• Journal of Preventive Medicine and Public Health
• /
• v.34 no.4
• /
• pp.389-398
• /
• 2001

Objectives : To investigate the information searching behavior of health care consumers according to sociodemographic characteristics. Methods : A questionnaire survey was conducted of 1,507 persons who were selected through a multi-stage stratified area cluster sampling of the Republic of Korea, excluding the province of Jeiu-do. Personal were conducted through a door-to-door survey between 27 July and 10 August 1999. Results : 80.5% of respondents used more than one source of information and those $40\sim59$ years of age, female, a housewife or student and those who claimed a religion demonstrated more active information searching behavior. A personal informer was used significantly more in those $20\sim39$ years old, female, and those who claimed a religion. Clerical workers, those with post-secondary education and a monthly income greater than 2,000,000 won ($1500) were more actively used a public informer. Low socioeconomic status and older persons used an experimental informer when they chose a health care institution. Conclusion : Regardless of the sociodemographic characteristics, personal and experimental informers were the most useful source of information. Because appropriate information was not easy to obtain, the health care consumer was dependent upon word-of-mouth communication(personal informer) when using health care services.

• Journal of Internet Computing and Services
• /
• v.7 no.2
• /
• pp.9-21
• /
• 2006

Researches on enhancing the searching function of the web service using the ontology concept have been studying. One of them suggests a searching method for UDDI using DAML and DAML+OIL. However this approach has inconveniences to use operations proper to the circumstance and to define respective ontologies according to them. To solve these problems, we introduce an effective method of dealing with N-Triple, filtering care Triples, merging Triples, semantic connection between Triples and searching Triples for searching information and recommending the results in semantic web environment. Furthermore, we implement this proposed method in a system to test it. Finally, we test the system in the virtual semantic web environment for out research analysis.

• Journal of Korea Multimedia Society
• /
• v.6 no.2
• /
• pp.259-266
• /
• 2003

In this paper, we propose a multi-level block matching algorithm using motion information in blocks. In the proposed algorithm, the block-level is decided by the motion degree in the block before motion searching procedure, and then adequate motion searching performs according to the block-level. This improves computational efficiency by eliminating the unnecessary searching Process in no motion or low motion regions, and brings more accurate estimation results by deepening motion searching Process in high motion regions. Simulation results show that the proposed algorithm brings the lower estimation error about 20％ MSE reduction with the fewer blocks pet frame and the operation number was reduced to 56% compared to TSSA and 98% compared to FS -BMA with constant block size.

• Journal of Korea Multimedia Society
• /
• v.6 no.2
• /
• pp.332-339
• /
• 2003

To solve the large scale optimization problem approximately, various approaches have been introduced. Recently the Particle Swarm Optimization has been introduced. The Particle Swarm Optimization simulates the process of birds flocking or fish schooling for food, as with the information of each agent is skated by other agents. The Particle Swarm Optimization technique has been applied to various optimization problems whose variables are continuous. However, there are seldom trials for visualization of searching process. This paper proposes a new visualization tool for searching process of Particle Swarm Optimization algorithm. The proposed tool is effective for understanding the searching process of Particle Swarm Optimization method and educational for students. The computational results can be shown tiny and very helpful for education.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.16 no.7
• /
• pp.640-650
• /
• 1991

In the paper, the threepoint search algorithm used direct search method for optimal design is proposed. Proposed algorithm is composed of two iteration procedure to determine the minimum value of performance index. The minumum value of three-point existing in the inner N-order searching is firstly determined and next searching space is then reduced by the result of first procedure. To compute performance index. 3N iteration for a searching is necessary. 3N searching method is also described and confirmed with exception of parameter included multiphicator and divisor. Proposed algorithm have good stability and reliability when performance index is linear or quadratic function.

• International Journal of Computer Science & Network Security
• /
• v.24 no.5
• /
• pp.79-88
• /
• 2024

The information retrieval domain deals with the retrieval of unstructured data such as text documents. Searching documents is a main component of the modern information retrieval system. Locality Sensitive Hashing (LSH) is one of the most popular methods used in searching for documents in a high-dimensional space. The main benefit of LSH is its theoretical guarantee of query accuracy in a multi-dimensional space. More enhancement can be achieved to LSH by adding a bit to its steps. In this paper, a new Dynamic Locality Sensitive Hashing (DLSH) algorithm is proposed as an improved version of the LSH algorithm, which relies on employing the hierarchal selection of LSH parameters (number of bands, number of shingles, and number of permutation lists) based on the similarity achieved by the algorithm to optimize searching accuracy and increasing its score. Using several tampered file structures, the technique was applied, and the performance is evaluated. In some circumstances, the accuracy of matching with DLSH exceeds 95% with the optimal parameter value selected for the number of bands, the number of shingles, and the number of permutations lists of the DLSH algorithm. The result makes DLSH algorithm suitable to be applied in many critical applications that depend on accurate searching such as forensics technology.

