Detection of User Interesting Fields and Personalization of Search Results using User Search History Information

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.