• International journal of advanced smart convergence
• /
• v.12 no.1
• /
• pp.1-8
• /
• 2023

Smart IoT over high speed network and high performance smart devices explodes the ubiquitous services and applications. Nearest Neighbor(NN) query is one of the important type of queries that have to be supported for ubiquitous information services. In order to process efficiently NN queries in the wireless broadcast environment, it is important that the clients determine quickly the search space and filter out NN from the candidates containing the search space. In this paper, we propose a hybrid index of Voronoi and grid partition to provide quick search space decision and rapid filtering out NN from the candidates. Grid partition plays the role of helping quick search space decision and Voronoi partition providing the rapid filtering. We show the effectiveness of the proposed index by comparing the existing indexing schemes in the access time and tuning time. The evaluation shows the proposed index scheme makes the two performance parameters improved than the existing schemes.

• Journal of KIISE:Databases
• /
• v.33 no.5
• /
• pp.513-525
• /
• 2006

Search results of XML keyword search are defined generally as the most specific elements containing all query keywords in the literature. The labels of XML elements and semantic information such as ontology, conceptual model, thesaurus, and so on, are used to improve the preciseness of the search results. This paper presents a hierarchical index for an efficient XML keyword query processing on the condition that returnable search concepts are defined and users' query concepts can be interpreted with the help of the semantic information. The hierarchical index separately stores the XML elements containing a keyword on the basis of the hierarchical relations of the concepts that the XML elements belong to, and makes it possible to obtain least common ancestors, which are candidates for the search results, with selectively reading the elements belonging to the concepts relevant to query concepts and without considering all the combinations of the elements having been read. This paper deals with how to organize the hierarchical index and how to process XML keyword queries with the index. In our experiment with the DBLP XML document and the XML documents in the INEX2003 test set, the hierarchical index worked well.

• Journal of KIISE:Databases
• /
• v.33 no.7
• /
• pp.754-765
• /
• 2006

In XML keyword search, a search result is defined as a set of the smallest elements (i.e., least common ancestors) containing all query keywords and a granularity of indexing is an XML element instead of a document. Under the conventional index structure, all least common ancestors produced by the combination of the elements, each of which contains a query keyword, are considered as a search result. In this paper, to avoid unnecessary operations of producing the least common ancestors and reduce query process time, we describe a way to construct a partitioned index composed of several partitions and produce a search result by merging those partitions if necessary. When a search result is restricted to be composed of the least common ancestors whose depths are higher than a given minimum depth, under the proposed partitioned index structure, search systems can reduce the query process time by considering only combinations of the elements belonging to the same partition. Even though the minimum depth is not given or unknown, search systems can obtain a search result with the partitioned index, which requires the same query process time to obtain the search result with non-partitioned index. Our experiment was conducted with the XML documents provided by the DBLP site and INEX2003, and the partitioned index could reduce a substantial amount of query processing time when the minimum depth is given.

• Journal of the Korean Society for Library and Information Science
• /
• v.32 no.1
• /
• pp.169-187
• /
• 1998

The primary purpose of this study is to compare printed index and abstract user's behaviours with digital index and abstract user's behaviours, and to verify of structured characteristics of a printed index and abstract. The major findings are as follows: (1) When the research topic is not specified enough, users tend to rely on printed indexes and abstracts search, whereas they utilize digital form in order to do retrospective search in the stage of research when the topic is determined. (2) Printed index and abstract users are expecting small number of literatures in search, whereas digital index and abstract users are expecting large number of literatures to be found The former are more satisfied with the result of search than the latter. (3) Digital index and abstract users experience more search failure than printed Index and abstract users. When they fail to find wanted materials, both users turn to the other form of indexes and abstracts. (4) Printed index and abstract users shows significantly less knowledge on online searching than digital index and abstract users.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.15 no.1
• /
• pp.87-97
• /
• 2005

A secure index search protocol let us search the index of encrypted documents using the trapdoor for a keyword. It enables an untrusted server to learn nothing more than the search result about the documents without revealing the keyword. A lot of secure search protocols have been suggested but they only considered the search between a single-user and a server. In real organizations such as government offices or enterprises where exist many hierarchical departments, the search system for groups is arisen more often. In this paper, we construct secure index search protocols for hierarchical group settings without re-encryption of the old encrypted documents when group keys are re-keyed newly.

