• The Journal of Information Systems
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• v.8 no.2
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• pp.91-110
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• 1999

Recently, searching agent systems to help purchase of products between business and customer have been actively studied in Electronic Commerce(EC). However, the most of comparative searching agent systems are only provided customers with searching results by the keyword-based search, and is not support the efficient decision models to be selected products considering the customer's requirements. This paper proposes the decision agent system applied decision model as well as searching functions based on the keyword-input to be selected useful products in EC. The proposed decision agent system is consist of the user interface, provider interface, decision model. Especially, as the example of the decision model, this paper is designed and implemented the prototype of decision agent system which is normalized the searching data and value of customer's preference weight as to each attribute, and orderly provided customers with computed results. This agent system is also carried out sensitive analysis according to the reflection ratio of the each attribute.

• The KIPS Transactions:PartD
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• v.18D no.4
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• pp.309-312
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• 2011

Handling fuzzy query in voice search on smartphones is one of the most difficult problems. It is mainly derived from the complexity and the degree of freedom of natural language. To reduce the complexity and the degree of freedom of fuzzy query in voice search on smartphones, attribute-driven approach for fuzzy query is proposed. In addition, a new page ranking algorithm based on the values of attributes for handling fuzzy query is proposed. It provides a smartphone user with location-based personalized page ranking based on user's search intentions. It is a further step toward location-based personalized web search for smartphone users. In this paper, we design a prototype model for handling fuzzy query in voice search on smartphones and show the experimental results of the proposed approach compared to existing smartphones.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.29 no.2
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• pp.13-19
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• 2006

The instance-based learning is a machine learning technique that has proven to be successful over a wide range of classification problems. Despite its high classification accuracy, however, it has a relatively high storage requirement and because it must search through all instances to classify unseen cases, it is slow to perform classification. In this paper, we have presented a new data reduction method for instance-based learning that integrates the strength of instance partitioning and attribute selection. Experimental results show that reducing the amount of data for instance-based learning reduces data storage requirements, lowers computational costs, minimizes noise, and can facilitates a more rapid search.

• Land and Housing Review
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• v.1 no.1
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• pp.1-7
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• 2010

Case-based reasoning (CBR) method can make estimators understand the estimation process more clearly. Thus, CBR is widely used as a methodology for cost estimation. In CBR, the quality of case retrieval affects the relevance of retrieved cases and hence the overall quality of the reminding capability of CBR system. Thus, it is essential to retrieve relevant past cases for establishing a robust CBR system. Case retrieval needs the following tasks to obtain appropriate case(s); indexing, search, and matching (Aamodt and Plaza 1994). However, the previous CBR researches mostly deal with matching process that has limits such as accuracy and efficiency of case retrieval. In order to address this issue, this research presents a CBR cost model for building projects that has two-step retrieval process: decision tree and nearest neighbor methods. Specifically, the proposed cost model has indexing, search and matching modules. Features in the model are divided into shape-based and scale-based attributes. Based on these, decision tree is established for facilitating the search task and nearest neighbor method was utilized for matching task. In regard to applying nearest neighbor method, attribute weights are assigned using GA optimization and similarity is calculated using the principle of distance measuring. Thereafter, the proposed CBR cost model is developed using 174 cases and validated using 12 test cases.

• Korean Journal of Human Ecology
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• v.10 no.1
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• pp.41-55
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• 2001

The purpose of this study was to compare the characteristics for pattern by making a sort of various store choice behaviors and analysing impact both direct and indirect, which is based on the presentation of the influence of clothing store choice behavior into the causal relationship per store type against clothing shopping orientation, information search activity and store image attribution. The results was that consumers who like to the top brand's commodities, had commonly high tendency to and fro its trademark and store allegiance. Furthermore, they have usually bought something following on their inclination what they had purchased as well as the store decoration character and the marketing promotion attribute. The other consumers who prefer to the discount store's merchandises, had also high propensity and the biggest influence on buying something which were those factors; their instance shopping habit, utility-economy trait, follow the fashion character and strong circumspection tendency besides using the mass media Info., personal data and commodities' attribute.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.212-222
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• 2022

