The problem of choosing the right product that will best fit a consumer's taste and preferences extends to the field of electronic commerce. However, e-commerce has been able to create a technological proxy for the social filtering process, known as online recommender systems (RSs). RSs aid users in filtering products and decisions on matters relating to personal taste. RSs have the potential to support and improve the quality of the decisions consumers make when searching for and selecting products and services online. However, most previous research on RSs has focused on the accuracy of the algorithms, with little emphasis on user interface and perspectives. This study identified transparency and feedback as possible ways to effectively evaluate RSs from the user's perspective. Thus, this research focused on examining and identifying the roles of transparency and feedback in recommender systems and how they affect users' attitudes toward the system. Results of the study showed that both transparency and feedback positively and significantly affected perceived trust, perceived value of the process, and perceived enjoyment. Furthermore, we found that perceived trust, perceived value of the process, and perceived enjoyment positively and directly affected users' intentions to use/reuse a recommender system.
In current digital broadcasting systems, GEM(Globally Executable MHP)-based middlewares such as MHP(Multimedia Home Platform), OCAP(OpenCable Application Platform), ACAP(Advanced Common Application Platform) are the norm. Despite much of the common characteristics shared, such as MPEG-2 and DSM-CC(Digital Storage Media-Command and Control) protocols, the information and data structures they need are slightly different, which results in incompatibility issues. In this paper, in line with an effort to develop an integrated DTV middleware, we propose a general-purpose, reconfigurable DSM-CC architecture for supporting various standard GEM-based middlewares without code modifications. First, we identify DSM-CC components that are common and thus can be shared by all GEM-based middlewares. Next, the system is provided with middleware-specific information and data structures in the form of XML. Since the XML information can be parsed dynamically at run time, it can be interchanged either statically or dynamically for a specific target middleware. As for the performance issues, the response time and usage frequency of DSM-CC module highly contribute to the performance of STB(Set-Top-Box). In this paper, we also propose an efficient application cache management strategy and evaluate its performance. The performance result has shown that the cache strategy reflecting user preferences greatly helps to reduce response time for executing application.
The Journal of Korean Institute of Communications and Information Sciences
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v.38B
no.5
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pp.385-393
/
2013
In the past decade, a paradigm shift from machine-centered to human-centered and from technology-driven to user-driven has been witnessed. Consequently, Social search is getting more social and Social Network Service (SNS) is a popular Web service to connect and/or find friends, and the tendency of users interests often affects his/her who have similar interests. If we can track users' preferences in certain boundaries in terms of Web search and/or knowledge sharing, we can find more relevant information for users. In this paper, we propose a novel Topic Sensitive_Social Relationship Rank (TS_SRR) algorithm. We propose enhanced Web searching idea by finding similar and credible users in a Social Network incorporating social information in Web search. The Social Relation Rank between users are Social Relation Value, that is, for a different topics, a different subset of the above attributes is used to measure the Social Relation Rank. We observe that a user has a certain common interest with his/her credible friends in a Social Network, then focus on the problem of identifying users who have similar interests and high credibility, and sharing their search experiences. Thus, the proposed algorithm can make social search improve one step forward.
The purpose of this study was to evaluate the usability of the tablet PC-based Korean high-tech AAC(Augmentative Alternative Communication System) software. In order to develop an AAC software which is appropriate to Korean cultural/linguistic contexts and communication needs of the users, we examined the necessity and ease of use for the communication functions that are required in native Korean communication, such as polite expressions, tense expressions, negative expressions, subject-verb auto-matching, and automatic sentence generation functions, using a scenario-based user testing. We also investigated the users' needs, preferences, and satisfaction for the tablet PC-based Korean high tech AAC using a semi-structured and open questionnaires. The participants of this study were 9 special education teachers, 6 speech therapists, and 6 parents whose children had communication disabilities. The results of the usability testing of the tablet PC-based Korean high-tech AAC software presented positive responses in general, by indicating overall scores of above 4 out of 5 except in tense and negative expressions. The necessity and ease of use in the tense and negative expressions were evaluated relatively low, and it might be related to the inconsistent interface with the polite expressions. In terms of the user interface(UI), there were users' needs for clear visual feedback in the symbol selection and display, consistent interface for all functions, more natural subject-verb auto-matching, and spacing in the text within symbols. The results of the usability testing and users' feedback might serve as a guideline to compensate and improve the function and UI of the existing AAC software.
