Research Library
Categories
Section titled “Categories”- Table of Contents
- Keyword Optimization & Management
- Bidding & Auction Strategies
- Machine Learning & AI Applications
- Consumer Behavior & Prediction
- Budget Allocation & Optimization
- Click-Through Rate (CTR) Prediction
- Ad Generation & Retrieval
- Causal Inference & Attribution
- Media Selection & Planning
- Market Analysis & Competition
- Sentiment Analysis & Product Descriptions
Keyword Optimization & Management
Section titled “Keyword Optimization & Management”- A Concept Knowledge-Driven Keywords Retrieval Framework for Sponsored Search Framework leveraging concept knowledge for improved keyword retrieval in sponsored search campaigns.
- BroadGen - A Framework for Generating Effective and Efficient Advertiser Broad Match Keyphrase Recommendations System for generating broad match keyword recommendations for advertisers.
- Combinatorial Keyword Recommendations for Sponsored Search with Deep Reinforcement Learning Deep RL approach to recommending keyword combinations in sponsored search.
- Diversity driven Query Rewriting in Search Advertising Methods for rewriting queries to increase diversity in search advertising results.
- Domain-Constrained Advertising Keyword Generation Techniques for generating keywords within specific domain constraints.
- Keyword Decisions in Sponsored Search Advertising Strategic framework for making keyword selection decisions in sponsored search.
- Keyword Optimization in Sponsored Search Advertising - A Multi-Level Computational Framework Comprehensive multi-level framework for keyword optimization.
- Keyword portfolio optimization Portfolio theory applied to keyword selection and management.
- Keyword Targeting Optimization in Sponsored Search Advertising - Combining Selection and Matching Integrated approach combining keyword selection with matching optimization.
- OKG - On-the-Fly Keyword Generation in Sponsored Search Advertising Real-time keyword generation system for sponsored search.
- OMS - On-the-fly, Multi-Objective, Self-Reflective Ad Keyword Generation via LLM Agent LLM-based agent for multi-objective keyword generation with self-reflection capabilities.
- Optimal Keywords Grouping in Sponsored Search Advertising under Uncertain Environments Methods for grouping keywords optimally under uncertainty.
- Retrieve Synonymous keywords for Frequent Queries in Sponsored Search in a Data Augmentation Way Data augmentation approach to finding synonym keywords for common queries.
- Triangular Bidword Generation for Sponsored Search Auction Novel approach to generating bidwords using triangular methods.
Unified Generative & Dense Retrieval for Query Rewriting in Sponsored Search(not found in docs)- VALUE - Value-Aware Large Language Model for Query Rewriting via Weighted Trie in Sponsored Search LLM approach using weighted tries for value-aware query rewriting.
Bidding & Auction Strategies
Section titled “Bidding & Auction Strategies”- A Game-theoretic Machine Learning Approach for Revenue Maximization in Sponsored Search Game theory and ML combined for maximizing revenue in sponsored search auctions.
- A Novel Bid Optimizer for Sponsored Search Auctions based on Cooperative Game Theory Cooperative game theory approach to bid optimization.
- Advertiser Bidding Prediction and Optimization in Online Advertising Methods for predicting and optimizing advertiser bidding behavior.
- An Adaptive Online Ad Auction Scoring Algorithm for Revenue Maximization Adaptive scoring algorithm for maximizing auction revenue.
- Auctions Meet Bandits - An Empirical Analysis Empirical study combining auction theory with multi-armed bandit algorithms.
- Bandits for Sponsored Search Auctions under Unknown Valuation Model - Case Study in E-Commerce Advertising Bandit algorithms applied to auctions with unknown valuations.
- Bid Optimization in Broad-Match Ad auctions Optimization strategies for broad-match auction bidding.
- Characterizing Optimal Adword Auctions Theoretical characterization of optimal auction mechanisms for AdWords.
- Contextual Bandits with Similarity Information Contextual bandit algorithms incorporating similarity metrics.
- Deep Reinforcement Learning for Sponsored Search Real-time Bidding Deep RL approach for real-time bidding in sponsored search.
