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Found 19 papers, 2 papers with code
Enhanced E-Commerce Attribute Extraction: Innovating with Decorative Relation Correction and LLAMA 2.0-Based Annotation
The rapid proliferation of e-commerce platforms accentuates the need for advanced search and retrieval systems to foster a superior user experience.
Leveraging Large Language Models for Enhanced Product Descriptions in eCommerce
In the dynamic field of eCommerce, the quality and comprehensiveness of product descriptions are pivotal for enhancing search visibility and customer engagement.
Bid Optimization for Offsite Display Ad Campaigns on eCommerce
Online retailers often use third-party demand-side-platforms (DSPs) to conduct offsite advertising and reach shoppers across the Internet on behalf of their advertisers.
Impression Allocation and Policy Search in Display Advertising
In order to address the unstable traffic pattern challenge and achieve the optimal overall outcome, we propose a multi-agent reinforcement learning method to adjust the bids from each guaranteed contract, which is simple, converging efficiently and scalable.
Learning Effective and Efficient Embedding via an Adaptively-Masked Twins-based Layer
Each feature value is mapped to an embedding vector via an embedding learning process.
Binary Code based Hash Embedding for Web-scale Applications
In these applications, embedding learning of categorical features is crucial to the success of deep learning models.
Towards a Better Tradeoff between Effectiveness and Efficiency in Pre-Ranking: A Learnable Feature Selection based Approach
In real-world search, recommendation, and advertising systems, the multi-stage ranking architecture is commonly adopted.
Exploration in Online Advertising Systems with Deep Uncertainty-Aware Learning
In this paper, we propose a novel Deep Uncertainty-Aware Learning (DUAL) method to learn CTR models based on Gaussian processes, which can provide predictive uncertainty estimations while maintaining the flexibility of deep neural networks.
Probabilistic Streaming Tensor Decomposition
Tensor decomposition is a fundamental tool for multiway data analysis.
Extracting Entities and Relations with Joint Minimum Risk Training
We investigate the task of joint entity relation extraction.
Ranked #1 on
Relation Extraction
on ACE 2005
(Sentence Encoder metric)
Large scale classification in deep neural network with Label Mapping
Therefore, it is infeasible to solve the multi-class classification problem using deep neural network when the number of classes are huge.
Proceedings of the 2017 AdKDD & TargetAd Workshop
Proceedings of the 2017 AdKDD and TargetAd Workshop held in conjunction with the 23rd ACM SIGKDD Conference on Knowledge Discovery and Data Mining Halifax, Nova Scotia, Canada.
Profit Maximization for Online Advertising Demand-Side Platforms
We develop an optimization model and corresponding algorithm for the management of a demand-side platform (DSP), whereby the DSP aims to maximize its own profit while acquiring valuable impressions for its advertiser clients.
Optimization and Control Computer Science and Game Theory
Distributed Flexible Nonlinear Tensor Factorization
Tensor factorization is a powerful tool to analyse multi-way data.
Lift-Based Bidding in Ad Selection
In this paper, we propose a new bidding strategy and prove that if the bid price is decided based on the performance lift rather than absolute performance value, advertisers can actually gain more action events.
Smart Pacing for Effective Online Ad Campaign Optimization
In this paper, we propose a smart pacing approach in which the delivery pace of each campaign is learned from both offline and online data to achieve smooth delivery and optimal performance goals.
User Clustering in Online Advertising via Topic Models
In the domain of online advertising, our aim is to serve the best ad to a user who visits a certain webpage, to maximize the chance of a desired action to be performed by this user after seeing the ad.
Visual Sentiment Prediction with Deep Convolutional Neural Networks
Images have become one of the most popular types of media through which users convey their emotions within online social networks.
Real Time Bid Optimization with Smooth Budget Delivery in Online Advertising
Today, billions of display ad impressions are purchased on a daily basis through a public auction hosted by real time bidding (RTB) exchanges.
