• Proceedings of the Korean Information Science Society Conference
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• 2003.10a
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• pp.169-171
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• 2003

웹에서의 검색 방법에는 크게 Text-Based 기법과 Link-Based 기법이 있다. 본 논문은 그 중에서 Link-Based 기법의 하나인 PageRank 알고리즘에 대해 연구 하고자 한다. 이 PageRank 알고리즘은 각 페이지의 중요성을 수치로 계산하는 방법이다. 하지만 이 알고리즘에서는 페이지에서 페이지로 링크를 따라갈 확률의 값을 일정하게 주어서 모든 페이지의 값을 획일적으로 계산하였기 때문에 각 페이지의 검색 효율성에 문제가 있다고 판단하여, 이를 해결하고자 본 논문은 페이지사이의 유사도를 측정하여 유사도에 따라 링크를 따라가는 확률 값인 Damping factor값을 다르게 부여하여 검색의 효율성을 높였다. 이를 위하여 두 가지 방법의 실험을 통하여 구현, 증명하였다.

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

• Journal of Information Processing Systems
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• v.13 no.4
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• pp.914-927
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• 2017

Weighted network link prediction is a challenge issue in complex network analysis. Unsupervised methods based on local structure are widely used to handle the predictive task. However, the results are still far from satisfied as major literatures neglect two important points: common neighbors produce different influence on potential links; weighted values associated with links in local structure are also different. In this paper, we adapt an effective link prediction model-local naive Bayes model into a weighted scenario to address this issue. Correspondingly, we propose a weighted local naive Bayes (WLNB) probabilistic link prediction framework. The main contribution here is that a weighted cluster coefficient has been incorporated, allowing our model to inference the weighted contribution in the predicting stage. In addition, WLNB can extensively be applied to several classic similarity metrics. We evaluate WLNB on different kinds of real-world weighted datasets. Experimental results show that our proposed approach performs better (by AUC and Prec) than several alternative methods for link prediction in weighted complex networks.

• Korean Journal of Environmental Biology
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• v.42 no.2
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• pp.207-218
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• 2024

Food webs have received global attention as next-generation biomonitoring tools; however, it remains challenging because revealing trophic links between species is costly and laborious. Although a link-extrapolation method utilizing published trophic link data can address this difficulty, it has limitations when applied to construct food webs in domestic streams due to the lack of information on endemic species in global literature. Therefore, this study aimed to develop a link extrapolation-based food web model adapted to Korean stream ecosystems. We considered taxonomic similarity of predation and dominance of generalists in aquatic ecosystems, designing taxonomically higher-level matching methods: family matching for all fish (Family), endemic fish (Family-E), endemic fish playing the role of consumers (Family-EC), and resources (Family-ER). By adding the commonly used genus matching method (Genus) to these four matching methods, a total of five matching methods were used to construct 103 domestic food webs. Predictive power of both individual links and food web indices were evaluated by comparing constructed food webs with corresponding empirical food webs. Results showed that, in both evaluations, proposed methods tended to perform better than Genus in a data-poor environment. In particular, Family-E and Family-EC were the most effective matching methods. Our model addressed domestic data scarcity problems when using a link-extrapolation method. It offers opportunities to understand stream ecosystem food webs and may provide novel insights into biomonitoring.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2030-2052
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• 2023

Analysis of a bipartite (two-mode) network is a significant research area to understand the formation of social communities, economic systems, drug side effect topology, etc. in complex information systems. Most of the previous works talk about a projection-based model or latent feature model, which predicts the link based on singular similarity. The projection-based models suffer from the loss of structural information in the projected network and the latent feature is hardly present. This work proposes a novel method for link prediction in the bipartite network based on an ensemble of composite similarities, overcoming the issues of model-based and latent feature models. The proposed method analyzes the structure, neighborhood nodes as well as latent attributes between the nodes to predict the link in the network. To illustrate the proposed method, experiments are performed with five real-world data sets and compared with various state-of-art link prediction methods and it is inferred that this method outperforms with ~3% to ~9% higher using area under the precision-recall curve (AUC-PR) measure. This work holds great significance in the study of biological networks, e-commerce networks, complex web-based systems, networks of drug binding, enzyme protein, and other related networks in understanding the formation of such complex networks. Further, this study helps in link prediction and its usability for different purposes ranging from building intelligent systems to providing services in big data and web-based systems.

