• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.14 no.3
• /
• pp.1-8
• /
• 2015

In transportation networks, searching speed and result accuracy are becoming more critical on searching minimum path algorithm. Current $A^*$ algorithm has a big advantage of high searching speed. However, it has disadvantage of complicated searching network and low accuracy rate of finding the minimum path algorithm. Therefore, this study developed $A^*$ algorithm's heuristic function and focused on improving it's disadvantages. Newly developed function in this study contains the area concept, not the line concept. During the progress, this study adopts the idea of a heavier node that remains lighter to the target node is better that the lighter node that becomes heavier when it is connected to the other. Lastly, newly developed algorithm has the feedback function, which allows the larger accuracy value of heuristic than before. This developed algorithm tested on real network, and proved that developed algorithm is useful.

• Journal of KIISE:Databases
• /
• v.36 no.1
• /
• pp.44-49
• /
• 2009

In recent years, with the development of portable terminals, various searching services on large data have been provided in portable terminals. In order to search large data, most applications for information retrieval use indexes such as B-trees or R-trees. However, only a small portion of the data set is accessed by users, and the access frequencies of each data are not uniform. The existing indexes such as B-trees or R-trees do not consider the properties of the skewed access patterns. And a cache stores the frequently accessed data for fast access in memory. But the size of memory used in the cache is restricted. In this paper, we propose a new index based on disk, called J-tree, which considers user's search patterns. The proposed index is a balanced tree which guarantees uniform searching time on all data. It also supports fast searching time on the frequently accessed data. Our experiments show the effectiveness of our proposed index under various settings.

• Journal of Internet Computing and Services
• /
• v.7 no.2
• /
• pp.71-80
• /
• 2006

In web search engines, there are two main methods: directory searching and keyword searching. Keyword searching shows high recall rate but tends to come up with too many search results to find which users want to see the pages. Directory searching has also a difficulty to find the pages that users want in case of selecting improper category without knowing the exact category, that is, it shows high precision rates but low recall rates. We designed and implemented a new web search engine to resolve the problems of directory search method. It regards a category as a fuzzy set which contains keywords and calculate the degree of inclusion between categories. The merit of this method is to enhance the recall rate of directory searching by expanding subcategories on the basis of similarity.

• Journal of Intelligence and Information Systems
• /
• v.24 no.2
• /
• pp.171-193
• /
• 2018

LOD(Linked Open Data) cloud is a practical implementation of semantic web. We suggested a new method that provides identity links conveniently in LOD cloud. It also allows changes in LOD to be reflected to searching results without any omissions. LOD provides detail descriptions of entities to public in RDF triple form. RDF triple is composed of subject, predicates, and objects and presents detail description for an entity. Links in LOD cloud, named identity links, are realized by asserting entities of different RDF triples to be identical. Currently, the identity link is provided with creating a link triple explicitly in which associates its subject and object with source and target entities. Link triples are appended to LOD. With identity links, a knowledge achieves from an LOD can be expanded with different knowledge from different LODs. The goal of LOD cloud is providing opportunity of knowledge expansion to users. Appending link triples to LOD, however, has serious difficulties in discovering identity links between entities one by one notwithstanding the enormous scale of LOD. Newly added entities cannot be reflected to searching results until identity links heading for them are serialized and published to LOD cloud. Instead of creating enormous identity links, we propose LOD to prepare its own link policy. The link policy specifies a set of target LODs to link and constraints necessary to discover identity links to entities on target LODs. On searching, it becomes possible to access newly added entities and reflect them to searching results without any omissions by referencing the link policies. Link policy specifies a set of predicate pairs for discovering identity between associated entities in source and target LODs. For the link policy specification, we have suggested a set of vocabularies that conform to RDFS and OWL. Identity between entities is evaluated in accordance with a similarity of the source and the target entities' objects which have been associated with the predicates' pair in the link policy. We implemented a system "Change Acceptable In-Depth Searching System(CAIDS)". With CAIDS, user's searching request starts from depth_0 LOD, i.e. surface searching. Referencing the link policies of LODs, CAIDS proceeds in-depth searching, next LODs of next depths. To supplement identity links derived from the link policies, CAIDS uses explicit link triples as well. Following the identity links, CAIDS's in-depth searching progresses. Content of an entity obtained from depth_0 LOD expands with the contents of entities of other LODs which have been discovered to be identical to depth_0 LOD entity. Expanding content of depth_0 LOD entity without user's cognition of such other LODs is the implementation of knowledge expansion. It is the goal of LOD cloud. The more identity links in LOD cloud, the wider content expansions in LOD cloud. We have suggested a new way to create identity links abundantly and supply them to LOD cloud. Experiments on CAIDS performed against DBpedia LODs of Korea, France, Italy, Spain, and Portugal. They present that CAIDS provides appropriate expansion ratio and inclusion ratio as long as degree of similarity between source and target objects is 0.8 ~ 0.9. Expansion ratio, for each depth, depicts the ratio of the entities discovered at the depth to the entities of depth_0 LOD. For each depth, inclusion ratio illustrates the ratio of the entities discovered only with explicit links to the entities discovered only with link policies. In cases of similarity degrees with under 0.8, expansion becomes excessive and thus contents become distorted. Similarity degree of 0.8 ~ 0.9 provides appropriate amount of RDF triples searched as well. Experiments have evaluated confidence degree of contents which have been expanded in accordance with in-depth searching. Confidence degree of content is directly coupled with identity ratio of an entity, which means the degree of identity to the entity of depth_0 LOD. Identity ratio of an entity is obtained by multiplying source LOD's confidence and source entity's identity ratio. By tracing the identity links in advance, LOD's confidence is evaluated in accordance with the amount of identity links incoming to the entities in the LOD. While evaluating the identity ratio, concept of identity agreement, which means that multiple identity links head to a common entity, has been considered. With the identity agreement concept, experimental results present that identity ratio decreases as depth deepens, but rebounds as the depth deepens more. For each entity, as the number of identity links increases, identity ratio rebounds early and reaches at 1 finally. We found out that more than 8 identity links for each entity would lead users to give their confidence to the contents expanded. Link policy based in-depth searching method, we proposed, is expected to contribute to abundant identity links provisions to LOD cloud.

