Journal of Jilin University (Information Science Edition) ›› 2019, Vol. 37 ›› Issue (4): 457-462.

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Design of Stac Course Database Automatic Retrieval System Based on Scene Theory

LI Shujun1a,ZHANG Hongjie2,WANG Haitang1b,WANG Qiushuang3   

  1. 1a. Department of Training Center Party School WorkState Grid Hebei Electric Power Company Limited;1b. Training Center,State Grid Hebei Electric Power Company Limited,Shijiazhuang 050023,China;2. Beijing Minxing Pioneering International Management Consulting CoLtd,Beijing 101100,China;3. College of Computer Science and Technology,Jilin University,Changchun 130012,China
  • Online:2019-07-24 Published:2019-12-16

Abstract: Due to the poor performance of the traditional course database retrieval system and the influence of noise,the retrieval accuracy is low,which can not meet the user's demand for Stac ( Statistical Analysis) course database retrieval. To this end,the design of the automatic retrieval system of Stac course database based on scene theory is proposed. Under the scene theory,the design of the database automatic retrieval system adding the word segmentation module,uses the combined ambiguity statistical method to distinguish synonymous or polysemous words in the Stac course database; and uses the web spider to find the web link address,reading the content,and performing all the goals address retrieval. When the collection volume reaches a certain scale,several independent search engines are called and cooperated with each other to establish an index library,collect data according to the Stac curriculum resource data specification standard,and use the index engine to input all the collection results into the system. By identifying the characteristics of the scene,the CD-ROM database is created,the retrieval process is designed,the behavior of each machine is closely monitored,and noise interference is avoided. After processing by the central DB ( Data Base) Server,the address lists are merged to form a new resource list for the user to retrieve. Experimental results show that the retrieval accuracy of the system can reach up to 98%,providing systematic support for multi-image retrieval.

Key words: scene theory, statistical analysis ( Stac) course, database, automatic retrieval, index, engine

CLC Number: 

  • TP391. 1