• KIPS Transactions on Software and Data Engineering
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• v.6 no.2
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• pp.85-90
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• 2017

Various mobile devices are spreading in recent developments in mobile computing environments. Especially the popularity of mobile devices equipped with GPS has become widespread, and various application services utilizing location information are born. In this paper, we propose a system model for storing and managing the trajectory of moving objects, which is the set of location information of moving objects acquired in continuous time, and the UDF (User-Defined Functions) based trajectory index method which can quickly query the large data set of moving object and the Pre-Materialized table method. Then we compare and evaluate the performance of each method through experiments. Experimental results show that the Pre-Materialized table method is about 1.2 times faster than the UDF based trajectory index method on execution time.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.2
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• pp.280-285
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• 2007

This paper proposes a technique improving performance using word senses and user feedback in web information retrieval, compared with the retrieval based on ambiguous user query and index. Disambiguation using word senses is very important processing for improving performance by eliminating the irrelevant pages from the result. According to semantic categories of nouns which are used as index for retrieval, we build the word sense knowledge-base and categorize the web pages. It can improve the performance of retrieval system with user feedback deciding the query sense and information seeking behavior to web pages.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.9
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• pp.2717-2738
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• 2024

Cloud computing has extensively grown in recent years. A large amount of data is stored in cloud servers. To ensure confidentiality, these data is often encrypted and then stored in cloud servers. However, encryption makes range queries difficult to perform. To solve this issue, we present a scheme that facilitates fast range queries on encrypted multi-dimensional data in scenarios involving multiple users. In our scheme, we construct a tree index on encrypted multi-dimensional data, and each node is linked to a secure enhanced multi-dimensional range (MDR). To support efficient range query on the tree index, we adopt bloom filter technique. Additionally, users' privileges are designed in a one-way calculation manner to support that different users can only perform range queries within their own privileges. Finally, we conduct extensive experiments which show the efficiency of our scheme, and also conduct a thorough analysis of its security.

• Journal of KIISE:Databases
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• v.36 no.2
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• pp.112-122
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• 2009

The EPCglobal leading the development in RFID standards proposed Event Cycle Specification (ECSpec) and Event Cycle Reports (ECReports) for the standard about RFID middleware interface. ECSpec is a specification for filtering and collecting RFID tag data and is treated as a Continuous Query (CQ) processed during fixed time intervals repeatedly. ECReport is a specification for describing the results after ECSpec is processed. Thus, it is efficient to apply Query Indexing technique designed for the continuous query processing. This query index processes ECSpecs as data and tag events as queries for efficiency. In logistics environment, the similar or same products are transferred together. Also, when RFID tags attached to the products are acquired, the acquisition events occur massively for the short period. For these properties, it is inefficient to process the massive events one by one. In this paper, we propose a technique reducing similar search process by considering tag events which are collected by the report period in ECSpec, as a range query. For this group processing, we suggest a queuing method for collecting tag events efficiently and a structure for generating range queries in the queues. The experiments show that performance is enhanced by the proposed methods.

• Journal of the Korea Computer Industry Society
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• v.4 no.4
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• pp.613-624
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• 2003

This paper proposes a design for efficient and accurate retrieval of similar image subsequences using the multi-dimensional time warping distance as similarity evaluation tool in image sequence database after building of two indexing structures implemented with priority queue and suffix tree respectively. Receiving query image sequence, at first step, the proposed method searches the candidate set of similar image subsequences in priory queue index structure. If it can not get satisfied results, it retrieves another candidate set in suffix tree index structure at second step. The using of the low-bound distance function can remove the dissimilar subsequence without false dismissals during similarity evaluating process between query image sequence and stored sequences in two index structures.

• Journal of Industrial Technology
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• v.21 no.A
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• pp.167-179
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• 2001

This paper discusses an index-based subsequence matching that supports time warping in large sequence databases. Time warping enables finding sequences with similar patterns even when they are of different lengths. In earlier work, we suggested an efficient method for whole matching under time warping. This method constructs a multidimensional index on a set of feature vectors, which are invariant to time warping, from data sequences. For filtering at feature space, it also applies a lower-bound function, which consistently underestimates the time warping distance as well as satisfies the triangular inequality. In this paper, we incorporate the prefix-querying approach based on sliding windows into the earlier approach. For indexing, we extract a feature vector from every subsequence inside a sliding window and construct a multi-dimensional index using a feature vector as indexing attributes. For query precessing, we perform a series of index searches using the feature vectors of qualifying query prefixes. Our approach provides effective and scalable subsequence matching even with a large volume of a database. We also prove that our approach does not incur false dismissal. To verily the superiority of our method, we perform extensive experiments. The results reseal that our method achieves significant speedup with real-world S&P 500 stock data and with very large synthetic data.

