• Journal of Internet Computing and Services
• /
• v.6 no.6
• /
• pp.163-178
• /
• 2005

The ultimate objective of Personal Information Management (PIM) is to collect, handle and manage wanted information in a systematic way that enables individuals to search the information more easily and effectively, However, existing personal information management systems are usually based on a traditional hierarchical directory model for storing information, limiting effective organization and retrieval of information as well as providing less support in search by associative interrelationship between objects (documents) and their attributes, To improve these problems, in this paper we propose a personal information management model based on the concept lattice of Formal Concept Analysis (FCA) to easily build and maintain individuals' own information on the Web, The proposed system can overcome the limitations of the traditional hierarchy approach as well as supporting search of other useful information by the inter-relationships between objects and their attributes in the concept lattice of FCA beyond a narrow search.

• Journal of Korean Institute of Industrial Engineers
• /
• v.39 no.2
• /
• pp.119-128
• /
• 2013

Most internet users utilize internet portal search engines, such as Naver, Daum and Google nowadays. But since the results of internet portal search engines are based on universal criteria (e.g. search frequency by region or country), they do not consider personal interests. Namely, current search engines do not provide exact search results for homonym or polysemy because they try to serve universal users. In order to solve this problem, this research determines keyword importance and weight value for each individual search characteristics by collecting and analyzing customized keyword at external database. The customized keyword weight values are integrated with search engine results (e.g. PageRank), and the search ranks are rearranged. Using 50 web pages of Goolge search results for experiment and 6 web pages for customized keyword collection, the new customized search results are proved to be 90% match. Our personalization approach is not the way that users enter preference directly, but the way that system automatically collects and analyzes personal information and then reflects them for customized search results.

• Journal of the Korean Institute of Navigation
• /
• v.24 no.1
• /
• pp.73-84
• /
• 2000

Shipping industry continues to face dramatic changes in its environment ranging from development in containerization, computerization and telecommunications to the emergence of global marketplace. Perhaps the most significant trend - representing both a threat and opportunity - is the increasingly competitive nature of shipping service market. In order for the shipping companies to cope with those improvements and challenges, they should analyze and clarify customer's DM(decision making) process for the purchase of container shipping service. The major research findings from the study were found as follows; 1) The degree of shipper's involvement in purchasing shipping services was found to be a discriminating variable affecting the information sources consisting of personal and non-personal information sources. 2) The positive relationship was found between the experiences on shipping services and non-personal information sources. 3) It was observed that as people had more experience searching for information, the more in depth their searches became. 4) There existed a positive relationship between knowledges on shipping services and information search. 5) According to the SEM analysis, the shipper's information search on shipping services was also found to have a great influence on the shipper's purchasing behavior. The shipper's search was resulted in positive customer satisfaction.

• Journal of Families and Better Life
• /
• v.10 no.1 s.19
• /
• pp.27-42
• /
• 1992

This study focused on consumer information search activity and consumer's post-purchase satisfaction. For these purpose, a survey was conducted suing questionaires on 430 homemakers that lived in seoul. Statistics used for data were Frequency Distribution. Percentile, Mean, One-way AAANOVA., Scheffe-test, T-test, Pearson's correlation. Multiple Regression Analysis and Multiple Classification Analysis. The major findings were ; 1) The level of each amount information search was lower than average. And the level of consumer's post-purchase satisfaction was a little higher than average. 2) On amount of "noncommercial-personal" information search, the influencing variables were desire to seek information, education, brand royalty in turn. These three variables explained 7% of dependent variable's variance. 3) On amount of "noncommercial-media" information search, the influencing variables were desire to seek information, amount of internal information, education, occupational status in turn. These variables explained 14% of dependent variable's variance. 4) On amount of "commercial-personal" information search, the influencing variable was desire to seek information, and this variable explained 3.1% of dependent variable'a variance. 5) On amount of "commercial-media" information search, the influencing variables were desire to seek information, education, amount of internal information in turn. These three variables explained 12.1% dependent variable's variance. 6) Resulting from multiple classification analysis, influencing variables on consumer's post-purchase satisfaction were amount of noncommercial-media information search and printed media search, and brand royalty. These three variables explained 9% of dependent variable's variance. Furthermore, througout all the subareas of consumer's satisfaction, the amount of noncommercial-media information search was the most influencing variable.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2009.10a
• /
• pp.257-258
• /
• 2009

This area information system is connected with Yahoo and Daum. consequently, When the user searches the specific area, the system will be able to provide information which is various and the newest. Also all provides information which is necessary to one window, the user gets the information which is necessary easily. In addition, Because being will be able to provide the search result which reflects the personal preference, the information search of oneself who is personal is possible, gets the informations which search before easily again.

