Entity similarity matching method and system
A matching method and entity technology, which can be applied in the fields of instruments, electrical digital data processing, computer components, etc., can solve problems such as low efficiency, and achieve the effect of improving efficiency
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Embodiment 1
[0034] The entity similarity matching method described in the embodiment of the present invention, such as figure 1 shown, including the following steps:
[0035] Step S1, initialize entity index table HASH_ENT, word index table HASH_CHAR and stop word and high-frequency word table STTF_WORD, described entity index table HASH_ENT is used for storing all entities, and described word index table HASH_CHAR is used for storing except stop word and high-frequency word table STTF_WORD The mapping relationship between all words of high-frequency words and entities, the stop word and high-frequency word table STTF_WORD is used to store stop words and high-frequency words in entities;
[0036] In this embodiment, the entity index table HASH_ENT and the word index table HASH_CHAR use a hash index, the hashkey of the entity index table is an auto-increment number sequence, the hashvalue of the entity index table HASH_ENT is an entity; the hashkey of the word index table HASH_CHAR is a wo...
Embodiment 2
[0061] Assuming that the input of the module is: "Infernal Affairs", the expected result is to return the most similar correct result "Infernal Affairs" within 100ms. The specific implementation process of the embodiment of the present invention is as follows.
[0062] Step A, initialize the entity index table HASH_ENT, the word index table HASH_CHAR and the stop word and high-frequency word table STTF_WORD, assuming that there are three title entities in the entity index table HASH_ENT: Infernal Affairs, Infernal Affairs, and Tomb Notes. Entity index table HASH_ENT such as image 3 As shown, the word index table HASH_CHAR such as Figure 4 As shown, the stop word and high frequency word table STTF_WORD such as Figure 5 shown;
[0063] Step B, receive the input "no gap to", and disperse the string sequence as ["none", "between", "to"], and filter stop words and high-frequency words;
[0064] Step C, search the word index table HASH_CHAR, and get the result: ["none":"0_3,1_...
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