Algorithms on strings, trees, and sequences: computer science and computational biology
Algorithms on strings, trees, and sequences: computer science and computational biology
Wrappers for feature subset selection
Artificial Intelligence - Special issue on relevance
Variations in relevance judgments and the measurement of retrieval effectiveness
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Large Margin Classification Using the Perceptron Algorithm
Machine Learning - The Eleventh Annual Conference on computational Learning Theory
Time Series Analysis: Forecasting and Control
Time Series Analysis: Forecasting and Control
The Use of Implicit Evidence for Relevance Feedback in Web Retrieval
Proceedings of the 24th BCS-IRSG European Colloquium on IR Research: Advances in Information Retrieval
Adaptive duplicate detection using learnable string similarity measures
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Word association norms, mutual information, and lexicography
ACL '89 Proceedings of the 27th annual meeting on Association for Computational Linguistics
Accurately interpreting clickthrough data as implicit feedback
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
A web-based kernel function for measuring the similarity of short text snippets
Proceedings of the 15th international conference on World Wide Web
Generating query substitutions
Proceedings of the 15th international conference on World Wide Web
Improving web search ranking by incorporating user behavior information
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Predicting clicks: estimating the click-through rate for new ads
Proceedings of the 16th international conference on World Wide Web
IEEE Transactions on Knowledge and Data Engineering
Practical guide to controlled experiments on the web: listen to your customers not to the hippo
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
The Forgetron: A Kernel-Based Perceptron on a Budget
SIAM Journal on Computing
Using the wisdom of the crowds for keyword generation
Proceedings of the 17th international conference on World Wide Web
Learning multiple graphs for document recommendations
Proceedings of the 17th international conference on World Wide Web
Online learning from click data for sponsored search
Proceedings of the 17th international conference on World Wide Web
Contextual advertising by combining relevance with click feedback
Proceedings of the 17th international conference on World Wide Web
Optimizing relevance and revenue in ad search: a query substitution approach
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
A general optimization framework for smoothing language models on graph structures
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Exploring mouse movements for inferring query intent
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Get another label? improving data quality and data mining using multiple, noisy labelers
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Context-aware query suggestion by mining click-through and session data
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Result enrichment in commerce search using browse trails
Proceedings of the fourth ACM international conference on Web search and data mining
Shopping for products you don't know you need
Proceedings of the fourth ACM international conference on Web search and data mining
Predictive client-side profiles for personalized advertising
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
A semantic approach to recommending text advertisements for images
Proceedings of the sixth ACM conference on Recommender systems
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Identifying similar keywords, known as broad matches, is an important task in online advertising that has become a standard feature on all major keyword advertising platforms. Effective broad matching leads to improvements in both relevance and monetization, while increasing advertisers' reach and making campaign management easier. In this paper, we present a learning-based approach to broad matching that is based on exploiting implicit feedback in the form of advertisement clickthrough logs. Our method can utilize arbitrary similarity functions by incorporating them as features. We present an online learning algorithm, Amnesiac Averaged Perceptron, that is highly efficient yet able to quickly adjust to the rapidly-changing distributions of bidded keywords, advertisements and user behavior. Experimental results obtained from (1) historical logs and (2) live trials on a large-scale advertising platform demonstrate the effectiveness of the proposed algorithm and the overall success of our approach in identifying high-quality broad match mappings.