• Proceedings of the Korean Geotechical Society Conference
• /
• 1999.03a
• /
• pp.331-338
• /
• 1999

In the present study, a searching technique for critical slip surface in two dimensional slope stability analysis is proposed. The failure surface generation and analysis has been usually limited to simple geometric shapes. However, more random surfaces need to be examined for some particular ground conditions. For this purpose, random searching technique is developed using genetic algorithm. The generalized limit equilibrium method is employed as the method of stability analysis. Using this technique, the factor of safety is compared with the result by using simplified Bishop's method. In addition, the convergent trend of fitness value is analyzed.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.9 no.3
• /
• pp.145-153
• /
• 2013

Multimedia contents' searching methods in existing mobile computer environment tend to be brought with many over heads when attempting to search data in large bulks. The MINT system has been studied to resolve such problem. However, MINT system delivers many over heads by searching multimedia contents through applying B-Tree. The suggested method is said to be CST-MCR searching system based on CST-Tree. The specific characteristic of this method is improved MINT system by applying CST-Tree's index. The result of capacity evaluation came out with improved capacity of 4.27% from MINT system and CST-MCR methods in average. Conclusively, it has been proven that the suggested method is superior.

• Proceedings of the Acoustical Society of Korea Conference
• /
• 1994.06c
• /
• pp.214-217
• /
• 1994

The major drawback in the Code Excited Linear Prediction type vocoders is their large computational requirements. In this paper, a simple method is proposed to reduce the pitch searching time in the pitch filter almost without degradation of quality. On the basis of the observational regularity of the correlation function of speech, only the limited numbers of pitch lags are considered to be an optimum pitch. This is done by skipping the negative envelope side of the correlation function and limiting the maximum number of lags to be considered preliminarily. By doing so, we can reduce the computational time of pitch searching more than 51% with negligible quality degradation. In addition to that, by combining that method with the conventional delta search technique, we can reduce the computational time requirements more than 60% without serious lowering the speech quality in segmental SNR measure compared to the conventional full search method.

• Journal of Korea Multimedia Society
• /
• v.18 no.8
• /
• pp.925-934
• /
• 2015

The frequency of natural disasters because of global warming is gradually increasing, risks of flooding due to typhoon and torrential rain have also increased. Among these causes, the roads are flooded by suddenly torrential rain, and then vehicle and personal injury are happening. In this respect, because of the possibility that immersion of a road may occur in a second, it is necessary to study the rapid data collection and quick response system. Our research proposes a big data analysis system based on the collected information and a variety of system information collection methods for searching flooded road areas by torrential rains. The data related flooded roads are utilized the SNS data, meteorological data and the road link data, etc. And the big data analysis system is implemented the distributed processing system based on the Hadoop platform.

• Proceedings of the IEEK Conference
• /
• 1998.10a
• /
• pp.887-890
• /
• 1998

We present a novel multi-resolution block matching algorithm (BMA) for fast motion estimation. At the coarsest level, a full search BMA (FSBMA) is performed for searching complex or random motion. Concurrently, spatial correlation of motion vector (MV) field is used for searching continuous motion. Here we present an efficient method for searching full resolution MVs without MV decimation even at the coarsest leve. After the coarsest level search, two or three initial MV candidates are chosen for the next level. At the further levels, the MV candidates are refined within much smaller search areas. Simulation results show that in comparison with FSBMA, the proposed BMA achieves a speed-up factor over 710 with minor PSNR degradation of 0.2dB at most, under a normal MPEG2 coding environment. Furthermore, our scheme is also suitable for hardware implementation due to regular data-flow.

• 한국HCI학회:학술대회논문집
• /
• 2008.02a
• /
• pp.722-727
• /
• 2008

As computer technology and internet industrial are growing, we can buy all kinds of merchandise very easily, However. To find relevant merchandise what we want is very difficult process in various internet mall and greate amount of merchandises. Searching merchandise using some keyword makes a lot of list in limited category, but we can not sure that searching results are relevant or not. For this reason, we proposed a interface using color information of goods that is able to search merchandise effectively.