KIPS Transactions on Software and Data Engineering
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v.11
no.5
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pp.189-196
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2022
Skyline query is a scheme for exploring objects that are suitable for user preferences based on multiple attributes of objects. Existing skyline queries return search results as batch processing, but the need for real-time search results has increased with the advent of interactive apps or mobile environments. Online algorithm for Skyline improves the return speed of objects to explore preferred objects in real time. However, the object navigation process requires unnecessary navigation time due to repeated comparative operations. This paper proposes a Pre-processing Online Algorithm for Skyline Query (POA) to eliminate unnecessary search time in Online Algorithm exploration techniques and provide the results of skyline queries in real time. Proposed techniques use the concept of range-limiting to existing Online Algorithm to perform pretreatment and then eliminate repetitive rediscovering regions first. POAs showed improvement in standard distributions, bias distributions, positive correlations, and negative correlations of discrete data sets compared to Online Algorithm. The POAs used in this paper improve navigation performance by minimizing comparison targets for Online Algorithm, which will be a new criterion for rapid service to users in the face of increasing use of mobile devices.
The development of information communication and artificial intelligence technology requires the intelligent command and control (C2) system for Korean military, and various studies are attempted to achieve it. In particular, as a volume ofinformation in the C2 workflow increases exponentially, this study pays attention to the collaborative filtering (CF) and recommendation systems (RS) that can provide the essential information for the users of the C2 system has been developed. The RS performing information filtering in the C2 system should provide an explanatory recommendation and consider the context of the tasks and users. In this paper, we propose a contextual pre-filtering CARS framework that recommends information in the C2 workflow. The proposed framework consists of four components: 1) contextual pre-filtering that filters data in advance based on the context and relationship of the users, 2) feature selection to overcome the data sparseness that is a weak point for the CF, 3) the proposed CF with the features distances between the users used to calculate user similarity, and 4) rule-based post filtering to reflect user preferences. In order to evaluate the superiority of this study, various distance methods of the existing CF method were compared to the proposed framework with two experimental datasets in real-world. As a result of comparative experiments, it was shown that the proposed framework was superior in terms of MAE, MSE, and MSLE.
In an era where digital technology reshapes brand-consumer interactions, this study examines the influence of Nike's Run Club and Adidas' Runtastic apps on loyalty and advocacy. Analyzing 3,715 English reviews from January 2020 to October 2023 through text mining, and conducting a focused sentiment analysis on 155 'recommend' mentions, we explore the nuances of 'hot loyalty'. The findings reveal Nike as a 'companion' with an emphasis on emotional engagement, versus Runtastic's 'tool' focus on reliability. This underscores the varied consumer perceptions across similar platforms, highlighting the necessity for brands to integrate user preferences and address technical flaws to foster loyalty. Demonstrating how customized technology adaptations impact loyalty, this research offers crucial insights for digital brand strategy, suggesting a proactive approach in app development and management for brand loyalty enhancement
Recommender system recommends the items expected to be purchased by a customer in the future according to his or her previous purchase behaviors. It has been served as a tool for realizing one-to-one personalization for an e-commerce service company. Traditional recommender systems, especially the recommender systems based on collaborative filtering (CF), which is the most popular recommendation algorithm in both academy and industry, are designed to generate the items list for recommendation by using 'overall rating' - a single criterion. However, it has critical limitations in understanding the customers' preferences in detail. Recently, to mitigate these limitations, some leading e-commerce companies have begun to get feedback from their customers in a form of 'multicritera ratings'. Multicriteria ratings enable the companies to understand their customers' preferences from the multidimensional viewpoints. Moreover, it is easy to handle and analyze the multidimensional ratings because they are quantitative. But, the recommendation using multicritera ratings also has limitation that it may omit detail information on a user's preference because it only considers three-to-five predetermined criteria in most cases. Under this background, this study proposes a novel hybrid recommendation system, which selectively uses the results from 'traditional CF' and 'CF using multicriteria ratings'. Our proposed system is based on the premise that some people have holistic preference scheme, whereas others have composite preference scheme. Thus, our system is designed to use traditional CF using overall rating for the users with holistic preference, and to use CF using multicriteria ratings for the users with composite preference. To validate the usefulness of the proposed system, we applied it to a real-world dataset regarding the recommendation for POI (point-of-interests). Providing personalized POI recommendation is getting more attentions as the popularity of the location-based services such as Yelp and Foursquare increases. The dataset was collected from university students via a Web-based online survey system. Using the survey system, we collected the overall ratings as well as the ratings for each criterion for 48 POIs that are located near K university in Seoul, South Korea. The criteria include 'food or taste', 'price' and 'service or mood'. As a result, we obtain 2,878 valid ratings from 112 users. Among 48 items, 38 items (80%) are used as training dataset, and the remaining 10 items (20%) are used as validation dataset. To examine the effectiveness of the proposed system (i.e. hybrid selective model), we compared its performance to the performances of two comparison models - the traditional CF and the CF with multicriteria ratings. The performances of recommender systems were evaluated by using two metrics - average MAE(mean absolute error) and precision-in-top-N. Precision-in-top-N represents the percentage of truly high overall ratings among those that the model predicted would be the N most relevant items for each user. The experimental system was developed using Microsoft Visual Basic for Applications (VBA). The experimental results showed that our proposed system (avg. MAE = 0.584) outperformed traditional CF (avg. MAE = 0.591) as well as multicriteria CF (avg. AVE = 0.608). We also found that multicriteria CF showed worse performance compared to traditional CF in our data set, which is contradictory to the results in the most previous studies. This result supports the premise of our study that people have two different types of preference schemes - holistic and composite. Besides MAE, the proposed system outperformed all the comparison models in precision-in-top-3, precision-in-top-5, and precision-in-top-7. The results from the paired samples t-test presented that our proposed system outperformed traditional CF with 10% statistical significance level, and multicriteria CF with 1% statistical significance level from the perspective of average MAE. The proposed system sheds light on how to understand and utilize user's preference schemes in recommender systems domain.