• Journal of the Korean Society for Library and Information Science
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• v.6
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• pp.87-103
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• 1979

Information storage and retrieval is a part of general communication process. In the Shannon's information theory, information contained in a message is a measure of -uncertainty about information source and the amount of information is measured by entropy. Indexing is a process of reducing entropy of information source since document collection is divided into many smaller groups according to the subjects documents deal with. Significant concepts contained in every document are mapped into the set of all sets of index terms. Thus index itself is formed by paired sets of index terms and documents. Without indexing the entropy of document collection consisting of N documents is $log_2\;N$, whereas the average entropy of smaller groups $(W_1,\;W_2,...W_m)$ is as small $(as\;(\sum\limits^m_{i=1}\;H(W_i))/m$. Retrieval efficiency is a measure of information system's performance, which is largely affected by goodness of index. If all and only documents evaluated relevant to user's query can be retrieved, the information system is said $100\%$ efficient. Document file W may be potentially classified into two sets of relevant documents and non-relevant documents to a specific query. After retrieval, the document file W' is reclassified into four sets of relevant-retrieved, relevant-not retrieved, non-relevant-retrieved and non-relevant-not retrieved. It is shown in the paper that the difference in two entropies of document file Wand document file W' is a proper measure of retrieval efficiency.

• Journal of Information Processing Systems
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• v.14 no.5
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• pp.1087-1101
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• 2018

As cloud computing has become a widespread technology, malicious attackers can obtain the private information of users that has leaked from the service provider in the outsourced databases. To resolve the problem, it is necessary to encrypt the database prior to outsourcing it to the service provider. However, the most existing data encryption schemes cannot process a query without decrypting the encrypted databases. Moreover, because the amount of the data is large, it takes too much time to decrypt all the data. For this, Programmable Order-Preserving Secure Index Scheme (POPIS) was proposed to hide the original data while performing query processing without decryption. However, POPIS is weak to both order matching attacks and data count attacks. To overcome the limitations, we propose a group order-preserving data encryption scheme (GOPES) that can support efficient query processing over the encrypted data. Since GOPES can preserve the order of each data group by generating the signatures of the encrypted data, it can provide a high degree of data privacy protection. Finally, it is shown that GOPES is better than the existing POPIS, with respect to both order matching attacks and data count attacks.

• Journal of Korea Spatial Information System Society
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• v.6 no.2 s.12
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• pp.51-62
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• 2004

Recently, the location-based service for moving customers is becoming one of the most important service in mobile communication area. For moving object applications, there are lots of update operations and such update loads are concentrated on some particular area unevenly. The primary processing of LBS application is spatio-temporal range queries. To improve the throughput of spatio-temporal range queries, the time of disk I/O in query processing should be reduced. In this paper, we adopt non-uniform two-level grid index structures of GALIS architecture,which are designed to minimize update operations. We propose query scheduling technique using spatial relationship and time relationship and a combined spatio-temporal query processing method using time zone concepts to improve the throughput of query processing. Some experimental results are shown for range queries with different query range to show the performance tradeoffs of the proposed methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.10
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• pp.2224-2229
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• 2012

Since sensor data are inserted into a data set continuously, continuous queries should be evaluated for searching data. To processing the continuous queries, it is required to build a query index on each sensor node and to transmit result data appropriate for query predicates. However, if query predicates are transferred to all sensor nodes, massive messages are required. In this paper, we propose the node decision scheme using the sensor node decision tree in order to diminish messages. The entry of a leaf node in the node decision tree represents a sensor node and defines the data region of the sensor node. When a user query is issued, sensor nodes are decided by intersecting between data regions of the tree with the query predicates of the user query, and then the query predicates are transmitted to the selected sensor nodes. We also implement the proposed sensor node decision tree and evaluate the experiments for the tree.