2011 | OriginalPaper | Buchkapitel
A Component Clustering Index Tree Based on Semantic
verfasst von : Chunhong Wang, Yaopeng Ren
Erschienen in: Emerging Research in Web Information Systems and Mining
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
The reasonable classification of components is the basis and key of component efficient retrieval. In order to overcome the shortcomings of faceted classification method widely used, we adopt a method combing faceted classification with full-text retrieval to describe components. Based on that description, a component cluster index tree is proposed which uses cluster analysis technique and semantic analysis technique. And the experiments prove that the index tree is feasible, which can effectively overcome the shortcomings of faceted classification method. Meanwhile to some extent, it can achieve the component semantic retrieval and has higher component recall ratio and precision ratio. Moreover, the description of retrieval conditions is no longer limited by restrictive terms so as to be convenient for general users.