- Dynamic Reserve Price Design with Distributed Solving Algorithm Distributed algorithms for dynamically setting reserve prices.
- Handling Advertisements of Unknown Quality in Search Advertising Strategies for managing ads with uncertain quality metrics.
- Keyword-Level Bayesian Online Bid Optimization for Sponsored Search Advertising Bayesian approach to optimizing bids at the keyword level.
- Mathematical Modeling of Competition in Sponsored Search Market Mathematical models of competitive dynamics in sponsored search.
- Multi-objective cluster based bidding algorithm Cluster-based approach to multi-objective bidding optimization.
- Networked Stochastic Multi-armed Bandits with Combinatorial Strategies Network-aware bandit algorithms with combinatorial action spaces.
- Nonparametric Pricing Bandits Leveraging Informational Externalities to Learn the Demand Curve Nonparametric methods for learning demand curves using bandit algorithms.
- Practical Constrained Optimization of Auction Mechanisms in E-Commerce Sponsored Search Advertisin Practical optimization methods for constrained auction mechanisms.
- Predicting Advertiser Bidding Behaviors in Sponsored Search Predictive models for advertiser bidding patterns.
- Prediction Model of Optimal Bid Price Based on Keyword Auction Data Through Machine Learning Algorithms ML-based prediction of optimal bid prices using auction data.
- Smart pacing for effective online ad campaign optimization Algorithms for optimal pacing of ad campaign spending.
- Sponsored Search Auction Design Beyond Single Utility Maximization Auction design considering multiple utility objectives.
- Sponsored Search Auctions with Markovian Users Auction theory incorporating Markovian user behavior models.
- To Broad-Match or Not to Broad-Match - An Auctioneer’s Dilemma Analysis of broad-match decisions from the auctioneer’s perspective.
Machine Learning & AI Applications
Section titled “Machine Learning & AI Applications”- AI and consumer behavior - Trends, technologies, and future directions from a scopus-based systematic review Comprehensive review of AI applications in consumer behavior research.
- AiAds - Automated and Intelligent Advertising System for Sponsored Search Automated AI system for managing sponsored search advertising.
- Algorithmic Methods for Sponsored Search Advertising Overview of algorithmic approaches in sponsored search advertising.
- An Enhanced Ad Event-Prediction Method Based on Feature Engineering Feature engineering techniques for predicting ad events.
- Application of machine learning in predicting consumer behavior and precision marketing ML applications for consumer behavior prediction and targeted marketing.
- Applying Large Language Models to Sponsored Search Applications of LLMs in sponsored search advertising.
- Balancing Efficiency and Effectiveness - An LLM-Infused Approach for Optimized CTR Prediction LLM-enhanced CTR prediction balancing multiple objectives.
Consumer Behavior & Prediction
Section titled “Consumer Behavior & Prediction”- Bayesian Network-based Modeling of Consumer Behavioral Decision Making Bayesian networks for modeling consumer decision processes.
- Decoding Gen Z - AI’s influence on brand trust and purchasing behavior Study of AI’s impact on Gen Z consumer behavior and brand perception.
- Predicting consumer behavior with web search Using web search data to predict consumer behavior patterns.
- Predicting online customer purchase - The integration of customer characteristics and browsing patterns Predictive models combining customer attributes with browsing behavior.
- Testing Models of Consumer Search Using Data on Web Browsing and Purchasing Behavior Empirical testing of consumer search models using web data.
- Which keyword design increases the click and purchase probability_ Analysis of keyword design effects on click and purchase rates.
Budget Allocation & Optimization
Section titled “Budget Allocation & Optimization”- Adaptive Budget Optimization for Multichannel Advertising Using Combinatorial Bandits Bandit algorithms for optimizing budget across multiple advertising channels.
- Allocating Budget across Portals in Search Engine Advertising Strategies for distributing budget across different search portals.
- Integrating Keyword Segmentation and Budget Allocation Decisions in Sponsored Search Advertising Integrated approach to keyword segmentation and budget allocation.
