BibSonomy :: user  :: pprett ::

bookmarks

publications

(20)   

• A probabilistic analysis of the Rocchio algorithm with TFIDF for text categorization
  Thorsten Joachims Proceedings of ICML-97, 14th International Conference on Machine Learning, page143--151. Nashville, US, Morgan Kaufmann Publishers, San Francisco, US, (1997)
  to text relevance, machine, categorization, feedback, rocchio, learning, by pprett and 4 other people on Jun 17, 2008, 4:01 PM
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• A Machine Learning Architecture for Optimizing Web Search Engines
  J. Boyan and D. Freitag and T. Joachims Proceedings of the AAAI Workshop on Internet-Based Information Systems, (1996)
  to search, relevance, machine, web reinforcement, feedback, learning, by pprett on Jun 17, 2008, 4:01 PM
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• A Comparison of Classifiers and Document Representations for the Routing Problem
  Hinrich Schütze and David A. Hull and Jan O. Pedersen Research and Development in Information Retrieval, page229--237. (1995)
  to relevance, machine, routing connectionist, feedback, learning, ann, by pprett and 2 other people on Jun 17, 2008, 4:01 PM
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• Beyond PageRank: machine learning for static ranking
  Matthew Richardson and Amit Prakash and Eric Brill WWW '06: Proceedings of the 15th international conference on World Wide Web, page707--715. New York, NY, USA, ACM Press, (2006)
  to ranknet msr, machine, pagerank, ranking, learning, by pprett and 4 other people on Jun 17, 2008, 4:01 PM
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• Active exploration for learning rankings from clickthrough data
  Filip Radlinski and Thorsten Joachims KDD '07: Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining, page570--579. New York, NY, USA, ACM Press, (2007)
  to clickthrough, relevance machine, feedback, learning, by pprett and 2 other people on Jun 17, 2008, 4:01 PM
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• Learning to rank using gradient descent
  Chris Burges and Tal Shaked and Erin Renshaw and Ari Lazier and Matt Deeds and Nicole Hamilton and Greg Hullender ICML '05: Proceedings of the 22nd international conference on Machine learning, page89--96. New York, NY, USA, ACM Press, (2005)
  to search, msr, neural, machine, web ranking, networks, ranknet, learning, by pprett and 3 other people on Jun 17, 2008, 4:01 PM
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• Improving web search ranking by incorporating user behavior information
  Eugene Agichtein and Eric Brill and Susan Dumais SIGIR '06: Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval, page19--26. New York, NY, USA, ACM Press, (2006)
  to relevance, retrieval, web behavior, feedback, ranknet, learning, user, search, msr, re-rank, evaluation, machine, information, by pprett and 2 other people on Jun 17, 2008, 4:01 PM
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• Some Formal Analysis of Rocchio's Similarity-Based Relevance Feedback Algorithm
  Zhixiang Chen and Binhai Zhu Inf. Retr.5(1):61--86January2002.
  to supervised, relevance, algorithm, machine, theoretical feedback, rocchio, learning, by pprett and 1 other person on Jun 17, 2008, 4:01 PM
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• Robustness of adaptive filtering methods in a cross-benchmark evaluation
  Yiming Yang and Shinjae Yoo and Jian Zhang and Bryan Kisiel SIGIR '05: Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval, page98--105. New York, NY, USA, ACM Press, (2005)
  to relevance, machine, filtering, ir, information, retrieval adaptive, feedback, learning, classification, by pprett and 1 other person on Jun 17, 2008, 4:01 PM
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• A regression framework for learning ranking functions using relative relevance judgments
  Zhaohui Zheng and Keke Chen and Gordon Sun and Hongyuan Zha SIGIR '07: Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval, page287--294. New York, NY, USA, ACM Press, (2007)
  to relevance, machine, judgements, information, retrieval ranking, feedback, learning, by pprett and 1 other person on Jun 17, 2008, 4:01 PM
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• Data Mining: Practical Machine Learning Tools and Techniques
  Ian H. Witten and Eibe Frank Morgan Kaufmann Series in Data Management Systems Morgan Kaufmann, Second edition, June2005.
  to data, clustering, weka machine, mining, learning, classification, by pprett and 6 other people on Jun 17, 2008, 4:01 PM
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• Query chains: learning to rank from implicit feedback
  Filip Radlinski and Thorsten Joachims KDD '05: Proceeding of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining, page239--248. New York, NY, USA, ACM Press, (2005)
  to query, learning2rank, machine, implicit, ml, ranking feedback, learning, by pprett and 5 other people on Jun 17, 2008, 4:01 PM
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• Automatic web query classification using labeled and unlabeled training data
  Steven M. Beitzel and Eric C. Jensen and Ophir Frieder and David Grossman and David D. Lewis and Abdur Chowdhury and Aleksandr Kolcz SIGIR '05: Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval, page581--582. New York, NY, USA, ACM, (2005)
  to query, machine, mining, aol, learning, supervised log, by pprett and 2 other people on Jun 17, 2008, 4:01 PM
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• Efficient text categorization
  Marko Grobelnik and Dunja Mladeni'c (1998)
  to n-gram, web, machine, categorization, text, learning, classification, yahoo by pprett and 1 other person on Jun 17, 2008, 4:01 PM
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• Machine learning in automated text categorization
  Fabrizio Sebastiani ACM Computing Surveys34(1):1--47(2002)
  to text survey, nbc, machine, categorization, rocchio, learning, classification, svm, ann, by pprett and 19 other people on Jun 17, 2008, 4:01 PM
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• On the Optimality of the Simple Bayesian Classifier under Zero-One Loss
  Pedro Domingos and Michael J. Pazzani Machine Learning29(2-3):103--130(1997)
  to text nbc, machine, mining, learning, by pprett and 2 other people on Jun 17, 2008, 4:01 PM
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• N-Gram-Based Text Categorization
  William B. Cavnar and John M. Trenkle Proceedings of SDAIR-94, 3rd Annual Symposium on Document Analysis and Information Retrieval, page161--175. Las Vegas, US, (1994)
  to n-gram, text machine, categorization, learning, by pprett and 2 other people on Jun 17, 2008, 4:01 PM
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• A tutorial on learning with bayesian networks
  D. Heckerman Microsoft Research, Redmond, Washington, (# 1995)
  to bayesian, machine, networks, probabilistic learning, by pprett and 7 other people on Jun 17, 2008, 4:01 PM
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• A study using n-gram features for text categorization
  F. Johannes (1998)
  to n-gram, text machine, categorization, learning, by pprett on Jun 17, 2008, 4:01 PM
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• An introduction to variable and feature selection
  Isabelle Guyon and Andre Elisseeff J. Mach. Learn. Res.(2003)
  to feature, machine, reduction, dimensionality, selection learning, by pprett and 2 other people on Jun 17, 2008, 4:01 PM
  URL | BibTeX