With the emergence of the deep Web, searching Web databases in domains such as vehicles, real estate, etc. has become a routine task. One of the problems in this context is ranking the results of a user query. Earlier approaches for addressing this problem have used frequencies of database values, query logs, and user profiles. A common thread in most of these approaches is that ranking is done in a user- and/or query-independent manner.
This paper proposes a novel query- and user-dependent approach for ranking query results in Web databases. We present a ranking model, based on two complementary notions of user and query similarity, to derive a ranking function for a given user query. This function is acquired from a sparse workload comprising of several such ranking functions derived for various user-query pairs. The model is based on the intuition that similar users display comparable ranking preferences over the results of similar queries. We define these similarities formally in alternative ways and discuss their effectiveness analytically and experimentally over two distinct Web databases.One Size Does Not Fit All Towards User- And Query-Dependent Ranking For Web Databases
The emergence of the deep Web has led to the proliferation of a large number of Web databases for a variety of applications (e.g., airline reservations, vehicle search, real estate scouting). These databases are typically searched by formulating query conditions on their schema attributes. When the number of results returned is large, it is time-consuming to browse and choose the most useful answer(s) for further
investigation. Currently, Web databases simplify this task by displaying query results sorted on the values of a single attribute (e.g., Price, Mileage, etc.). However, most Web users would prefer an ordering derived using multiple attribute values, which would be closer to their expectation. Consider Google Base’s Vehicle database that comprises of a table with attributes Make, Price, Mileage, Location, Color, etc. where each tuple represents a vehicle for sale