Information filtering and query indexing for an information retrieval model

Abstract

In the information filtering 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 article deals with the filtering problem that needs to be solved efficiently 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 . AWP is based on named attributes with values of type text, and its query language includes Boolean and word proximity operators.