- Joint optimization of bid and budget allocation in sponsored search Simultaneous optimization of bidding and budget allocation decisions.
oint Optimization of Bid and Budget Allocation in Sponsored Search(not found in docs)oint Optimization of Multiple Performance Metrics in Online Video Advertising(not found in docs)- Online joint bid_daily budget optimization of Internet advertising campaigns Real-time optimization of bids and daily budgets.
- Optimal Budget Allocation Across Search Advertising Markets Optimal allocation strategies across different search markets.
- Optimal delivery of sponsored search advertisements subject to budget constraints Ad delivery optimization under budget constraints.
- Optimization of Ads Allocation in Sponsored Search Methods for optimizing ad allocation in sponsored search.
- Optimizing budget constrained spend in search advertising Strategies for optimizing spending under budget constraints.
- Optimizing Your Online-Advertisement Asynchronously Asynchronous optimization approaches for online advertising.
- ROI constrained optimal online allocation in sponsored search Optimal allocation strategies subject to ROI constraints.
Click-Through Rate (CTR) Prediction
Section titled “Click-Through Rate (CTR) Prediction”- A Model of Individual Keyword Performance in Paid Search Advertising Modeling individual keyword performance metrics in paid search.
- Deep Character-Level Click-Through Rate Prediction for Sponsored Search Character-level deep learning for CTR prediction.
- Dynamic Hierarchical Empirical Bayes - A Predictive Model Applied to Online Advertising Hierarchical Bayesian approach to advertising performance prediction.
- Estimating Individual Advertising Effect in E-Commerce Methods for estimating individual-level advertising effects.
- Implicit Look-alike Modelling in Display Ads - Transfer Collaborative Filtering to CTR Estimation Look-alike modeling using collaborative filtering for CTR prediction.
- Reacting to Variations in Product Demand - An Application for Conversion Rate (CR) Prediction in Sponsored Search Conversion rate prediction adapting to demand fluctuations.
- Using Neural Networks for Click Prediction of Sponsored Search Neural network approaches to click prediction.
Ad Generation & Retrieval
Section titled “Ad Generation & Retrieval”- DeepGen - Diverse Search Ad Generation and Real-Time Customization Deep learning system for generating diverse, customized search ads in real-time.
- ProphetNet-Ads - A Looking Ahead Strategy for Generative Retrieval Models in Sponsored Search Engine Forward-looking generative retrieval approach for sponsored search.
- Real-time Ad retrieval via LLM-generative Commercial Intention for Sponsored Search Advertising LLM-based real-time ad retrieval using commercial intent generation.
- Scalable Semantic Matching of Queries to Ads in Sponsored Search Advertising Scalable methods for semantic matching between queries and ads.
Causal Inference & Attribution
Section titled “Causal Inference & Attribution”- AdAlyze Redux - Post-Click and Post-Conversion Text Feature Attribution for Sponsored Search Ads Text feature attribution analysis for post-click and post-conversion events.
- Bayesian Modeling of Marketing Attribution Bayesian approaches to marketing attribution modeling.
- Causal Inference in the Presence of Interference in Sponsored Search Advertising Causal inference methods accounting for interference effects.
- Do Specific Text Features Influence Click Probabilities in Paid Search Advertising Analysis of text feature effects on click probabilities.
- Estimating Social Influence from Observational Data Methods for estimating social influence effects from observational data.
- Modeling Indirect Effects of Paid Search Advertising Models for capturing indirect effects of paid search campaigns.
- Social Influence Analysis - Models, Methods, and Evaluation Comprehensive review of social influence analysis techniques.
Media Selection & Planning
Section titled “Media Selection & Planning”- Developing a fuzzy enhanced Russell measure for media selection Fuzzy logic approach to media selection using Russell measures.
- Media selection by mean-variance analysis (1980) Classic portfolio theory approach to media selection.
- Media selection in the presence of flexible factors and imprecise data Media selection under uncertainty and imprecise information.