There has been a rapid increase in the use of cloud email services. As a result, email encryption has become more commonplace as concerns about cloud privacy and security grow. Nevertheless, this increase in usage is creating the challenge of how to effectively be searching and filtering the encrypted emails. They are popular technologies of solving the issue of the encrypted emails searching through searchable public key encryption. However, the problem of encrypted email filtering remains to be solved. As a new approach to finding and filtering encrypted emails in the cloud, we propose a ciphertext-based encrypted policy attribute-based encryption scheme and keyword search procedure based on hidden policy ciphertext. This feature allows the user of searching using some encrypted emails keywords in the cloud as well as allowing the emails filter-based server toward filter the content of the encrypted emails, similar to the traditional email keyword filtering service. By utilizing composite order bilinear groups, a hidden policy system has been successfully demonstrated to be secure by our dual system encryption process. Proposed system can be used with other scenarios such as searching and filtering files as an applicable method.

• Journal of Internet Computing and Services
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• v.4 no.6
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• pp.33-42
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• 2003

A XML Instance repository model based on the Edge-Labeled Graph is suggested for storing the XML instance in Relational Databases, This repository model represents the XML instance as a data graph based on the Edge-Labeled Graph, extracts the defined value based on the structure of data path, element, attribute, and table index table presented as database schema, and stores these values using the Mapper module, In order to support querry, XML repository model offers the module translating XQL which is a query language under XPATH to SQL, and has DBtoXML generator module restoring the stored XML instance. As a result, it is possible to represent the storage relationship between the XML instances and the proposed repository model in terms of Graph-based Path, and it shows the possibility of easy search of specific element and attribute information.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.5
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• pp.993-1001
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• 2003

A RDB Storage Model based on the Edge-Labeled Graph is suggested for store the XML instance in Relational Databases(RDB). The XML instance being stored is represented by Data Graph based on the Edge-Labeled Graph. Data Path Table, Element, Attribute, and Table Index Table values are extracted. Then Database Schema is defined, and the extracted values are stored using the Mapper. In order to support querry, Repository Model offers the translator translating XQL which is used as query language under XPATH, into SQL. In addition, it creates DBtoXML generator restoring the stored XML instance. As a result, storage relationship between the XML instance and proposed model structure can be expressed in terms of Graph-based Path, and it shows the possibility of easy search of random Element and Attribute information.

• Journal of Digital Convergence
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• v.13 no.9
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• pp.201-208
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• 2015

With services such as SNS and facebook, Big Data popularize the use of small size such as micro blogs are increasing. However, the problem of accuracy and computational cost of the search result of big data of a small size is unresolved. In this paper, we propose a subnet selection techniques based probability to improve the browsing speed of the small size of the text information from big data environments, such as micro-blogs. The proposed method is to configure the subnets to give to the attribute information of the data increased the probability data search speed. In addition, the proposed method improves the accessibility of the data by processing a pair of the connection information between the probability of the data constituting the subnet to easily access the distributed data. Experimental results showed the proposed method is 6.8% higher detection rates than CELF algorithm, the average processing time was reduced by 8.2%.

• Journal of the Korean Institute of Landscape Architecture
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• v.21 no.3
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• pp.89-98
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• 1993

It is necessary for the park tree manager to have the current information about the status of trees, which can help him with right decisions. However, there are many problems in the existing management method such as huge amount of data, tedious work, and the difficult update work due to the lack of necessary data or the inappropriate data record and management method. The sole use of database management system(DBMS) cannot slove these problems because it cannot handle graphic data based on the locational information. So, it is imperative for the park manager to have locational data as well as attribute data of the park tree concerned. Therefore, the purpose of this study is to develop the personal computer-based, user friendly park tree management information system, which deals with attribute data(DBMS) and graphic data(using the CAD) together within the integrated environment. The park tree management information system developed in this study provides a complete operating environment for data input, update, query, delete, and retrieve. The major advantages of this system are as follows: 1) To search the location and distribution of trees. 2) To record, store, and manage data easily. 3) When the manager is changed, delivery of the park tree work is convenient. 4) The system can help the manager with the correct information for the efficient park tree management.