A Bag of Features for Short Text Classification
Intent Based Relevance Estimation from Click Logs
A Large Scale Prediction Engine for App Install Clicks and Conversions
DeepRank: A New Deep Architecture for Relevance Ranking in Information Retrieval
Regularized and Retrofitted models for Learning Sentence Representation with Context
Deep Sequential Models for Task Satisfaction Prediction
- Forecasting Ad-Impressions on Online Retail Websites using Non-homogeneous Hawkes Processes -
A Hawkes Process Based Approach for Modeling Online Activity Correlations
Neural Attentive Session-based Recommendation
A Topic Model Based on Poisson Decomposition
An Empirical Study of Embedding Features in Learning to Rank
Session-aware Information Embedding for E-commerce Product Recommendation -
Online Expectation-Maximization for Click Models
An Ad CTR Prediction Method Based on Feature Learning of Deep and Shallow Layers -
Deep Context Modeling for Web Query Entity Disambiguation
Intent Based Relevance Estimation from Click Logs
DeepRank: A New Deep Architecture for Relevance Ranking in Information Retrieval
Neural Attentive Session-based Recommendation
A Topic Model Based on Poisson Decomposition
Deep Sequential Models for Task Satisfaction Prediction
A Probabilistic Multi-Touch Attribution Model for Online Advertising
LambdaFM: Learning Optimal Ranking with Factorization Machines Using Lambda Surrogates
Understanding Mobile Searcher Attention with Rich Ad Formats
Optimizing Update Frequencies for Decaying Information,
A Probabilistic Framework for Temporal User Modeling on Microblogs
A Multi-Scale Adaptive Personalized Model for Temporal Human Behavior Prediction
Learning to Propagate Rare Labels
Learning Context-aware Representations for Context-aware Recommendations
Improving Tail Query Performance by Fusion Model
On Building Decision Trees from Large-scale Data in Applications of On-line Advertising
Graph-of-word and TW-IDF: new approach to ad hoc IR
CRF framework for supervised preference aggregation
Exploiting proximity feature in statistical translation models for information retrieval
Incorporating user preferences into click models.
Predicting the impact of expansion terms using semantic and user interaction features
Personalization of web-search using short-term browsing context
Large-scale deep learning at Baidu.
Relevance Weighting using Within-document Term Statistics
Learning to Target: What Works for Behavioral Targeting
Reranking Search Results for Sparse Queries
Learning to Rank User Intent
A Probabilistic Method for Inferring Preferences from Clicks
Efficiency Optimizations for Interpolating Subqueries
A Language Model Approach to Capture Commercial Intent and Information Relevance for Sponsored Search
. Inferring Query Aspects from Reformulations Using Clustering
Advertiser-Centric Approach to Understand User Click Behavior in Sponsored Search
Factors Affecting Click-Through Behavior in Aggregated Search Interfaces,
The Anatomy of a Click: Modeling user behavior on web information systems,
Explore Click Models for Search Ranking
Query Reformulation using Conditional Random Fields
Online learning for recency search ranking using real-time user feedback
Enriching Context in Contextual Advertising
Pattern Based Keyword Extraction for Contextual Advertising
Mixture Model Label Propagation
Regularization and Feature Selection for Networked Features