Detection of User Interesting Fields and Personalization of Search Results using User Search History Information Heejun Han, Heeseok Choi, Jaesoo Kim Department of NTIS, Korea Institute of Science and Technology Information 245 Daehak-ro, Yuseong-gu, Daejeon, South Korea hhj@kisti.re.kr, choihs@kisti.re.kr, jaesoo@kisti.re.kr ABSTRACT When a user inputs a search query to find a document or information, the search service provides a list of search results. To get more information, the user explores the provided list and selects one of the results to move to the page with detailed views. Most search services provide the same results for the same search queries. But providing the same results for the same search queries each time cannot satisfy the ever so different users‟ needs. In this article, we propose a method to analyze the user search query, search result set, and the user history for detailed views to decide an individual's field of interest, and reflect this information to individualize the search results. To obtain classification information for comprehending the users‟ fields of interest, the Dewey Decimal Classification (DDC) codes pre- assigned to the published journal document records are used, and this information is applied to re-rank the search results individually, using the boosting method. Using this method, different search results individualized to each user‟s preference are suggested for the same search queries by the users. KEYWORDS Search personalization; search history; user preference detection; information retrieval; boosting 1 INTRODUCTION Most internet users perform web searches to find wanted information. But most web search services provide the same search results for a search query regardless of individual interests [1-4]. This is problematic for users wanting to easily access information of interest and preference. It is most important to provide the desired information of the users at the top of the search results. If two users entered the same search term „virus‟ into a search service, the results desired by a computer engineer and a biologist may be different. For the computer engineer, information regarding computer viruses should be at the top of the search results, and for the biologist, information regarding disease related viruses is more appropriate. In this article, the users‟ search queries, search result set created by the search query, and users' history on provided detailed views are analyzed to determine individual fields of interest. Every time an individual performs a search, the weighted information on the user's fields of interest is recalculated and re-determined, and this information is reflected on the search results again to provide the information of preference at the top of the search results. The published journal database serviced by KISTI (Korea Institute of Science and Technology Information) was used as a search subject for this experiment, and the DDC codes were used to determine individual fields of interest. In section 2, we explain some related works about search technologies such as content personalization by user profile, content- based recommendation system, and a personalization retrieval system based on a classification and user query. In section 3, the user search history information used for determination of individual fields of interest will be defined and its storage structure is designed. And a method for determining individual fields of interest by analyzing search ISBN:978-0-9891305-8-5 ©2014 SDIWC 34