Embedded electronic dictionary word stock structure

Abstract

The invention discloses an embedded word stock structure of electronic dictionary, comprising a dictionary tree layer, a index flow layer and a information flow layer, wherein, the dictionary tree layer is the first layer and memory-resident and the index flow layer and the information flow layer are the second layer and the third layer respectively. The dictionary tree layer is tree index area used for rapid locating the word and the index flow layer is used for inputting a series of word lists most similar to the imported word in order to fix the word finally. The information flow layer is used for storing the information of concrete explanation of the word and the crunodes of the dictionary tree layer point to the corresponding index crunodes of the index flow layer. The words in the index crunodes of the index flow layer point to the block of explanation information of the words in the information flow layer. The invention has the advantages of rational and effective structure of the word stock, high independence of the layers and rapid and practical search, significantly decreased operation quantity of the processor, reduced match times during searching, greatly increased speed and efficiency of search and saved memory space.

Description

technical field [0001] The invention relates to the technical field of databases, in particular to a thesaurus structure of an embedded electronic dictionary. Background technique [0002] At present, the organizational structure of electronic dictionaries mostly adopts the physical structure of the first-level index. When using this structure, it is necessary to search in the entire index to match the input prefix, and generally a fixed-length index is used to search and match in the index by dichotomy. Using this method to index, the amount of data is generally relatively large, and it can only be stored in the external memory in the embedded system, so the query speed is relatively slow. And when the scale of the thesaurus reaches a certain level, the search efficiency will be greatly reduced for the thesaurus with this structure. At the same time, the fixed-length index structure will also cause a large waste of space. In addition, the processing power and storage cap...

AI Technical Summary

Problems solved by technology

Using this method to index, the amount of data is generally relatively large, and it can only be stored in the external memory in the embedded system, so the query speed is relatively slow

When the size of the thesaurus reaches a certain level, the search efficiency will be greatly reduced for the thesaurus with this structure.

At the same time, the fixed-length index structure will also cause a large waste of space

In addition, the processing power and storage capacity of the embedded system itself are extremely limited. In the case of a large-scale lexicon, using the above structure, the query efficiency and space utilization are very low, which is extremely inconvenient for users, which seriously affects the dictionary. Effectiveness and practicality

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