Obtaining Profiles Based on Localized Non-negative Matrix Factorization

Nonnegative matrix factorization (NMF) is a method to get parts-based features of information and form the typical profiles. But the basis vectors NMF gets are not orthogonal so that parts-based features of information are usually redundancy. In this paper, we propose two different approaches based on localized non-negative matrix factorization (LNMF) to obtain the typical user session profiles and typical semantic profiles of junk mails. The LNMF get basis vectors as orthogonal as possible so that it can get accurate profiles. The experiments show that the approach based on LNMF can obtain better profiles than the approach based on NMF. Key words localized non-negative matrix factorization - profile - log mining - mail filtering CLC number TP 391 Foundation item: Supported by the National Natural Science Foundation of China (60373066, 60303024), National Grand Fundamental Research 973 Program of China (2002CB312000), National Research Foundation for the Doctoral Program of Higher Education of China (20020286004).Biography: Jiang Ji-xiang (1980-), male, Master candidate, research direction: data mining, knowledge representation on the Web.

Bridge Ontology: A Multi-Ontologies-Based Approach for Semantic Annotation

Representing the relationships between ontologies is the key problem of semantic annotations based on multi-ontologies. Traditional approaches only had the ability of denoting the simple concept subsumption relations between ontologies. Through analyzing and classifying the relationships between ontologies, the idea of bridge ontology was proposed, which had the powerful capability of expressing the complex relationships between concepts and relationships between relations in multi-ontologies. Meanwhile, a new approach employing bridge ontology was proposed to deal with the multi-ontologies-based semantic annotation problem. The bridge ontology is a peculiar ontology, which can be created and maintained conveniently, and is effective in the multi-ontologies-based semantic annotation. The approach using bridge ontology has the advantages of low-cost, scalable, robust in the web circumstance, and avoiding the unnecessary ontology extending and integration. Key words semantic web - bridge ontology - multi-ontologies - semantic annotation CLC number TP 391 Foundation item: Supported by the National Natural Science Foundation of China (60373066, 60303024). National Grand Fundamental Research 973 Program of China (2002CB312000), National Re-search Foundation for the Doctoral Program of Higher Education of China (20020286004)Biography: WANG Peng (1977-), male, Ph.D candidate, research direction: semantic web, ontology, and knowledge representation on the Web.

A Classification Method for Web Information Extraction

Web information extraction is viewed as a classification process and a competing classification method is presented to extract Web information directly through classification. Web fragments are represented with three general features and the similarities between fragments are then defined on the bases of these features. Through competitions of fragments for different slots in information templates, the method classifies fragments into slot classes and filters out noise information. Far less annotated samples are needed as compared with rule-based methods and therefore it has a strong portability. Experiments show that the method has good performance and is superior to DOM-based method in information extraction. Key words information extraction - competing classification - feature extraction - wrapper induction CLC number TP 311 Foundation item: Supported by the National Natural Science Foundation of China (60303024)Biography: LI Xiang-yang (1974-), male, Ph. D. Candidate, research direction: information extraction, natural language processing.

Query Through Heterogeneous Ontologies Using Association Matrix

This paper introduces the definition and calculation of the association matrix between ontologies. It uses the association matrix to describe the relations between concepts in different ontologies and uses concept vectors to represent queries; then computes the vectors with the association matrix in order to rewrite queries. This paper proposes a simple method of querying through heterogeneous Ontology using association matrix. This method is based on the correctness of approximate information filtering theory; and it is simple to be implemented and expected to run quite fast. Key words semantic Web - information retrieval - ontology - query - association matrix CLC number TP 391 Foundation item: Supported by the National Natural Science Foundation of China (60373066, 60303024), National Grand Fundamental Research 973 Program of China (2002CB312000) and National Research Foundation for the Doctoral Program of Higher Education of China (20020286004)Biography: KANG Da-zhou (1980-), male, Master candidate, research direction: Semantic Web, knowledge representation on the Web.