• The Transactions of the Korea Information Processing Society
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• v.6 no.7
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• pp.1832-1840
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• 1999

Since the existed Korean Web IR systems generally use boolean system, it is difficult to retrieve the information to be wanted at one time. Also, because of the feature that web documents have the frequent abbreviation and many links, the keyword extraction using the inverted document frequency extracts the improper keywords for adding ambiguous meaning problem. Therefore, users must repeat the modification of the queries until they get the proper information. In this paper, we design and implement the relevance feedback agent system for resolving the above problems. The relevance feedback agent system extracts the proper information in response to user's preferred keywords and stores these keywords in preference DB table. When users retrieve this information later, the relevance feedback agent system will search it adding relevant keywords to user's queries. As a result of this method, the system can reduce the number of modification of user's queries and improve the efficiency of the IR system.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.6
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• pp.1-12
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• 2022

As the music streaming service and the Hi-Fi market grow, various audio devices are being released. As a result, consumers have a wider range of product choices, but it has become more difficult to find products that match their musical tastes. In this study, we proposed a system that extracts the vocal component from the user's preferred sound source and recommends the most suitable audio device to the user based on this information. To achieve this, first, the original sound source was separated using Python's Spleeter Library, the vocal sound source was extracted, and the result of collecting frequency band data of manufacturers' audio devices was shown in a grid graph. The Matching Gap Index (MGI) was proposed as an indicator for comparing the frequency band of the extracted vocal sound source and the measurement data of the frequency band of the audio devices. Based on the calculated MGI value, the audio device with the highest similarity with the user's preference is recommended. The recommendation results were verified using equalizer data for each genre provided by sound professional companies.

• Journal of the Korea Society of Computer and Information
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• v.26 no.10
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• pp.185-198
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• 2021

With the development of Internet technology, because traditional recommendation algorithms cannot learn the in-depth characteristics of users or items, this paper proposed a recommendation algorithm based on the AMITI(attention mechanism and improved TF-IDF) to solve this problem. By introducing the two-layer attention mechanism into the CNN, the feature extraction ability of the CNN is improved, and different preference weights are assigned to item features, recommendations that are more in line with user preferences are achieved. When recommending items to target users, the scoring data and item type data are combined with TF-IDF to complete the grouping of the recommendation results. In this paper, the experimental results on the MovieLens-1M data set show that the AMITI algorithm improves the accuracy of recommendation to a certain extent and enhances the orderliness and selectivity of presentation methods.

• Journal of IKEEE
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• v.14 no.4
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• pp.305-311
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• 2010

Most recent web search engines perform effective keyword-based multimedia contents retrieval by investigating keywords associated with multimedia contents on the Web and comparing them with query keywords. On the other hand, most music and compilation albums provide professional artwork as cover art that will be displayed when the music is played. If the cover art is not available, then the music player just displays some dummy or random images, but this has been a source of dissatisfaction. In this paper, in order to automatically create cover art that is matched with music contents, we propose a music album cover art creation scheme based on music contents analysis and result synthesis. We first (i) analyze music contents and their lyrics and extract representative keywords, (ii) expand the keywords using WordNet and generate various queries, (iii) retrieve related images from the Web using those queries, and finally (iv) synthesize them according to the user preference for album cover art. To show the effectiveness of our scheme, we developed a prototype system and reported some results.

• Journal of Digital Convergence
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• v.12 no.4
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• pp.319-326
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• 2014

According to the increasing mobile security users who have experienced authentication failure by forgetting passwords, user names, or a response to a knowledge-based question have preference for biological information such as hand geometry, fingerprints, voice in personal identification and authentication. Therefore biometric verification of personal identification and authentication for mobile security provides assurance to both the customer and the seller in the internet. Our study focuses on human hand biometric information recognition system for personal identification and personal Authentication, including its shape, palm features and the lengths and widths of the fingers taken from mobile phone photographs such as iPhone4 and galaxy s2. Our hand biometric information recognition system consists of six steps processing: image acquisition, preprocessing, removing noises, extracting standard hand feature extraction, individual feature pattern extraction, hand biometric information recognition for personal identification and authentication from input images. The validity of the proposed system from mobile phone image is demonstrated through 93.5% of the sucessful recognition rate for 250 experimental data of hand shape images and palm information images from 50 subjects.

