance and Minimum Redundancy Feature Selection Methods for a Marketing Machine Learning Platform

Zhenyu Zhao, Radhika Anand, Mallory Wang•Wed Aug 14 2019

The mRMR feature selection methods for classification problem in a marketing machine learning platform at Uber that automates creation and deployment of targeting and personalization models at scale are extended by introducing a non-linear feature redundancy measure and a model-based feature relevance measure.

199 0

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Interpretable Click-Through Rate Prediction through Hierarchical Attention

Haifeng Chen, Yang Chen, Wei Cheng, Wei Wang, Zeyu Li•Sun Jan 19 2020

InterHAt is proposed that employs a Transformer with multi-head self-attention for feature learning that captures high-order feature interactions by an efficient attentional aggregation strategy with low computational complexity.

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Targeting customers under response-dependent costs

Johannes Haupt, S. Lessmann•Thu Mar 12 2020

The empirical results demonstrate that the consideration of treatment cost substantially increases campaign profit when used for customer targeting in combination with the estimation of the average or customer-level treatment effect.

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TUNIZI: a Tunisian Arabizi sentiment analysis Dataset

Chayma Fourati, Abir Messaoudi, Hatem Haddad•Tue Apr 28 2020

TUNIZI a sentiment analysis Tunisian Arabizi Dataset, collected from social networks, preprocessed for analytical studies and annotated manually by Tunisian native speakers is introduced.

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