answering bounded continuous search queries in the world wide web
Search queries applied to extract relevant information from the World Wide Web over a period of time may be denoted as continuous search queries. The improvement of continuous search queries may concern not only the quality of retrieved results but also the freshness of results, i.e. the time between the availability of a respective data object on the Web and the notification of a user by the search engine. In some cases a user should be notified immediately since the value of the respective information decreases quickly, as e.g. news about companies that affect the value of respective stocks, or sales offers for products that may no longer be available after a short period of time. In the document filtering literature, the optimization of such queries is usually based on threshold classification. Documents above a quality threshold are returned to a user. The threshold is tuned in order to optimize the quality of retrieved results. The disadvantage of such approaches is that the amount of information returned to a user may hardly be controlled without further user-interaction. In this paper, we consider the optimization of bounded continuous search queries where only the estimated best k elements are returned to a user. We present a new optimization method for bounded continuous search queries based on the optimal stopping theory and compare the new method to methods currently applied by Web search systems. The new method provides results of significantly higher quality for the cases where very fresh results have to be delivered.
optimal stopping monitoring search continuous queries