Kakinada Institute of Engineering and Technology for Women
Abstract
User penchants are shown by a set of keywords. A central server monitors the document stream and continuously reports to each user the top-k documents that are most relevant to her keywords. Our unprejudiced is to backing large numbers of users and high stream rates, while energizing the top-k results almost instantly. Our clarification walks out on the customary frequency-ordered indexing approach. As an alternative, it trails an identifier-ordering paradigm that ensembles better the nature of the problem. When supplemented with a new, locally adaptive method, our method offers confirmed optimality the number of well-thought-out queries per stream event, and direction of extent shorter retort time than the contemporary state-of-the-art
