filtering algorithms for information retrieval models with named attributes and proximity operators
In the selective dissemination of information (or publish/subscribe) paradigm, clients subscribe to a server with continuous queries (or profiles) that express their information needs. Clients can also publish documents to servers. Whenever a document is published, the continuous queries satisfying this document are found and notifications are sent to appropriate clients. This paper deals with the filtering problem that needs to be solved effciently by each server: Given a database of continuous queries db and a document d , find all queries q ? db that match d . We present data structures and indexing algorithms that enable us to solve the filtering problem efficiently for large databases of queries expressed in the model AWP which is based on named attributes with values of type text, and word proximity operators.
filtering algorithms selective dissemination of information performance evaluation