• Journal of KIISE:Computing Practices and Letters
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• v.15 no.3
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• pp.189-199
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• 2009

The amount of information on the Web is explosively growing as the Internet gains in popularity. However, only a small portion of the information on the Web is truly relevant or useful to the user. Thus, offering suitable information according to user demand is an important subject in information retrieval. In e-commerce, the recommender system is essential to revitalize commercial transactions, raise user satisfaction and loyalty towards the information provider. The existing recommender systems are mostly based on user data collected at servers, so user data are dispersed over several servers. Therefore, web servers that lack sufficient user behavior data cannot easily infer user preferences. Also, if the user visits the server infrequently, it may be hard to reflect the dynamically changing user's interest. This paper proposes a novel personalization system analyzing the user preference based on web documents that are accessed by the user on a user device. The system also identifies non-content blocks appearing repeatedly in the dynamically generated web documents, and adds weight to the keywords extracted from the hyperlink sentence selected by the user. Therefore, the system establishes at an early stage recommendation strategies for the web server that has little user data. Also, user profiles are generated rapidly and more accurately by identifying the information blocks. In order to evaluate the proposed system, this study collected web data and purchase history from users who have current purchase activity. Then, we computed the similarity between purchase data and the user profile. We confirm the accuracy of the generated user profile since the web page containing the purchased item has higher correlation than other item pages.

• Journal of the Korean Institute of Landscape Architecture
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• v.44 no.1
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• pp.40-50
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• 2016

A BIM, which is being applied actively to the construction and civil construction industries, is a technology that can maximize efficiency of various sectors from initial planning and design, construction, and maintenance, to demolition; however, it is in the introductory phase in the field of domestic landscaping. In order to introduce and promote BIM in the field of landscape design, this study developed a prototype of a library and template and analyzed the performance of trial application. For the development of a prototype, annotations and types were analyzed from floor plans of existing small parks, and components of landscape template were deduced. Based on this, play facilities, pergola, and benches were madeintofamily and templates, making automatic design possible. In addition, annotations and tags that are often used in landscape design were made, and a 3D view was materialized through visibility/graphic reassignment. As for tables and quantities, boundary stone table, mounding table, summary sheet of quantities, table of contents, and summary sheet of packaging quantities were grouped and connected with floor plans; regarding landscaping trees, classification criteria and name of trees that are suitable for domestic situations were applied. A landscape template was created to enable the library file format(rfa) that can be mounted on a building with BIM programs. As for problems that arose after the trial application of the prepared template, some CAD files could not be imported; also, while writing tables, the basis of calculation could not be made automatically. Regarding this, it is thought that functions of a BIM program and template need improvement.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.1
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• pp.105-114
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• 2016

With approximately 20 million transportation card data entries of the metropolitan districts being generated per day, application of the data to management and policy interventions is becoming an issue of interest. The research herein attempts a model of the possibility of dynamic demand change predictions and its purpose is thereby to construct a Dynamic Passengers Trip Assignment Model. The model and algorithm created are targeted at city rail lines operated by seven different transport facilities with the exclusion of travel by bus, as passenger movements by this mode can be minutely disaggregated through card tagging. The model created has been constructed in continuous time as is fitting to the big data characteristic of transport card data, while passenger path choice behavior is effectively represented using a perception parameter as a function of increasing number of transfers. Running the model on 800 pairs of metropolitan city rail data has proven its capability in determining dynamic demand at any moment in time, in line with the typical advantages expected of a continuous time-based model. Comparison against data measured by the eye of existing rail operating facilities to assess changes in congestion intensity shows that the model closely approximates the values and trends of the existing data with high levels of confidence. Future research efforts should be directed toward continued examination into construction of an integrated bus-city rail system model.