• Proceedings of the KSRS Conference
• /
• 2008.10a
• /
• pp.107-110
• /
• 2008

In this study, we propose a system for setting a Destination on CNS(Car Navigation System) or PNS(Personal Navigation System). The present Navigation does set the destination by only static method like name search, address search and wire telegraph telephone number search. But, the kind of setting a static destination does not reflect the dynamic moving situation. So we suggest setting the destination of navigation using Identifier of moving terminal. And it includes privacy protection on personal position information

• Korean Journal of Oriental Medicine
• /
• v.16 no.2
• /
• pp.91-99
• /
• 2010

In this paper, we designed and implemented a semantic social network system in Korea Institute of Oriental Medicine (abbreviated as KIOM). Our social network system provides the capabilities such as tracking search, ontology reasoning, ontology graph view, and personal information input, update and management. Tracking search provides the search results by the research information of relevant researchers using ontology, in addition to those by keywords. Ontology reasoning provides the reasoning for experts, mentors, and personal contacts. Users can easily browse the personal connections among researchers by traversing the ontology by graph viewer. These allows KIOM researchers to search other researchers who could aid the researches and to easily share their research information.

• Journal of Information Science Theory and Practice
• /
• v.8 no.3
• /
• pp.6-14
• /
• 2020

On information markets, we can identify different relations between sellers and their customers, with some users paying with money, some paying with attention, and others paying with their personal data. For the description of these different market relations, this article introduces the notion of arity into the scientific discussion. On unary information markets, customers pay with their money; examples include commercial information suppliers. Binary information markets are characterized by one market side paying with attention (e.g., on the search engine Google) or with personal data (e.g., on most social media services) and the other market side (mainly advertisers) paying with money. Our example of a ternary market is a social media market with the additional market side of influencers. If customers buy on unary markets, they know what to pay (in terms of money). If they pay with attention or with their personal data, they do not know what they have to pay exactly in the end. On n-ary markets (n greater than 1), laws should regulate company's abuse of money and-which is new-abuse of data streams with the aid of competition (or anti-trust) laws, and by modified data protection laws, which are guided by fair use of end users' attention and data.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.31 no.9_10
• /
• pp.1396-1407
• /
• 2007

The purpose of this study was to identify the effect of clothing involvement, store and brand loyalty orientation on the information search behavior. The study subjects comprised 298 females living in Seoul and Kyung-gi area. The data were analyzed with factor analysis, regression, cluster analysis, ANOVA and correlation analysis. Clothing involvement and information search behavior consisted of various factors. Clothing involvement, store and brand loyalty influenced information search behavior. Fashion and clothing involvement was the most important factor which influenced all loyalty and information search behavior(i.e. brand and store loyalty, personal and nonpersonal information search behavior). According to store and brand loyalty factors, female consumers classified into three groups : low loyalty, brand loyalty and store loyalty group. Three groups showed different clothing involvement, information search, clothing purchasing behavior and demographic variables. Therefore, loyalty orientation is the important factor which can describe the consumer behavior more effectively.

• Journal of Digital Convergence
• /
• v.15 no.4
• /
• pp.191-198
• /
• 2017

It is needed to support intelligent customized health information service for user convenience in PHR based Personal Health Care Service Platform. In this paper, we specify an ontology-based health data model for Personal Health Care Service Platform. We also design a knowledge search algorithm that can be used to figure out similar health record by applying machine learning and data mining techniques. Axis-based mining algorithm, which we proposed, can be performed based on axis-attributes in order to improve relevance of knowledge exploration and to provide efficient search time by reducing the size of candidate item set. And K-Nearest Neighbor algorithm is used to perform to do grouping users byaccording to the similarity of the user profile. These algorithms improves the efficiency of customized information exploration according to the user 's disease and health condition. It can be useful to apply the proposed algorithm to a process of inference in the Personal Health Care Service Platform and makes it possible to recommend customized health information to the user. It is useful for people to manage smart health care in aging society.