• International Journal of Contents
• /
• v.1 no.1
• /
• pp.50-58
• /
• 2005

Generally, multidimensional data such as image and spatial data require large amount of storage space. There is a limit to store and manage those large amounts of data in single workstation. If we manage the data on parallel computing environment which is being actively researched these days, we can get highly improved performance. In this paper, we propose a parallel multidimensional index structure that exploits the parallelism of the parallel computing environment. The proposed index structure is nP(processor)-nxmD(disk) architecture which is the hybrid type of nP-nD and 1P-nD. Its node structure in-creases fan-out and reduces the height of an index. Also, a range search algorithm that maximizes I/O parallelism is devised, and it is applied to k-nearest neighbor queries. Through various experiments, it is shown that the proposed method outperforms other parallel index structures.

• Journal of Korean Library and Information Science Society
• /
• v.31 no.1
• /
• pp.87-114
• /
• 2000

The purpose of this study is offering appropriate system and training program to helf the system designer and the trainer in addition to analyze information use behavior about the web search tools and evaluate the estimated system by user groups. The results of the study are as follows $\circledS1$ It is desirable to consider age than other demographic variables in the case of web search tool. $\circledS2$ It is desirable to design Directory Search Tool in the case of web search tool which serves the student user group. $\circledS3$ An Intelligent Search Tool is more appropriate for the students who are using keyword search tool than any other tools. $\circledS4$ A discussion about standard classification of the web information should be accomplished soon because users feel confused in using web search tools due t o absence of standard mode of classification about classified item. $\circledS5$ Librarians need the cognition about data on internet s a source of information and need positive service and user training program about these information because student users hardly get help from librarians or library orientation for learning method to use web search tool. $\circledS6$ Internet use experience and years of computer use had effect on their use ability when using web search tool, whereas computer use experience, library use experience and Online Public Access Catalogs (OPAC) use experience had no effect on it. Especially, OPAC use experience had no effect on use ability of web search tool of student user group because student user groups had no information about internet and web search tool and they did not recognized the difference about search method between web search tool and OPAC. $\circledS7$In the case of web search tool, it si important to index the increasing web resource automatically by a searching robot. But in the case of student users, web search tool is much more needed to index by index expert due to the absence of ability about selecting and combining keyword.

• Journal of Electrical Engineering and Technology
• /
• v.13 no.4
• /
• pp.1724-1731
• /
• 2018

The conventional polynomial neural network (PNN) is a classical flexible neural structure and self-organizing network, however it is not free from the limitation of overfitting problem. In this study, we propose a space search-optimized polynomial neural network (ssPNN) structure to alleviate this problem. Ranking selection is realized by means of ranking selection-based performance index (RS_PI) which is combined with conventional performance index (PI) and coefficients based performance index (CPI) (viz. the sum of squared coefficient). Unlike the conventional PNN, L2-norm regularization method for estimating the polynomial coefficients is also used when designing the ssPNN. Furthermore, space search optimization (SSO) is exploited here to optimize the parameters of ssPNN (viz. the number of input variables, which variables will be selected as input variables, and the type of polynomial). Experimental results show that the proposed ranking selection-based polynomial neural network gives rise to better performance in comparison with the neuron fuzzy models reported in the literatures.

• Journal of KIISE:Databases
• /
• v.31 no.6
• /
• pp.710-720
• /
• 2004

As XML documents have much richer information than plain texts, we can perform very elaborated, fine-grained search which was difficult in past years. However, as the cost of finer grained element level search is very high, the processing overhead has become a new challenge. We propose an inverted index structure called PIX, which reduces the number of elements processed by partitioning elements according to their match potentiality. We choose a base level and partition elements according to whether they have possibility of having a common ancestor higher than the level. We also propose partition merging technique by which we can get same results as unpartitioned case. Our experimental results show that the index partitioning strategy can reduce processing time considerably.

• The Journal of the Korea Contents Association
• /
• v.9 no.9
• /
• pp.80-89
• /
• 2009

A fast and efficient search algorithm to determine an optimal number of clusters in clustering algorithms is presented. The method is based on cluster validity index which is a measure for clustering optimality. As the clustering procedure progresses and reaches an optimal cluster configuration, the cluster validity index is expected to be minimized or maximized. In this Paper, a fast non-exhaustive search method for finding the optimal number of clusters is designed and shown to work well in clustering. The proposed algorithm is implemented with the k-mean++ algorithm as underlying clustering techniques using CB and PBM as a cluster validity index. Experimental results show that the proposed method provides the computation time efficiency without loss of accuracy on several artificial and real-life data sets.