A language modeling approach to information retrieval
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Analysis of a very large web search engine query log
ACM SIGIR Forum
Optimizing search engines using clickthrough data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
ACM SIGIR Forum
A study of smoothing methods for language models applied to information retrieval
ACM Transactions on Information Systems (TOIS)
Display time as implicit feedback: understanding task effects
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Combining the language model and inference network approaches to retrieval
Information Processing and Management: an International Journal - Special issue: Bayesian networks and information retrieval
Automatic identification of user goals in Web search
WWW '05 Proceedings of the 14th international conference on World Wide Web
Similarity measures for tracking information flow
Proceedings of the 14th ACM international conference on Information and knowledge management
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
Wikify!: linking documents to encyclopedic knowledge
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Mining the search trails of surfing crowds: identifying relevant websites from user activity
Proceedings of the 17th international conference on World Wide Web
The query-flow graph: model and applications
Proceedings of the 17th ACM conference on Information and knowledge management
Classifying and Characterizing Query Intent
ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
Predicting user interests from contextual information
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
A contextual-bandit approach to personalized news article recommendation
Proceedings of the 19th international conference on World wide web
Studying trailfinding algorithms for enhanced web search
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Linking online news and social media
Proceedings of the fourth ACM international conference on Web search and data mining
Hypergeometric language models for republished article finding
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Intent-aware search result diversification
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Ranking related news predictions
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
A multi-faceted approach to query intent classification
SPIRE'11 Proceedings of the 18th international conference on String processing and information retrieval
Proceedings of the 20th ACM international conference on Information and knowledge management
Intent-based diversification of web search results: metrics and algorithms
Information Retrieval
Access patterns for robots and humans in web archives
Proceedings of the 13th ACM/IEEE-CS joint conference on Digital libraries
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Modeling user browsing behavior is an active research area with tangible real-world applications, e.g., organizations can adapt their online presence to their visitors browsing behavior with positive effects in user engagement, and revenue. We concentrate on online news agents, and present a semi-supervised method for predicting news articles that a user will visit after reading an initial article. Our method tackles the problem using language intent models trained on historical data which can cope with unseen articles. We evaluate our method on a large set of articles and in several experimental settings. Our results demonstrate the utility of language intent models for predicting user browsing behavior within online news sites.