• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.293-304
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• 2011

The world of ubiquitous computing is one in which we will be surrounded by an ever-richer set of networked devices and services. Especially, mobile phone now becomes one of the key issues in ubiquitous computing environments. Mobile phones have been infecting our normal lives more thoroughly, and are the fastest technology in human history that has been adapted to people. In Korea, the number of mobile phones registered to the telecom company, is more than the population of the country. Last year, the numbers of mobile phone sold are many times more than the number of personal computer sold. The new advanced technology of mobile phone is now becoming the most concern on every field of technologies. The mix of wireless communication technology (wifi) and mobile phone (smart phone) has made a new world of ubiquitous computing and people can always access to the network anywhere, in high speed, and easily. In such a world, people cannot expect to have available to us specific applications that allow them to accomplish every conceivable combination of information that they might wish. They are willing to have information they want at easy way, and fast way, compared to the world we had before, where we had to have a desktop, cable connection, limited application, and limited speed to achieve what they want. Instead, now people can believe that many of their interactions will be through highly generic tools that allow end-user discovery, configuration, interconnection, and control of the devices around them. Serendipity is an application of the architecture that will help people to solve a concern of achieving their information. The word 'serendipity', introduced to scientific fields in eighteenth century, is the meaning of making new discoveries by accidents and sagacity. By combining to the field of ubiquitous computing and smart phone, it will change the way of achieving the information. Serendipity may enable professional practitioners to function more effectively in the unpredictable, dynamic environment that informs the reality of information seeking. This paper designs the Serendipity Service based on NFC (Near Field Communication) technology. When users of NFC smart phone get information and services by touching the NFC tags, serendipity service will be core services which will give an unexpected but valuable finding. This paper proposes the architecture, scenario and the interface of serendipity service using tag touch data, serendipity cases, serendipity rule base and user profile.

• Information Systems Review
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• v.17 no.2
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• pp.133-156
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• 2015

A recent interesting user experience in social curation websites is that they often encounter unanticipated, valuable information through accidental, incidental, or serendipitous discoveries. Prior research suggests that serendipity can help solve a problem, generate a creative idea, and invent a new product because it allows for an intellectual leap to arrive at a novel insight that is suddenly instrumental to a task. Despite the significant roles, the notion of serendipity is relatively unexplored especially in the context where people actually experience it, such as social curation websites. In this study, we theoretically identified the key technological features of social curation websites, which support three major curation activities respectively: browsing, collection, and interaction. We then examined their impacts on the occurrence of serendipitous discoveries in the process of information seeking. Our results using data collected from real users reveal that the technological features all affected user experience of serendipity and the interaction feature has stronger impacts than the other two. Moreover, it was also found that user experience of serendipity significantly affected website usage behavior such as intention to return and intention to contribute to the website.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.2
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• pp.128-136
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• 2015

With the recent interests with culture technologies, many studies for recommendation systems have been done. In this vein, various music recommendation systems have been developed. However, they have often focused on the technical aspects such as feature extraction and similarity comparison, and have not sufficiently addressed them in user-centered perspectives. For users' high satisfaction with recommended music items, it is necessary to study how the items are connected to the users' actual desires. For this, our study proposes a novel music recommendation method based on serendipity, which means the freshness users feel for their familiar items. The serendipity is measured through the comparison of users' past and recent listening tendencies. We utilize neural networks to apply these tendencies to the recommendation process and to extract the features of music items as MFCCs (Mel-frequency cepstral coefficients). In that the recommendation method is developed based on the characteristics of user behaviors, it is expected that user satisfaction for the recommended items can be actually increased.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.533-543
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• 2021

This study aims to determine and analyze the effect of social shopping, adventure shopping, value shopping, relaxation shopping, and idea shopping in influencing impulsive online buying behavior moderated by scarcity and serendipity information. The research method used is the quantitative research paradigm using surveys as a medium to obtain primary data. The paper examines the theoretical research model and tested fifteen hypotheses. The questionnaire was developed based on indicators from previous research. A non-probability sampling framework is used in this study. The data collection method uses electronic and online questionnaires to collect primary data with a total sample of 330 taken with the criteria of having made transactions in e-commerce Shopee in the last three months. Data analysis tools using Structural Equation Modelling (SEM) approach. The results showed that 8 out of 15 hypotheses were accepted and supported. The results show that there is a relationship between the value of hedonic shopping, scarcity, and serendipity information on impulsive online buying behavior. Therefore, analyzing the needs of customers, optimizing customer satisfaction, service excellence, website quality, and the ease of use of e-shopping itself especially in the e-commerce industry should be taken seriously nowadays.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.89-103
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• 2019

Recently, various approaches to recommendation systems have been studied in terms of the quality of recommendation system. A recommender system basically aims to provide personalized recommendations to users for specific items. Most of these systems always recommend the most relevant items of users or items. Traditionally, the evaluation of recommender system quality has focused on the various predictive accuracy metrics of these. However, recommender system must be not only accurate but also useful to users. User satisfaction with recommender systems as an evaluation criterion of recommender system is related not only to how accurately the system recommends but also to how much it supports the user's decision making. In particular, highly serendipitous recommendation would help a user to find a surprising and interesting item. Serendipity in this study is defined as a measure of the extent to which the recommended items are both attractive and surprising to the users. Therefore, this paper proposes an application of serendipity measure to recommender systems to evaluate the performance of recommender systems in terms of recommendation system quality. In this study we define relevant or attractive unexpectedness as serendipity measure for assessing recommendation systems. That is, serendipity measure is evaluated as the measure indicating how the recommender system can find unexpected and useful items for users. Our experimental results show that highly serendipitous recommendation such as item-based collaborative filtering method has better performance than the other recommendations, i.e. user-based collaborative filtering method in terms of recommendation system quality.

