SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
Some simple effective approximations to the 2-Poisson model for probabilistic weighted retrieval
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Query expansion using local and global document analysis
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
A probabilistic model of information retrieval: development and comparative experiments
Information Processing and Management: an International Journal
Relevance based language models
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
A study of smoothing methods for language models applied to Ad Hoc information retrieval
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Probabilistic query expansion using query logs
Proceedings of the 11th international conference on World Wide Web
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
Domain-Specific Keyphrase Extraction
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Simple BM25 extension to multiple weighted fields
Proceedings of the thirteenth ACM international conference on Information and knowledge management
Impedance coupling in content-targeted advertising
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Predicting good probabilities with supervised learning
ICML '05 Proceedings of the 22nd international conference on Machine learning
Finding advertising keywords on web pages
Proceedings of the 15th international conference on World Wide Web
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
Time-dependent semantic similarity measure of queries using historical click-through data
Proceedings of the 15th international conference on World Wide Web
Learning user interaction models for predicting web search result preferences
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)
Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)
Random walks on the click graph
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
A semantic approach to contextual advertising
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Improving similarity measures for short segments of text
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Similarity measures for short segments of text
ECIR'07 Proceedings of the 29th European conference on IR research
Report on the second KDD workshop on data mining for advertising
ACM SIGKDD Explorations Newsletter
Data-driven text features for sponsored search click prediction
Proceedings of the Third International Workshop on Data Mining and Audience Intelligence for Advertising
Large-scale computation of distributional similarities for queries
NAACL-Short '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers
Gazpacho and summer rash: lexical relationships from temporal patterns of web search queries
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 3 - Volume 3
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Measuring the relevance between a document and a phrase is fundamental to many information retrieval and matching tasks including on-line advertising. In this paper, we explore two approaches for measuring the relevance between a document and a phrase aiming to provide consistent relevance scores for both in and out-of document phrases. The first approach is a similarity-based method which represents both the document and phrase as term vectors to derive a real-valued relevance score. The second approach takes as input the relevance estimates of some in-document phrases and uses Gaussian Process Regression to predict the score of a target out-of-document phrase. While both of these two approaches work well, the best result is given by a Gaussian Process Regression model, which is significantly better than the similarity-based approach and 10% better than a baseline similarity method using bag-of-word vectors.