Blar i TKD - Institutt for informasjonsteknologi på emneord "Data mining"

Viser treff 1-7 av 7

    • Associating Absent Frequent Itemsets with Infrequent Items to Identify Abnormal Transactions 

      Kao, Li-Jen; Huang, Yo-Ping; Sandnes, Frode Eika (Applied intelligence;42(4), Journal article; Peer reviewed, 2014-12-07)
      Data stored in transactional databases are vulnerable to noise and outliers and are often discarded at the early stage of data mining. Abnormal transactions in the marketing transactional database are those transactions ...

    • Discovering Fuzzy Association Rules from Patient's Daily Text Messages to Diagnose Melancholia 

      Huang, Yo-Ping; Chiu, Hong-Wen; Chuan, Wei-Po; Sandnes, Frode Eika (Chapter; Peer reviewed, 2010)
      With the constant stress from work load and daily life people may show symptoms of melancholia. However, most people are reluctant to describe it or may not know that they already have it. In this paper a novel system ...

    • Efficient quantile tracking using an oracle 

      Hammer, Hugo Lewi; Yazidi, Anis; Riegler, Michael; Rue, Håvard (Applied intelligence (Boston);, Peer reviewed; Journal article, 2022-04-14)
      Concept drift is a well-known issue that arises when working with data streams. In this paper, we present a procedure that allows a quantile tracking procedure to cope with concept drift. We suggest using expected quantile ...

    • Experiences with RFID-Based Interactive Learning in Museums 

      Huang, Yo-Ping; Chang, Yueh-Tsun; Sandnes, Frode Eika (International Journal of Autonomous and Adaptive Communications Systems;3 (1), Journal article; Peer reviewed, 2010)
      Tourism plays an important role in the economies of many countries. Tourism can secure employment, foreign exchange earnings, investment and regional development. To attract more tourists and local visitors, many stakeholders ...

    • A Fuzzy ART2 Model for Finding Association Rules in Medical Data 

      Huang, Yo-Ping; Vu, Thi Thanh Hoa; Jau, Jung-Shian; Sandnes, Frode Eika (Chapter; Peer reviewed, 2010-09)
      This paper describes a model that discovers association rules from a medical database to help doctors treat and diagnose a group of patients who show similar prehistoric medical symptoms. The proposed data mining ...

    • Joint tracking of multiple quantiles through conditional quantiles 

      Hammer, Hugo Lewi; Yazidi, Anis; Rue, Håvard (Information Sciences;Volume 563, July 2021, Peer reviewed; Journal article, 2021-03-05)
      The estimation of quantiles is one of the most fundamental data mining tasks. As most real-time data streams vary dynamically over time, there is a quest for adaptive quantile estimators. The most well-known type of adaptive ...

    • Unsupervised and Fast Continent Classification of Digital Image Collections using Time 

      Sandnes, Frode Eika (Chapter; Peer reviewed, 2010-08)
      Advances in storage capacity means that digital cameras can store huge collections of digital photographs. Typically such images are given non-descriptive filenames names such as a unique identifier, often an integer. ...