Journal of the Korean Institute of Landscape Architecture
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v.38
no.4
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pp.25-34
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2010
This study was conducted to develop evaluation indicators to improve athletic performance and operational management of golf courses and the results of the research are as follows. Through theoretical research and a preliminary professional survey, 15 on-going evaluations of golf course composition and operational management and 55 sub-evaluation indices were rejected while 10 on-going evaluations and 52 sub-evaluation indicators were reconfigured as final for environmental-friendliness, level of member services, level of human service of game personnel, difficulties of course, management level of the course, fairness of operational management, accessibility and location characteristic, traditions and ambiance of the golf club, quality of course, and course layout. When analyzing the important decision factors in golf course user preference evaluation indicators, the following contributed in the order of higher to lower contributions: the management level of the course, excellence of the course, level of human services for personnel, course layout and environmental-friendliness. When identifying the path coefficient of golf course evaluation indicators, the curvature of a hole and the length of the course had a causal effect on the 'course layout' section. Tournament facilities and various shot values had a causal relationship with 'excellence of the course', in the order of higher to lower, and convenience of waiting and fair allocation of reservations for 'fairness of operational management'. The history of the golf course and its environmental characteristics, history and culture of the region have relatively higher causal effects on 'traditions of the golf club' and geographical conditions on 'accessibility and location characteristics', pesticide and fertilizer usage and water pollution on 'environmental-friendliness', and member benefit and kindness of employees on 'level of member services'. The kindness and expertise of the game personnel had a relatively higher causal effect on the 'level of human services of game personnel', the location of tenning area, and location of OB and hazards on 'difficulties of course', and rough conditions and obstacles management on 'management level of the course'. There is a need to complete a systematic evaluation index system for golf course user preferences through future studies for a more detailed assessment, as well as a process to verify these evaluation indicators by application to domestic and international golf courses.
KSCE Journal of Civil and Environmental Engineering Research
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v.39
no.4
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pp.513-521
/
2019
The purpose of this research is to find out the preference of users on the characteristics of the subway sign blank. In detail, The purpose is to introduce the concept of designing various characteristics of the subway sign blank according to characteristics such as gender and age, etc. The methodology of this study is to investigate the preference of the characteristics of the characteristics of the subway sign blank space and analyze the preference of the whole group and the cluster group. A survey was conducted to investigate preferences. A cluster analysis was conducted to analyze the preferences. And a demographic and conjoint analysis was conducted for whole group and the cluster group. The attributes of the subway sign blank space for preference survey are as follow : top and bottom blank, side blank, border line blank, arrow thickness, 'station name' and 'line number' order. The results of the preference analysis are as follows. The importance of the attributes in the whole group is shown in the order of the border line blank, 'station name' and 'line number' blank, side blank, top and bottom blank, and arrow thickness. The cluster group is composed of 3 groups, 1 cluster is a woman who uses the subway almost every day, three to four times a week, and seems to prefer half the side blank. 2 crowd is the user who thinks that 60 or more subway signs are uncomfortable, and preferring the order of 'station name' + 'line number' order without border. The 3 clusters were men in their 20s and 30s, with a preference for 1/5 border line blank and thin arrow thickness. The conclusion is as follows. First, the characteristics of the subway sign blank must be designed consistently. However, it is necessary to consider various factors according to gender, age, and frequency of subway use for specific regions or routes. Secondly, It has been shown that, depending on the specific area or route, it is possible to design two or more types of design, not one type of standardized marking of the characteristics of the subway sign blank.
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