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Author: search.filters.author.Pushpalatha, K.Subject: search.filters.subject.Multimedia documents

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    Feature pattern based representation of multimedia documents for efficient knowledge discovery
    (Springer New York LLC barbara.b.bertram@gsk.com, 2016) Pushpalatha, K.; Ananthanarayana, V.S.
    The rapid growth of multimedia documents has raised huge demand for sophisticated multimedia knowledge discovery systems. The knowledge extraction of the documents mainly relies on the data representation model and the document representation model. As the multimedia document comprised of multimodal multimedia objects, the data representation depends on modality of the objects. The multimodal objects require distinct processing and feature extraction methods resulting in different features with different dimensionalities. Managing multiple types of features is challenging for knowledge extraction tasks. The unified representation of multimedia document benefits the knowledge extraction process, as they are represented by same type of features. The appropriate document representation will benefit the overall decision making process by reducing the search time and memory requirements. In this paper, we propose a domain converting method known as Multimedia to Signal converter (MSC) to represent the multimodal multimedia document in an unified representation by converting multimodal objects as signal objects. A tree based approach known as Multimedia Feature Pattern (MFP) tree is proposed for the compact representation of multimedia documents in terms of features of multimedia objects. The effectiveness of the proposed framework is evaluated by performing the experiments on four multimodal datasets. Experimental results show that the unified representation of multimedia documents helped in improving the classification accuracy for the documents. The MFP tree based representation of multimedia documents not only reduces the search time and memory requirements, also outperforms the competitive approaches for search and retrieval of multimedia documents. © 2016, Springer Science+Business Media New York.
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    A tree based representation for effective pattern discovery from multimedia documents
    (Elsevier B.V., 2017) Pushpalatha, K.; Ananthanarayana, A.
    The growing amount of multimedia documents demanded the efficient knowledge discovery systems. The efficacy of the knowledge discovery systems is influenced by the representation of multimedia documents. The suitable multimedia document representation acts as a platform for multimedia mining tasks. In this paper, a Multimedia Suffix Tree Document model (MSTD) is presented to represent the multimedia documents in a tree based structure. The MSTD model discovers the useful patterns embedded in the multimedia documents and reduces the search time thereby aiding the multimedia mining methods. It provides the complete information of the multimedia documents in one structure. In order to evaluate the proficiency of the proposed MSTD model, the MSTD model based mining methods are proposed. The experiments are conducted with three multimodal multimedia document datasets. The experimental analysis of the proposed methods reveal the significance of MSTD representation for multimedia documents in achieving the significant performance of multimedia mining tasks. © 2016 Elsevier B.V.