BEST KEYWORD SEARCH ON SPATIAL DATABASE WITH FRQUENT ITEM SEARCH

Abstract

Databases nowadays contain large volumes of data, and they are accessed by numerous users on a daily basis. The large volume of data poses challenges to both users accessing the databases and the companies or organizations managing them. Enterprises on the other hand, need to make their content visible and accessible to the users and identify which objects in their database (e.g. products) have a significant impact on the user basis and use this information for promoting their products. The original target of increasing the visibility of the available products is thus hindered by the abundance of products contained in the database. It is therefore necessary to develop data exploration techniques that will enable users to explore large databases and provide them with a wide, yet coherent overview of objects that fit their preferences. In this paper, we propose exploratory algorithms that return to the user a small number of results, which at the same time provide a wide overview of the available content. In addition, we present algorithms that identify items that are appealing to users and can be exploited for offering users an insight of the available items and motivating them to explore the database. We also propose analysis techniques using FP growth algorithm for identifying frequent search objects that are attractive to the users. This algorithm is a more efficient algorithm that achieves results of comparable quality, but with significantly lower processing cost