Optimizing search engines using clickthrough data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
ACM SIGIR Forum
CubeSVD: a novel approach to personalized Web search
WWW '05 Proceedings of the 14th international conference on World Wide Web
Accurately interpreting clickthrough data as implicit feedback
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Personalizing search via automated analysis of interests and activities
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Query chains: learning to rank from implicit feedback
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Fast maximum margin matrix factorization for collaborative prediction
ICML '05 Proceedings of the 22nd international conference on Machine learning
Reading level assessment using support vector machines and statistical language models
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
A large-scale evaluation and analysis of personalized search strategies
Proceedings of the 16th international conference on World Wide Web
Information re-retrieval: repeat queries in Yahoo's logs
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Robust classification of rare queries using web knowledge
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Knowledge sharing and yahoo answers: everyone knows something
Proceedings of the 17th international conference on World Wide Web
To personalize or not to personalize: modeling queries with variation in user intent
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Characterizing the influence of domain expertise on web search behavior
Proceedings of the Second ACM International Conference on Web Search and Data Mining
Predicting the readability of short web summaries
Proceedings of the Second ACM International Conference on Web Search and Data Mining
A dynamic bayesian network click model for web search ranking
Proceedings of the 18th international conference on World wide web
Regression-based latent factor models
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Building enriched document representations using aggregated anchor text
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Revisiting readability: a unified framework for predicting text quality
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Exploiting site-level information to improve web search
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Towards query log based personalization using topic models
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Personalizing web search using long term browsing history
Proceedings of the fourth ACM international conference on Web search and data mining
Quality-biased ranking of web documents
Proceedings of the fourth ACM international conference on Web search and data mining
Personalizing web search results by reading level
Proceedings of the 20th ACM international conference on Information and knowledge management
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Characterizing web content, user interests, and search behavior by reading level and topic
Proceedings of the fifth ACM international conference on Web search and data mining
Characterizing web content, user interests, and search behavior by reading level and topic
Proceedings of the fifth ACM international conference on Web search and data mining
Large-scale learning of word relatedness with constraints
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Personalizing atypical web search sessions
Proceedings of the sixth ACM international conference on Web search and data mining
WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01
Take this personally: pollution attacks on personalized services
SEC'13 Proceedings of the 22nd USENIX conference on Security
Lessons from the journey: a query log analysis of within-session learning
Proceedings of the 7th ACM international conference on Web search and data mining
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Imagine a physician and a patient doing a search on antibiotic resistance. Or a chess amateur and a grandmaster conducting a search on Alekhine's Defence. Although the topic is the same, arguably the two users in each case will satisfy their information needs with very different texts. Yet today search engines mostly adopt the one-size-fits-all solution, where personalization is restricted to topical preference. We found that users do not uniformly prefer simple texts, and that the text comprehensibility level should match the user's level of preparedness. Consequently, we propose to model the comprehensibility of texts as well as the users' reading proficiency in order to better explain how different users choose content for further exploration. We also model topic-specific reading proficiency, which allows us to better explain why a physician might choose to read sophisticated medical articles yet simple descriptions of SLR cameras. We explore different ways to build user profiles, and use collaborative filtering techniques to overcome data sparsity. We conducted experiments on large-scale datasets from a major Web search engine and a community question answering forum. Our findings confirm that explicitly modeling text comprehensibility can significantly improve content ranking (search results or answers, respectively).