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    EMNLP
    2006
    158views Natural Language Processing» more  EMNLP 2006»
    Boosting Unsupervised Relation Extraction by Using NER
    13 years 9 months ago
    Boosting Unsupervised Relation Extraction by Using NER
    Download  acl.ldc.upenn.edu
    Web extraction systems attempt to use the immense amount of unlabeled text in the Web in order to create large lists of entities and relations. Unlike traditional IE methods, the ...
    Ronen Feldman, Benjamin Rosenfeld
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    ACE
    2003
    180views Education» more  ACE 2003»
    Managing the managers: Collaborative virtual teams with large staff and student numbers
    13 years 9 months ago
    Managing the managers: Collaborative virtual teams with large staff and student numbers
    Download  crpit.com
    Virtual teaming involving online presentations and peer reviews support the notion of collaborative student learning, whilst preparing them for the virtual work environment. Howev...
    Kathy Egea
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    ICVGIP
    2004
    143views Computer Vision» more  ICVGIP 2004»
    Modeling Signs Using Functional Data Analysis
    13 years 9 months ago
    Modeling Signs Using Functional Data Analysis
    Download  www.csee.usf.edu
    1 We present a functional data analysis (FDA) based method to statistically model continuous signs of the American Sign Language (ASL) for use in the recognition of signs in contin...
    Sunita Nayak, Sudeep Sarkar, Kuntal Sengupta
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    IAAI
    2003
    156views Artificial Intelligence» more  IAAI 2003»
    Searching for Hidden Messages: Automatic Detection of Steganography
    13 years 9 months ago
    Searching for Hidden Messages: Automatic Detection of Steganography
    Download  www.aaai.org
    Steganography is the field of hiding messages in apparently innocuous media (e.g. images), and steganalysis is the field of detecting these covert messages. Almost all steganalysi...
    George Berg, Ian Davidson, Ming-Yuan Duan, Goutam ...
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    NIPS
    2001
    210views Information Technology» more  NIPS 2001»
    Fast and Robust Classification using Asymmetric AdaBoost and a Detector Cascade
    13 years 9 months ago
    Fast and Robust Classification using Asymmetric AdaBoost and a Detector Cascade
    Download  research.microsoft.com
    This paper develops a new approach for extremely fast detection in domains where the distribution of positive and negative examples is highly skewed (e.g. face detection or databa...
    Paul A. Viola, Michael J. Jones
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