• Speech Sciences
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• v.8 no.2
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• pp.181-191
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• 2001

The acoustic quality of a vowel is known to be mostly determined by the frequencies of the first formant(Fl) and the second formant(F2). The perceptual(or psychological) dimensions of vowel perception were examined in this study. Also the relationships among perceptual dimensions, acoustical dimensions(Fl & F2), and articulatory gestures of vowel were discussed. Using multi-dimensional scaling(MDS) technique, the experiment was performed in order to identify the perceptual dimensions of the perception of Korean vowel. In the experiment 8 Seoul standard speakers performed the similarity rating task of 10 synthesized Korean vowels. Two-dimensional MDS solution based. on the similarity rating scores was obtained. The results showed that two perceptual dimensions, D1 and D2 were correlated strongly with F2 and F1(r = -.895 and .878 respectively), and were so interpreted as 'vowel advancement' and 'vowel height' respectively. The relationship between the perceptual dimensions of vowel and the articulatory positions of tongue suggested that perception may be directly linked to production. Further research problems were discussed in the .final section.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.1
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• pp.121-128
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• 2005

This paper proposes the heuristic approach for the generalized GT(Group Technology) problem to consider the restrictions which are given the number of cell, maximum number of machines and minimum number of machines. This approach is classified into two stages. In the first stage, we use the similarity coefficient method which is proposed and calculate the similarity values about each pair of all machines and align these values in descending order. If two machines which is selected is possible to link the each other on the edge of machine cell and they don't have zero similarity value, then we assign the machines to the machine cell. In the second stage, it is the course to form part families using proposed grouping efficacy. Finally, machine-part incidence matrix is realigned to block diagonal structure. The results of using the proposed approach are compared to the Modified p-median model.

• Journal of Distribution Science
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• v.21 no.6
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• pp.69-81
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• 2023

Purpose: The study investigates the moderating impact of interpersonal mindfulness (IM) on the link between perceived similarity (OPS), physical appearance (OPA), and suitable behavior (OSB) - three key factors of other consumer perception (OCP) and brand experience (BE) in distribution of OCP and brand. Research design, data, and methodology: This study collected data from 612 consumers at shopping malls. SmartPLS 3.3.9 software were used to assess the measurement model and structural model. Results: According to the study's findings, IM has a negative modality in the impact between BE and OPS, OPA, and OSB. That also demonstrates how distribution of OCP and brand can affect a person's brand experience. Conclusions: The distribution of OCP and IM interactions have a significant influence on the brand experience in brand distribution. The study's results show that IM including mindfulness will function as a moderator between perceived similarity, physical appearance, suitable behavior regarded proper by other consumers, and brand experiences; therefore, they impact to brand distribution. The findings give a foundation for further IM research and add to the brand distribution theory that already exists. The findings also have some managerial implications in brand distribution.

• The KIPS Transactions:PartB
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• v.11B no.4
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• pp.509-516
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• 2004

Semantic interpretation of image is incomplete without some mechanism for understanding semantic content that is not directly visible. For this reason, human assisted content-annotation through natural language is an attachment of textual description to image. However, keyword-based retrieval is in the level of syntactic pattern matching. In other words, dissimilarity computation among terms is usually done by using string matching not concept matching. In this paper, we propose a method for computerized semantic similarity calculation In WordNet space. We consider the edge, depth, link type and density as well as existence of common ancestors. Also, we have introduced method that applied similarity measurement on semantic image retrieval. To combine wi#h the low level features, we use the spatial color distribution model. When tested on a image set of Microsoft's 'Design Gallery Line', proposed method outperforms other approach.

• The KIPS Transactions:PartC
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• v.18C no.6
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• pp.441-444
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• 2011

In this study, we present a method for efficiently aggregating network state information. It is especially useful for aggregating links that have both delay and bandwidth in an asymmetric network. Proposed method reduces the information distortion of logical link by integration process after similar measure and grouping of logical links in multi-level topology transformation to reduce the space complexity. It is applied to transform the full mesh topology whose Service Boundary Line (SBL) serves as its logical link into a spanning tree topology. Simulation results show that aggregated information accuracy and query response accuracy are higher than that of other known method.