User Preference Information Retrieval by Using Multiplicative Adaptive Refinement Search Algorithm

Abstract

One of the experiments of user preference information retrieval is to rank the most relevant documents. This system used MARS (Multiplicative Adaptive Refinement Search) algorithm for user preference information. User can give a query as an input. The input is the query that contains song name, song types, singer names that are part of the information which the user wants to know. The song information is retrieved from the web pages. The system returns the song information that is related to the input query that similarity values of web pages and query by using Cosine Similarity. From the initial result, user’s preference can mark by clicking the corresponding check box at interface. When the user marked the relevant document, and then refined by using MARS algorithm. The end result is the collection of documents list at a central location. The relevant documents are showed at the top of the system as output. This is called for choosing the proper methods to evaluate the system performance. The traditional performance measures, this system used precision and recall, are relies on user’s relevance judgment.