• Journal of Korean Institute of Industrial Engineers
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• v.29 no.1
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• pp.49-64
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• 2003

Although assembly sequence planning is an essential task in assembly process planning, it is known as one of the most difficult and time consuming jobs because its complexity is increased geometrically when the number of parts in an assembly is increased. The purpose of this study is to develop a more efficient algorithm for generating assembly sequences automatically. By considering subassemblies, a new heuristic method generates a preferred parallel assembly sequence that can be used in robotic assembly systems. A parallel assembly sequence concept provides a new representation scheme for an assembly in which the assembly sequence precedence information is not required. After an user inputs both the directional mating relation information and the mating condition information, an assembly product is divided into subgroups if the product has cut-vertices. Then, a virtual disassembly process is executed to generate alternate parallel assembly sequences with intermediate assembly stability. Through searching parts relations in the virtual disassembly process, stable subassemblies are extracted from translation-free parts along disassembling directions and this extraction continues until no more subassemblies are existed. Also, the arithmetic mean parallelism formula as a preference criterion is adapted to select the best parallel assembly sequence among others. Finally a preferred parallel assembly sequence is converted to an assembly BOM structure. The results from this study can be utilized for developing CAAPP(Computer-Aided Assembly Process Planning) systems as an efficient assembly sequence planning algorithm.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.2
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• pp.301-314
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• 2016

Juels and Sudan's fuzzy vault scheme has been applied to various researches due to its error-tolerance property. However, the fuzzy vault scheme does not consider the difference between people's preferences, even though the authors instantiated movie lover' case in their paper. On the other hand, to make secure and high performance face authentication system, Nyang and Lee introduced a face authentication system, so-called fuzzy face vault, that has a specially designed association structure between face features and ordinary fuzzy vault in order to let each face feature have different weight. However, because of optimizing intra/inter class difference of underlying feature extraction methods, we can easily expect that the face authentication system does not successfully decrease the face authentication failure. In this paper, for ensuring the flexible use of the fuzzy vault scheme, we introduce the bucket structure, which differently implements the weighting idea of Nyang and Lee's face authentication system, and three distribution functions, which formalize the relation between user's weight of preferences and system implementation. In addition, we suggest a matchmaker scheme based on them and confirm its computational performance through the movie database.

• Science of Emotion and Sensibility
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• v.25 no.1
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• pp.41-54
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• 2022

The purpose of this study was to propose a "user experience (UX)-centered product development process" so that the product design development process using the service design process can be systematized and used in practice. In a situation in which usability research on office phones is lacking compared to general home phones, this study expands to a product-based service design point of view rather than simple product development, intending to research ways to provide user experience value through office phone design in smart office. This study focused on extracting UX-centered user needs using the service design process and developing product design that realizes user experience value. In particular, the service design process was applied to systematically extract user needs and experience value elements in the product development process and to discover ideas that were converged with product-based services. For this purpose, the "Double Diamond Design Process Model," which is widely used in the service design field, was adopted. In addition, a product design development process was established so that usability improvement plans, user experience value elements, and product-service connected ideas could be extracted through a work-flow in which real users and people from various fields participate. Based on the double diamond design process, in the "Discover" information collection stage, design trends were identified mainly in the office phone markets. In the "Define" analysis and extraction stage, user needs were analyzed through user observation, interview, and usability survey, and design requirements and user experience issues were extracted. Persona was set through user type analysis, and user scenarios were presented. In the "Develop" development stage, ideation workshops and concept renderings were conducted to embody the design, and people from various fields within the company participated to set the design direction reflecting design preference and usability improvement plans. In the "Deliver" improvement/prototype development/evaluation stage, a working mock-up of a design prototype was produced and design and usability evaluation were conducted through consultation with external design experts. It is meaningful that it established a "UX-centered product development process" model that converged with the existing product design development process and service design process. Ultimately, service design-based product design development process was presented so that I Corp.'s products could realize user experience value through service convergence.

• The KIPS Transactions:PartB
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• v.17B no.4
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• pp.263-274
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• 2010

To provide context-aware music recommendation service, first of all, we need to catch music mood that a user prefers depending on his situation or context. Among various music characteristics, music mood has a close relation with people‘s emotion. Based on this relationship, some researchers have studied on music mood detection, where they manually select a representative segment of music and classify its mood. Although such approaches show good performance on music mood classification, it's difficult to apply them to new music due to the manual intervention. Moreover, it is more difficult to detect music mood because the mood usually varies with time. To cope with these problems, this paper presents an automatic method to classify the music mood. First, a whole music is segmented into several groups that have similar characteristics by structural information. Then, the mood of each segments is detected, where each individual's preference on mood is modelled by regression based on Thayer's two-dimensional mood model. Experimental results show that the proposed method achieves 80% or higher accuracy.