• Asia pacific journal of information systems
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• v.15 no.1
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• pp.63-79
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• 2005

Recommender systems are a personalized information filtering technology to help customers find the products they would like to purchase. Collaborative filtering is known to be the most successful recommendation technology, but its widespread use has exposed some problems such as sparsity and scalability in the e-business environment. In this paper, we propose a recommendation system, WebCF-PT based on Web usage mining and product taxonomy to enhance the recommendation quality and the system performance of traditional CF-based recommender systems. Web usage mining populates the rating database by tracking customers' shopping behaviors on the Web, so leading to better quality recommendations. The product taxonomy is used to improve the performance of searching for nearest neighbors through dimensionality reduction of the rating database. A prototype recommendation system, WebCF-PT is developed and Internet shopping mall, EBIB(e-Business & Intelligence Business) is constructed to test the WebCF-PT system.

• Journal of Intelligence and Information Systems
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• v.11 no.2
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• pp.1-15
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• 2005

The explosive growth of the Internet leads to various on-line shopping malls and active E-Commerce. however, as the internet has experienced continuous growth, users have to face a variety and a huge amount of items, and often waste a lot of time on purchasing items that are relevant to their interests. To overcome this problem the comparison shopping systems, which can help to compare items' information with those other shopping malls, have been issued as a solution. However, when users do not have much knowledge what they want to find, a keyword-based searching in the existing comparison shopping systems lead users to waste time for searching information. Thereby, the performance is fell down. To solve this problem in this research, we suggest the Comparison Shopping System using Image Retrieval based on Semantic Web. The proposed system can assist users who don't know items' information that they want to find and serve users for quickly comparing information among the items. In the proposed system we use semantic web technology. We insert the Semantic Annotation based on Ontology into items' image of each shopping mall. Consequently, we employ those images for searching the items instead of using a complex keyword. In order to evaluate performance of the proposed system we compare our experimental results with those of Keyword-based Comparison Shopping System and simple Semantic Web-based Comparison Shopping System. Our result shows that the proposed system has improved performance in comparison with the other systems.

• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.127-138
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• 2003

Although the research on electronic commerce is plentiful, there is little empirical research related to Web-Based Shopping Systems (WBSS). This is especially so in global electronic commerce circumstances. WBSS are the fastest growing segment of digital economies and are perceived as driving forces of electronic commerce in terms of global markets and digital business. Using WBSS, organizations have a new chance of their business evolving successfully as global marketers. This paper develops a unified model to assess the diffusion of WBSS. Factors that impact WBSS diffusion are identified and analyzed as the basis for empirical testing. A set of propositions is developed that allows operationalization of the model. The ultimate goal is to provide the new research insights for the academic circles and the practical guidelines for organizations wishing to undertake WBSS.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.3
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• pp.366-370
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• 2003

In this research, we suggest a hybrid intelligent Web recommendation systems based on Web data mining and case-based reasoning (CBR). One of the important research topics in the field of Internet business is blending artificial intelligence (AI) techniques with knowledge discovering in database (KDD) or data mining (DM). Data mining is used as an efficient mechanism in reasoning for association knowledge between goods and customers＇ preference. In the field of data mining, the features, called attributes, are often selected primary for mining the association knowledge between related products. Therefore, most of researches, in the arena of Web data mining, used association rules extraction mechanism. However, association rules extraction mechanism has a potential limitation in flexibility of reasoning. If there are some goods, which were not retrieved by association rules-based reasoning, we can＇t present more information to customer. To overcome this limitation case, we combined CBR with Web data mining. CBR is one of the AI techniques and used in problems for which it is difficult to solve with logical (association) rules. A Web-log data gathered in real-world Web shopping mall was given to illustrate the quality of the proposed hybrid recommendation mechanism. This Web shopping mall deals with remote-controlled plastic models such as remote-controlled car, yacht, airplane, and helicopter. The experimental results showed that our hybrid recommendation mechanism could reflect both association knowledge and implicit human knowledge extracted from cases in Web databases.

• International Commerce and Information Review
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• v.6 no.3
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• pp.81-99
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• 2004

Research relevant to the electronic commerce tends to either overestimate or underrate the role of Information and Communication Technology (lCT). There is both technological skepticism within the social science circles and technical optimism within the engineering and computing field. Each perspective seems to have a limitation in adequately explaining the phenomenon of electronic commerce diffusion. Therefore, this research attempts to explore major characteristics of Web-based shopping systems as enablers of new business, concerning both the technical and business aspects in contemporary electronic commerce settings. On this basis, this paper addresses a configuration model of WBSS on the harmonious perspective concerning both the technical and business issues. It is our hope that both technical perspective and business perspective for exploring WBSS's configuration model presented in this paper can be an initial step towards a more balanced debate of ICT role, for electronic commerce.

