The Study Of Automatic Mapping Between Chinese Library Classification And DDC

As the number of information spring up, information users ask more and more for information retrieval, they expect to browse and download the required document information resources in one-stop serve system. An information organization tool, classification vocabularies act an extremely important role in the integration and access process. Scholars from many countries concentrate on the development and research, established distinctive classification vocabularies. It is these vocabularies bring insurmountable gaps to information database. Database in different countries, different regions, represented with different languages, use different classification organizing their IR, appear different retrieval interface, required user mastering diverse retrieval strategies. This result in many issues as retrieval difficult, inefficient use of IR, poor shared.Classification interoperation is an important means to solve the "one stop" access to demand. As the widest used international classification, is the best choose to achieve domestic classification connected with the world’s. The current researches are concentrated in the theoretical level of DDC and CLC interoperation. Because of low accuracy matching, small research coverage, copyright issues, it is difficult to realize their interoperation. Under this background, it needs more effective methods to solve these problems, then semantic similarity calculation, co-occurrence mapping, cross-browser begin used in automatic mapping. As an effectively interoperate method, categories mapping can connect the two independent classification, and then connect the information resource they represented.First, this paper makes a brief overview on present research situation of information retrieval language interoperation, and makes detailed research and analysis classification interoperation in types, methods, semantic similarity calculation. Based on artificial mapping achieving the categories of science, this paper analyze and compare targeted the established principles, class table structures, category levels, languages between DDC and CLC, conclude the basis of categories mapping, which include category names, notations, subject vocabularies, semantic relations, bibliographic records and so on, and their used situation in mapping. This paper envisages trying to put the artificial mapping data in the automatic computer mapping system, based on characteristic similarity calculation of each basis, achieves partial match, and then combined the principle of bibliographic records, finishes they two matches. This would improve the integrity and accuracy of computer automatic mapping between DDC and CLC, overcome the existing limitation of relying solely on the category names matching method. Based on this principle and method, this paper experiment the data finished mapping, then calculate the priority and weight values of each kind of basis and their characteristic words.