- Parameter estimation and objective definition in mean-variance media scheduling (1981) Methods for parameter estimation in mean-variance media scheduling.
Market Analysis & Competition
Section titled “Market Analysis & Competition”- A Cooperative-Competitive Multi-Agent Framework for Auto-bidding in Online Advertising Multi-agent framework modeling cooperation and competition in auto-bidding.
- AdSight - Scalable and Accurate Quantification of User Attention in Multi-Slot Sponsored Search System for measuring user attention across multiple ad slots.
- Efficiency Evaluation in Search Advertising Methods for evaluating efficiency in search advertising markets.
- Modeling Competition and Its Impact on Paid-Search Advertising Models of competitive effects in paid search markets.
- Multi-Category Fairness in Sponsored Search Auctions Fairness considerations across multiple categories in sponsored search.
- Optimizing Sponsored Search Ranking Strategy by Deep Reinforcement Learning Deep RL approach to optimizing ranking strategies.
- Towards a Unified Marketing Optimization Framework for e-Commerce Sponsored Search Unified framework for e-commerce sponsored search optimization.
Sentiment Analysis & Product Descriptions
Section titled “Sentiment Analysis & Product Descriptions”- Optimizing sentiment analysis in product descriptions Methods for optimizing sentiment analysis applied to product descriptions.
- The Impact of Sentiment Scores Extracted from Product Descriptions on Customer Purchase Intention Study of sentiment’s effect on purchase intent.
Missing in docs
Section titled “Missing in docs”- Keyword Optimization & Management — tried keyword-optimization-and-management, untitled
- Bidding & Auction Strategies — tried bidding-and-auction-strategies, untitled
- Machine Learning & AI Applications — tried machine-learning-and-ai-applications, untitled
- Consumer Behavior & Prediction — tried consumer-behavior-and-prediction, untitled
- Budget Allocation & Optimization — tried budget-allocation-and-optimization, untitled
- Click-Through Rate (CTR) Prediction — tried click-through-rate-ctr-prediction, untitled
- Ad Generation & Retrieval — tried ad-generation-and-retrieval, untitled
- Causal Inference & Attribution — tried causal-inference-and-attribution, untitled
- Media Selection & Planning — tried media-selection-and-planning, untitled
- Market Analysis & Competition — tried market-analysis-and-competition, untitled
- — — tried untitled
- Unified Generative & Dense Retrieval for Query Rewriting in Sponsored Search — tried unified-generative-and-dense-retrieval-for-query-rewriting-in-sponsored-search, unified-generative-and-dense-retrieval-for-query-rewriting-in-sponsored-search
- oint Optimization of Bid and Budget Allocation in Sponsored Search — tried oint-optimization-of-bid-and-budget-allocation-in-sponsored-search, oint-optimization-of-bid-and-budget-allocation-in-sponsored-search
- oint Optimization of Multiple Performance Metrics in Online Video Advertising — tried oint-optimization-of-multiple-performance-metrics-in-online-video-advertising, oint-optimization-of-multiple-performance-metrics-in-online-video-advertising
- — — tried untitled
- Total Papers: 97** — tried total-papers-97
- Main Topics: Keyword optimization, bidding strategies, machine learning/AI, consumer behavior, budget allocation, CTR prediction, ad generation, attribution modeling** — tried main-topics-keyword-optimization-bidding-strategies-machine-learning-ai-consumer-behavior-budget-allocation-ctr-prediction-ad-generation-attribution-modeling
- Date Range: Most papers from 2015-2024, with some classic papers from the 1980s on media selection** — tried date-range-most-papers-from-2015-2024-with-some-classic-papers-from-the-1980s-on-media-selection
- Primary Focus: Sponsored search advertising and online marketing optimization** — tried primary-focus-sponsored-search-advertising-and-online-marketing-optimization
Unlisted in seed
Section titled “Unlisted in seed”- /joint-optimization-of-multiple-performance-metrics-in-online-video-advertising/
- /unified-generative-dense-retrieval-for-query-rewriting-in-sponsored-search/