• Korean Institute of Interior Design Journal
• /
• v.23 no.2
• /
• pp.90-98
• /
• 2014

This study has analyzed the meaning of observation time in the course of acquiring the information of subjects who observed the space of hall in subway stations to figure out the process of spatial information excluded and the features of intensive searching. The followings are the results from the analysis of searching process with the interpretation of the process for information acquirement through the interpretation of observation area and time. First, based on the general definition of observation time, the reason for analyzing the features of acquiring spatial information according to the subjects' observation time has been established. The feature of decreased analysis data reflected that of observation time in the process of perceiving and recognizing spatial information, which showed that the observation was focused on the enter of the space during the time spent in the process of observing the space and the spent time with considerable exclusion of bottom end (in particular, right bottom end). Second, while the subjects were observing the space of hall in subway stations, they focused on the top of the left center and the signs on the right exit the most, which was followed by the focus on the both side horizontally and the clock on the top. Third, the analysis of consecutive observation frequency enabled the comparison of the changes to the observation concentration by area. The difference of time by area produced the data with which the change to the contents of spatial searching in the process of searching space could be known. Fourth, as the observation frequency in the area of I changed [three times -> six times -> 9 times], the observation time included in the area increased, which showed the process for the change from perception to recognition of information with the concentration of attention through visual information. It makes it possible to understand that more time was spent on the information to be acquired with the exclusion of the unnecessary information around.

• Spatial Information Research
• /
• v.22 no.4
• /
• pp.21-38
• /
• 2014

Since users who search maps conduct their searching using the name they already know or is commonly called rather than formal name of a specific place, they tend to fail to find their destination. In addition, in typical web map service in terms of spatial searching of map. Location information of unintended place can be provided because when spatial searching is conducted with the vocabulary 'nearby' and 'in the vicinity', location exceeding 2 km from the current location is searched altogether as well. In this research, spatial range that human can perceive is calculated by extracting POI date with the usage of twitter data of SNS, constructing spatial relations with existing POI, which is already constructed. As a result, various place names acquired could be utilized as different names of existing POI data and it is expected that new POI data would contribute to select places for constructing POI data by utilizing to recognize places having lots of POI variation. Besides, we also expect efficient spatial searching be conducted using diverse spatial vocabulary which can be used in spatial searching and spatial range that human can perceive.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.12 no.6
• /
• pp.1-9
• /
• 2013

The studies on the shortest path algorithms based on Dijkstra algorithm has been done continuously to decrease the time for searching. $A^*$ algorithm is the most represented one. Although fast searching speed is the major point of $A^*$ algorithm, there are high rates of failing in search of the shortest path, because of complex and irregular networks. The failure of the search means that it either did not find the target node, or found the shortest path, witch is not true. This study proposed $A^*$ algorithm applying method that can reduce searching failure rates, preferentially organizing the relations between the starting node and the targeting node, and appling it in reverse according to the organized path. This proposed method may not build exactly the shortest path, but the entire failure in search of th path would not occur. Following the developed algorithm tested in a real complex networks, it revealed that this algorithm increases the amount of time than the usual $A^*$ algorithm, but the accuracy rates of the shortest paths built is very high.

• Journal of KIISE:Computer Systems and Theory
• /
• v.29 no.8
• /
• pp.456-462
• /
• 2002

We are developing searching algorithms for weighted strings such as protein sequences. Let${\sum}$ be an alphabet and for each $a{\in}{\sum}$ its weight ${\mu}(a)$ is given. Given a string $A=a_1a_2…a_n\; with each ai{\in}{\sum}$, a substring<$A(i.j)=a_ia_{i+1}…a_j$ has weight ${\in}(A(i.j))={\in}(a_i)+{\in}(a_i+1)+…+{\in}(a_j)$.The problem we are dealing with is to preprocess A to build a searching structure, and later, given a query weight M, the structure is used to answer the question of whether there is a substring A(i,j) such that$M={\in}(A(i,j))$.In this paper an algorithm that improves over the previous result will be presented. The previously best known algorithm answers a query in $0(\frac{nlog\;logn}{log\; n})$time using a searching structure that requires O(n) amount of memory. Our algorithm reduces the memory requirement to $0(\frac{n}{log\; n})$ while achieving the same query answer time.