The Research on Recommender for New Customers Using Collaborative Filtering and Social Network Analysis (협력필터링과 사회연결망을 이용한 신규고객 추천방법에 대한 연구)
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- Journal of Intelligence and Information Systems
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- v.18 no.4
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- pp.19-42
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- 2012
Consumer consumption patterns are shifting rapidly as buyers migrate from offline markets to e-commerce routes, such as shopping channels on TV and internet shopping malls. In the offline markets consumers go shopping, see the shopping items, and choose from them. Recently consumers tend towards buying at shopping sites free from time and place. However, as e-commerce markets continue to expand, customers are complaining that it is becoming a bigger hassle to shop online. In the online shopping, shoppers have very limited information on the products. The delivered products can be different from what they have wanted. This case results to purchase cancellation. Because these things happen frequently, they are likely to refer to the consumer reviews and companies should be concerned about consumer's voice. E-commerce is a very important marketing tool for suppliers. It can recommend products to customers and connect them directly with suppliers with just a click of a button. The recommender system is being studied in various ways. Some of the more prominent ones include recommendation based on best-seller and demographics, contents filtering, and collaborative filtering. However, these systems all share two weaknesses : they cannot recommend products to consumers on a personal level, and they cannot recommend products to new consumers with no buying history. To fix these problems, we can use the information which has been collected from the questionnaires about their demographics and preference ratings. But, consumers feel these questionnaires are a burden and are unlikely to provide correct information. This study investigates combining collaborative filtering with the centrality of social network analysis. This centrality measure provides the information to infer the preference of new consumers from the shopping history of existing and previous ones. While the past researches had focused on the existing consumers with similar shopping patterns, this study tried to improve the accuracy of recommendation with all shopping information, which included not only similar shopping patterns but also dissimilar ones. Data used in this study, Movie Lens' data, was made by Group Lens research Project Team at University of Minnesota to recommend movies with a collaborative filtering technique. This data was built from the questionnaires of 943 respondents which gave the information on the preference ratings on 1,684 movies. Total data of 100,000 was organized by time, with initial data of 50,000 being existing customers and the latter 50,000 being new customers. The proposed recommender system consists of three systems : [+] group recommender system, [-] group recommender system, and integrated recommender system. [+] group recommender system looks at customers with similar buying patterns as 'neighbors', whereas [-] group recommender system looks at customers with opposite buying patterns as 'contraries'. Integrated recommender system uses both of the aforementioned recommender systems to recommend movies that both recommender systems pick. The study of three systems allows us to find the most suitable recommender system that will optimize accuracy and customer satisfaction. Our analysis showed that integrated recommender system is the best solution among the three systems studied, followed by [-] group recommended system and [+] group recommender system. This result conforms to the intuition that the accuracy of recommendation can be improved using all the relevant information. We provided contour maps and graphs to easily compare the accuracy of each recommender system. Although we saw improvement on accuracy with the integrated recommender system, we must remember that this research is based on static data with no live customers. In other words, consumers did not see the movies actually recommended from the system. Also, this recommendation system may not work well with products other than movies. Thus, it is important to note that recommendation systems need particular calibration for specific product/customer types.
When the marcher visited Korea in fall 1994, he was shocked to see high rise apartment buildings around the capitol region including Seoul and Suwon, resulting from rising demand of housing because of urban migration followed by second and third industrial development. After 6 years in March 2000, the researcher witnessed more apartment buildings and vinyl house complexes, one of the evidences of continued economic progress in Korea. Korea had to receive the rescue finance from International Monetary Fund (IMF) because of financial crisis in 1997. However, the sign of recovery was seen in a year, and the growth rate of Gross Domestic Products (GDP) in 1999 recorded as high as 10.7 percent. During this period, the Korean government has been working on restructuring of banks, enterprises, labour and public sectors. The major directions of government were; localization, reducing administrative manpower, limiting agricultural budgets, privatization of public enterprises, integration of agricultural organization, and easing of various regulations. Thus, the power of central government shifted to local government resulting in a power increase for city mayors and county chiefs. Agricultural extension services was one of targets of government restructuring, transferred to local governments from central government. At the same time, the number of extension offices was reduced by 64 percent, extension personnel reduced by 24 percent, and extension budgets reduced. During the process of restructuring, the basic direction of extension services was set by central Rural Development Administration Personnel management, technology development and supports were transferred to provincial Rural Development Administrations, and operational responsibilities transferred to city/county governments. Agricultural extension services at the local levels changed the name to Agricultural Technology Extension Center, established under jurisdiction of city mayor or county chief. The function of technology development works were added, at the same time reducing the number of educators for agriculture and rural life. As a result of observations of rural areas and agricultural extension services at various levels, functional responsibilities of extension were not well recognized throughout the central, provincial, and local levels. Central agricultural extension services should be more concerned about effective rural development by monitoring provincial and local level extension activities more throughly. At county level extension services, it may be desirable to add a research function to reflect local agricultural technological needs. Sometimes, adding administrative tasks for extension educators may be helpful far farmers. However, tasks such as inspection and investigation should be avoided, since it may hinder the effectiveness of extension educational activities. It appeared that major contents of the agricultural extension service in Korea were focused on saving agricultural materials, developing new agricultural technology, enhancing agricultural export, increasing production and establishing market oriented farming. However these kinds of efforts may lead to non-sustainable agriculture. It would be better to put more emphasis on sustainable agriculture in the future. Agricultural extension methods in Korea may be better classified into two approaches or functions; consultation function for advanced farmers and technology transfer or educational function for small farmers. Advanced farmers were more interested in technology and management information, while small farmers were more concerned about information for farm management directions and timely diffusion of agricultural technology information. Agricultural extension service should put more emphasis on small farmer groups and active participation of farmers in these groups. Providing information and moderate advice in selecting alternatives should be the major activities for consultation for advanced farmers, while problem solving processes may be the major educational function for small farmers. Systems such as internet and e-mail should be utilized for functions of information exchange. These activities may not be an easy task for decreased numbers of extension educators along with increased administrative tasks. It may be difficult to practice a one-to-one approach However group guidance may improve the task to a certain degree.