• Asia pacific journal of information systems
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• v.17 no.3
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• pp.1-24
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• 2007

With the development of information technology (IT), various information systems (IS) such as Web-based systems and mobile systems have appeared utilizing different technologies. However, recent studies on IS use and user satisfaction rarely account for technological differences among IS and environmental characteristics where IS are intended to be used. The purpose of this research is to investigate the determinants of the use of Web-based ticketing systems for cultural activities and to empirically validate their relationships. Environmental psychology suggests that human beings respond to external stimuli from environments with their emotions, and their emotional states influence human actions, e.g., IS use in this research. Applying environmental psychology to the use of Web-based systems in the culture and entertainment industry, we propose that web site characteristics first influence a user's internal state of mind (i.e., flow) and then the flow state influences the IS use. Studies related to the state of flow collectively affirm the key role played by the flow construct in shaping individual attitudes and behaviors toward IS. Users' flow states are captured by their shopping enjoyment, perceived behavioral control, and the level of concentration on the IS use. Referring to social presence theory, we have included such web site characteristics as content quality, context of web site, and community quality. In our research model, a second order construct is utilized to represent web site quality, because flow theory suggests that holistic experiences with web-based systems (rather than individual characteristics of the web site) are important in explaining the IS use. Further, we have included trust as another important factor influencing the IS use since business transactions on the web encompass higher uncertainty comparing to offline transactions. In order to test our hypotheses, we have conducted an online survey which results in 1,141 valid responses in the final sample. The data were collected from respondents who have experiences in Internet ticketing systems. Although it was a convenient sample, the sample represents a wide variety of user demographics. Validity and reliability of the research instrument were tested and research hypotheses were examined using PLS Graph 3.0. The results indicate that web site characteristics significantly influence the level of user concentration, user's enjoyment in shopping, and perceived behavioral control. Further, the use of Internet ticketing systems is influenced by users' flow states and trust in the web channel. User satisfaction is turned out to be affected by the use of Internet ticketing systems. Unlike extant research on the relationship between web site characteristics and its use, our study has found that, in the culture and entertainment industry, the impact of web site characteristics on IS use is mediated by a user's flow state. This finding has a practical implication that web site design should include as many features that enhance shopping enjoyment and concentration. Other practical implications of these findings and future research implications are also discussed.

• The Journal of Information Systems
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• v.20 no.3
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• pp.41-61
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• 2011

In order to buy products through the Internet, consumers dissipate much time and efforts in collecting and comparing product information from various online shopping malls. Consumers can save their efforts by using price comparison sites, but there are some shortcomings in comparison shopping. Firstly, comparison sites do not show the lowest price of some products that are selling in shopping malls. Secondly, the product information provided by comparison sites is sometimes wrong. Thirdly, there are too many results. In order to overcome the shortcomings, we suggested a comparison shopping system based on RSS by using ontology matching. We used the current RSS standard for syntactic interoperability instead of suggesting new standards. Moreover, we used ontology matching for semantic interoperability to compare product information with different ontologies. The suggested ontology matching consists of three steps. The first step is finding exact sense from WordNet for a given product category, and the second step is searching for matching product category candidates from the products of RSS feeds. The final step is calculating similarities of the candidates with the target product category. From the experiments, we could get better recall rates that are suitable for e-commerce environments and the results show that our system is effective in product comparison.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.3
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• pp.318-325
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• 2010

In this study, the wrapper database description language and model is suggested to collect product reviews from Korean shopping malls with multi-layer structures and are built in a variety of web languages. Above all, the wrapper based web crawlers have the website structure information to bring the exact desired data. The previously suggested wrapper based web crawler can collect HTML documents and the hierarchical structure of the target documents were only 2-3 layers. However, the Korean shopping malls in the study consist of not only HTML documents but also of various web language (JavaScript, Flash, and AJAX), and have a 5-layer hierarchical structure. A web crawler should have information about the review pages in order to visit the pages without visiting any non-review pages. The proposed wrapper contains the location information of review pages. We also propose a language grammar used in describing the location information.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.443-446
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• 2002

In this research, we suggest a Web-based hybrid recommendation mechanism using CBR (Case-Based Reasoning) and web data mining. Data mining is used as an efficient mechanism in reasoning for relationship between goods, customers' preference and future behavior. CBR systems are normally used in problems for which it is difficult to define rules. We use CBR as an AI tool to recommend the similar purchase case. A Web-log data gathered in real-world Internet shopping mall was given to illustrate the quality of the proposed mechanism. The results showed that the CBR and web data mining-based hybrid recommendation mechanism could reflect both association knowledge and purchase information about our former customers.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.25 no.1
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• pp.35-41
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• 2002

XML(eXtensible Markup Language) based electronic catalog is very useful for searching target information because of its structural and contents based searching support capability. And XML document editing is easier than HTML because of XML document is divided by structure, contents and presentation. This paper is to present a prototype of XML based Electronic Catalog Management System(ECMS) whose system consists of data input, output and manipulation system for inserting, updating, editing and deletion. A proposed system could resolved the problems at virtual intermediary shopping mall invloved in the difficulty of interoperability when customer try to compare similar products at mixed shopping mall and reduced web service costs at independent shopping mall by using XML format. The proposed ECMS offers rapid response capability for product data change of electronic catalog and easy and friendly interoperability among similar products.