Personalized questions, answers and grammars: aiding the search for relevant web information

Abstract

This work is about guiding the user web search by generating most relevant questions, answers and grammars from web documents. The proposed approach is based on the representation of the main domain concepts as a set of attributes and relating these attributes to the user models and to a syntactico-semantic taxonomy, that describes the general relationships between conceptual and linguistic knowledge. This taxonomy is used for both generating questions and answers and also for extracting data from the web. The data extracted from the web documents is represented as instances of the domain concepts. Questions, answers and grammars are generated from these instances.