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    Mining frequent arrangements of temporal intervals

    Papapetrou, Panagiotis and Kollios, G. and Sclaroff, S. and Gunopulos, D. (2009) Mining frequent arrangements of temporal intervals. Knowledge and Information Systems 21 (2), pp. 133-171. ISSN 0219-1377.

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    Abstract

    The problem of discovering frequent arrangements of temporal intervals is studied. It is assumed that the database consists of sequences of events, where an event occurs during a time-interval. The goal is to mine temporal arrangements of event intervals that appear frequently in the database. The motivation of this work is the observation that in practice most events are not instantaneous but occur over a period of time and different events may occur concurrently. Thus, there are many practical applications that require mining such temporal correlations between intervals including the linguistic analysis of annotated data from American Sign Language as well as network and biological data. Three efficient methods to find frequent arrangements of temporal intervals are described; the first two are tree-based and use breadth and depth first search to mine the set of frequent arrangements, whereas the third one is prefix-based. The above methods apply efficient pruning techniques that include a set of constraints that add user-controlled focus into the mining process. Moreover, based on the extracted patterns a standard method for mining association rules is employed that applies different interestingness measures to evaluate the significance of the discovered patterns and rules. The performance of the proposed algorithms is evaluated and compared with other approaches on real (American Sign Language annotations and network data) and large synthetic datasets.

    Metadata

    Item Type: Article
    Keyword(s) / Subject(s): sequential pattern mining, data mining, temporal mining, arrangement mining, constraint-based mining, arrangement rule mining, American sign language
    School: Birkbeck Schools and Departments > School of Business, Economics & Informatics > Computer Science and Information Systems
    Depositing User: Sarah Hall
    Date Deposited: 01 Aug 2013 09:59
    Last Modified: 01 Aug 2013 09:59
    URI: http://eprints.bbk.ac.uk/id/eprint/7881

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