• The KIPS Transactions:PartD
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• v.14D no.6
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• pp.615-622
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• 2007

Recently, users who want to be provided motile devices, such as PDP, PMP, and IPTV connected wireless internet, with multimedia contents are increasing due to an influence of multimedia contents. In the paper, we propose an efficient database design method for managing mobile multimedia services on home network systems. For this, we build relations using attributes required while providing multimedia services, and then design a database. Specially, we propose a database design method based on normalization theory to eliminate redundancies and update anomalies caused by a non trivial multi valued dependency in relations. In the experiments, we compare and analyze occurrence frequencies of data redundancies and update anomalies through query executions on the relation decomposed into normal forms. The results reveal that our database design is failrly effective.

• Journal of KIISE:Databases
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• v.33 no.1
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• pp.12-31
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• 2006

The n-gram inverted index has two major advantages: language-neutral and error-tolerant. Due to these advantages, it has been widely used in information retrieval or in similar sequence matching for DNA and Protein databases. Nevertheless, the n-gram inverted index also has drawbacks: the size tends to be very large, and the performance of queries tends to be bad. In this paper, we propose the two-level n-gram inverted index (simply, the n-gram/2L index) that significantly reduces the size and improves the query performance while preserving the advantages of the n-gram inverted index. The proposed index eliminates the redundancy of the position information that exists in the n-gram inverted index. The proposed index is constructed in two steps: 1) extracting subsequences of length m from documents and 2) extracting n-grams from those subsequences. We formally prove that this two-step construction is identical to the relational normalization process that removes the redundancy caused by a non-trivial multivalued dependency. The n-gram/2L index has excellent properties: 1) it significantly reduces the size and improves the Performance compared with the n-gram inverted index with these improvements becoming more marked as the database size gets larger; 2) the query processing time increases only very slightly as the query length gets longer. Experimental results using databases of 1 GBytes show that the size of the n-gram/2L index is reduced by up to 1.9${\~}$2.7 times and, at the same time, the query performance is improved by up to 13.1 times compared with those of the n-gram inverted index.