Web Document Management Based On Concept Lattice

Since the precision and recall of web information retrieval systems is very low now, we present a new method for automatic query expansion to improve the performance of retrieval. Techniques for automatic expansion have been extensively studied as a means for addressing words mismatch between queries and documents. However, these techniques always exist many limitations; for instance, they can't address the synonym and ambiguity in natural language synchronously. After analyzing the limitations of traditional techniques of query expansion, we describe a new technique of query expansion based on concept and user interaction. Firstly, we set up the ontology knowledge bases in a predefined set of domains based on Yahoo classified category, and retrieval documents using conceptual query expansion to replace traditional methods based on key words. Secondly, we utilized formal concept analysis and ontology knowledge to construct the concept lattice of query words in concept level for interacting and learning user's Interest profile automatically. By making the individual query expansion with user interaction, we can eliminate ambiguity of query words and expand words.Utilizing formal concept analysis to organize the result of searching finally, and combining domain knowledge according to the similar degree of each other, the pages are divided into several groups, every group has a clear theme, users can scan the group and choose the group those are most correlated with his goal rapidly.The main contribution of the thesis includes the following respect: (1)By studied the merits and defeats of traditional query expansion, this paper presents a new method of query expansion based on concept and user'interaction. By constructing the...