Now showing items 1-16 of 16

    • Counter-Surveillance in an Algorithmic World 

      Dutrisac, James George (2007-09-26)
      Surveillance is the act of collecting, analysing, and acting upon information about specific objects, data, or individuals. Recent advances have allowed for the automation of a large part of this process. Of particular ...
    • Data Mining the Genetics of Leukemia 

      Morton, Geoffrey (2010-01-13)
      Acute Lymphoblastic Leukemia (ALL) is the most common cancer in children under the age of 15. At present, diagnosis, prognosis and treatment decisions are made based upon blood and bone marrow laboratory testing. With ...
    • The Design and Applications of a Privacy-Preserving Identity and Trust-Management System 

      Hussain, Mohammed (2010-04-08)
      Identities are present in the interactions between individuals and organizations. Online shopping requires credit card information, while e-government services require social security or passport numbers. The involvement ...
    • Detecting Deception in Interrogation Settings 

      Lamb, Carolyn (2012-12-18)
      Bag-of-words deception detection systems outperform humans, but are still not always accurate enough to be useful. In interrogation settings, present models do not take into account potential influence of the words in a ...
    • Explicating a Biological Basis for Chronic Fatigue Syndrome 

      Abou-Gouda, Samar A. (2007-12-18)
      In the absence of clinical markers for Chronic Fatigue Syndrome (CFS), research to find a biological basis for it is still open. Many data-mining techniques have been widely employed to analyze biomedical data describing ...
    • Improved Document Summarization and Tag Clouds via Singular Value Decomposition 

      Provost, James (2008-09-25)
      Automated summarization is a difficult task. World-class summarizers can provide only "best guesses" of which sentences encapsulate the important content from within a set of documents. As automated systems continue to ...
    • Inferring Systemic Functional Language Models 

      Alsadhan, Nasser (2014-08-29)
      Language production in the brain is a complicated process that is not yet fully understood. The bag-of-words model, which considers the frequencies of each word in a document, is a useful approach in many text mining fields, ...
    • Measuring Interestingness of Documents Using Variability 

      Kondi Chandrasekaran, Pradeep Kumar (2012-02-01)
      The amount of data we are dealing with is being generated at an astronomical pace. With the rapid technological advances in the field of data storage techniques, storing and transmitting copious amounts of data has become ...
    • Modelling Deception Detection in Text 

      Gupta, Smita (2007-11-29)
      As organizations and government agencies work diligently to detect financial irregularities, malfeasance, fraud and criminal activities through intercepted communication, there is an increasing interest in devising an ...
    • Ranks and Partial Cuts in Forward Hypergraphs 

      Sawilla, Reginald Elias (2011-05-02)
      Many real-world relations are networks that can be modelled with a kind of directed hypergraph named a forward hypergraph (F-graph). F-graphs capture the semantics of both conjunctive and disjunctive dependency relations. ...
    • Social Structure in Tagging Practices: Reality or Myth? 

      Fani Marvasti, Amin (2008-12-04)
      Tagging is widely adopted in so-called "collaborative-tagging" systems which are one of the Web 2.0 applications that have achieved lots of attention lately. They provide services for users to store, manage and search ...
    • Spectral Techniques for Heterogeneous Social Networks 

      Zheng, Quan (2016-01-26)
      Social networks represent a set of participants and the pairwise relationships between them. There are several different types of networks, such as directed networks, networks with typed edges, dynamic networks and signed ...
    • Streaming Random Forests 

      Abdulsalam, Hanady (2008-07-16)
      Recent research addresses the problem of data-stream mining to deal with applications that require processing huge amounts of data such as sensor data analysis and financial applications. Data-stream mining algorithms ...
    • Type-Safe Computation With Heterogeneous Data 

      Huang, Freeman Yufei (2007-09-14)
      Computation with large-scale heterogeneous data typically requires universal traversal to search for all occurrences of a substructure that matches a possibly complex search pattern, whose context may be different in ...
    • Using Deep Learning to predict the mortality of Leukemia patients 

      Muthalaly, Reena Shaw
      “If it were not for the great variability among individuals, medicine might as well be a science, not an art.” Sir William Osler, Canadian physician and McGill alumnus, quoted in 1892. Personalized medicine is ...
    • Using Topic Models to Support Software Maintenance 

      Grant, Scott (2012-04-30)
      Latent topic models are statistical structures in which a "latent topic" describes some relationship between parts of the data. Co-maintenance is defined as an observable property of software systems under source control ...