• Journal of the Korean Society for Library and Information Science
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• v.54 no.2
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• pp.399-417
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• 2020

In this study, we tried to analyze the relative importance of features for various functions provided by Discovery. We identified a total of 36 assessment items in five categories including contents, search function, serendipity, interactivity, and ease of use based on literature review. In order to objectively evaluate the relative importance of each evaluation element, an AHP technique was adopted. As a result, 'Easy of use' received the highest weighted value among the five categories, followed by 'contents', 'search function', 'interactivity', and 'serendipity'. In addition, among all the 36 assessment items, 'Quality of data for central index' had higher weighted value. These findings can be used as basic data to adopt a discovery tool for libraries.

• Journal of the Korean Society for Library and Information Science
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• v.50 no.1
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• pp.493-511
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• 2016

Discovery is an emerging concept to enhance the search capabilities of library resources with the Next Generation Library Catalog. This paper defined the Discovery feature based on the information search behavior, and then derived the elements that make up its function. After that, the 11 regional representatives libraries' OPACs and 3 Internet bookstores are evaluated and compared against Search & Discovery capabilities. As a result, the Internet bookstores were superior to the libraries' OPACs for all the elements that make up the Discovery functions. This study verified that the public libraries OPACs are still concentrating on known item search, and it is hard for the users to meet a serendipity which is gained through the Discovery functions.

• Journal of Ocean Engineering and Technology
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• v.13 no.1 s.31
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• pp.11-17
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• 1999

A three dimensional finite element generation code has been developed attaching simple blocks. Block can be either a quadrature or a cube depending on the dimension of a subject considered. Finite element serendipity basis functions are employed to map elements between the computational domain and the physical domain. Elements can be generated with wser defined progressive ratio for each block. For blocks to be connected properly, a block should have a consistent numbering scheme for vertices, side nodes, edges and surfaces. In addition the edge information such as the number of elements and the progressive ratio for each direction should also be checked for interfaces to have unique node numbers. Having done so, user can add blocks with little worry about the orientation of blocks, Since the present the present code has been written by a Visual Basic language, it can be developed easily for a user interactive manner under a Windows environment.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.20 no.4
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• pp.101-113
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• 2009

This paper reports the results of the analysis on the access points of two bibliographic databases specialized in children's materials: "A" public library's online catalog and "N" children's novel database. The analysis particularly focused on the access points that lead users to discover their own needs and on the ways users search and navigate. The findings showed that the selected bibliographic systems supported many access points that were taken from the materials as well as from other relevant information sources and that browsing and navigating with hyperlinks supported the users' 'recognition' of information through 'interactivity' between the users and the systems, 'information encountering,' and 'serendipity.' The findings of this paper have implications for librarians and systems designers who want to develop user-friendly bibliographic systems that give access to children's materials.

• Asia pacific journal of information systems
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• v.29 no.4
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• pp.856-874
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• 2019

The performance of recommender systems (RS) has been measured mainly in terms of accuracy. However, there are other aspects of performance that are difficult to understand in terms of accuracy, such as coverage, serendipity, and satisfaction with recommended results. Moreover, particularly with RSs that suggest multiple items at a time, such as YouTube, user satisfaction with recommended results may vary not only depending on their accuracy, but also on their configuration, content, and design displayed to the user. This is true when classifying an RS as a single RS with one recommended result and as a multiple RS with diverse results. No empirical analysis has been conducted on the influence of the content and distribution of recommendation items on user satisfaction. In this study, we propose a research model representing the content and distribution of recommended items and how they affect user satisfaction with the RS. We focus on RSs that recommend multiple items. We performed an empirical analysis involving 149 YouTube users. The results suggest that user satisfaction with recommended results is significantly affected according to the HHI (Herfindahl-Hirschman Index). In addition, satisfaction significantly increased when the recommended item on the top of the list was the same category in terms of content that users were currently watching. Particularly when the purpose of using RS is hedonic, not utilitarian, the results showed greater satisfaction when the number of views of the recommended items was evenly distributed. However, other characteristics of selected content, such as view count and playback time, had relatively less impact on satisfaction with recommended items. To the best of our knowledge, this study is the first to show that the category concentration of items impacts user satisfaction on websites recommending diverse items in different categories using a content-based filtering system, such as YouTube. In addition, our use of the HHI index, which has been extensively used in economics research, to show the distributional characteristics of recommended items, is also unique. The HHI for categories of recommended items was useful in explaining user satisfaction.