# US 11,113,474 B2 · Address analysis using morphemes > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,113,474 B2 - Document ID: US11113474B2 - Status: Granted - Kind: B2 - Application number: 15/944,569 - Filed: 2018-04-03 - Published: 2018-08-09 - Granted: 2021-09-07 - Earliest claimed: 2015-10-10 - Assignees: Advanced New Technologies Co., Ltd. - Applicants: Advanced New Technologies Co., Ltd. - Inventors: Qing Lu - Web page: https://patentgrep.com/patent/US11113474B2 ## CPC - G06F 40/30: Semantic analysis - G06F 40/268: Morphological analysis - G06F 40/53: Processing of non-Latin text (kana-to-kanji conversion G06F40/129; vowelisation G06F40/232) - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) ## Abstract A computer-implemented method comprises: receiving a first address and a second address, the first address including n morphemes and the second address including m morphemes, wherein a morpheme is a smallest semantic unit in the address, and wherein n and m are both natural numbers; determining first correlation values between the n morphemes and the m morphemes; obtaining, based on the first correlation values and a preset algorithm, a second correlation value between the first address and the second address; and analyzing a correlation between the first address and the second address based on the second correlation value. ## Claims ### Claim 1 A computer-implemented method comprising: receiving a first address and a second address representing one or more physical locations involved in an online transaction, the first address including n morphemes and the second address including m morphemes, wherein a morpheme is a smallest semantic unit in an address, and wherein n and m are both natural numbers; determining first correlation values between the n morphemes and the m morphemes; for each of the n morphemes as a first morpheme: selecting a second morpheme of the m morphemes that best matches the first morpheme based on the first correlation values and a preset algorithm; and recording a target correlation value between the first morpheme and the second morpheme as part of a set of n target correlation values; obtaining a second correlation value between the first address and the second address based on the n target correlation values, wherein the second correlation value is a summation of a plurality of values of the n target correlation values; and analyzing a correlation between the first address and the second address based on the second correlation value. ### Claim 2 (depends on 1) The computer-implemented method of claim 1, wherein determining the first correlation values comprises determining the first correlation values between each of the n morphemes and the m morphemes to obtain n×m first correlation values. ### Claim 3 (depends on 2) The computer-implemented method of claim 2, wherein selecting the second morpheme that best matches the first morpheme comprises: constructing an n×m matrix based on the n×m first correlation values; and pre-processing the n×m matrix based on the preset algorithm. ### Claim 4 (depends on 3) The computer-implemented method of claim 3, further comprising selecting the second morpheme based on the pre-processed n×m matrix. ### Claim 5 (depends on 1) The computer-implemented method of claim 1, wherein a value of the first correlation values is an edit distance value, a hamming distance value, a Jaccard distance value, an N-Gram distance value, a Jaro-Winkler (JW) distance value, or a cosine distance value. ### Claim 6 A non-transitory, computer-readable medium storing one or more instructions executable by a computer system to perform operations comprising: receiving a first address and a second address representing one or more physical locations involved in an online transaction, the first address including n morphemes and the second address including m morphemes, wherein a morpheme is a smallest semantic unit in an address, and wherein n and m are both natural numbers; determining first correlation values between the n morphemes and the m morphemes; for each of the n morphemes as a first morpheme: selecting a second morpheme of the m morphemes that best matches the first morpheme based on the first correlation values and a preset algorithm; and recording a target correlation value between the first morpheme and the second morpheme as part of a set of n target correlation values; obtaining a second correlation value between the first address and the second address based on the n target correlation values, wherein the second correlation value is a summation of a plurality of values of the n target correlation values; and analyzing a correlation between the first address and the second address based on the second correlation value. ### Claim 7 (depends on 6) The non-transitory, computer-readable medium of claim 6, wherein determining the first correlation values comprises determining the first correlation values between each of the n morphemes and the m morphemes to obtain n×m first correlation values. ### Claim 8 (depends on 7) The non-transitory, computer-readable medium of claim 7, wherein selecting the second morpheme that best matches the first morpheme comprises: constructing an n×m matrix based on the n×m first correlation values; and pre-processing the n×m matrix based on the preset algorithm. ### Claim 9 (depends on 8) The non-transitory, computer-readable medium of claim 8, the operations further comprising selecting the second morpheme based on the pre-processed n×m matrix. ### Claim 10 (depends on 6) The non-transitory, computer-readable medium of claim 6, wherein a value of the first correlation values is an edit distance value, a hamming distance value, a Jaccard distance value, an N-Gram distance value, a Jaro-Winkler (JW) distance value, or a cosine distance value. ### Claim 11 A computer-implemented system, comprising: one or more computers; and one or more computer memory devices interoperably coupled with the one or more computers and having tangible, non-transitory, machine-readable media storing one or more instructions that, when executed by the one or more computers, perform one or more operations comprising: receiving a first address and a second address representing one or more physical locations involved in an online transaction, the first address including n morphemes and the second address including m morphemes, wherein a morpheme is a smallest semantic unit in an address, and wherein n and m are both natural numbers; determining first correlation values between the n morphemes and the m morphemes; for each of the n morphemes as a first morpheme: selecting a second morpheme of the m morphemes that best matches the first morpheme based on the first correlation values and a preset algorithm; and recording a target correlation value between the first morpheme and the second morpheme as part of a set of n target correlation values; obtaining a second correlation value between the first address and the second address based on the n target correlation values, wherein the second correlation value is a summation of a plurality of values of the n target correlation values; and analyzing a correlation between the first address and the second address based on the second correlation value. ### Claim 12 (depends on 11) The computer-implemented system of claim 11, wherein determining the first correlation values comprises determining the first correlation values between each of the n morphemes and the m morphemes to obtain n×m first correlation values. ### Claim 13 (depends on 12) The computer-implemented system of claim 12, wherein selecting the second morpheme that best matches the first morpheme comprises: constructing an n×m matrix based on the n×m first correlation values; and pre-processing the n×m matrix based on the preset algorithm. ### Claim 14 (depends on 13) The computer-implemented system of claim 13, the operations further comprising selecting the second morpheme based on the pre-processed n×m matrix. ### Claim 15 (depends on 11) The computer-implemented system of claim 11, wherein a value of the first correlation values is an edit distance value, a hamming distance value, a Jaccard distance value, an N-Gram distance value, a Jaro-Winkler (JW) distance value, or a cosine distance value. ### Claim 16 (depends on 1) The computer-implemented method of claim 1, further comprising pre-processing the first address by varying a writing order of the first address to account for regional differences. ### Claim 17 (depends on 6) The non-transitory, computer-readable medium of claim 6, further comprising pre-processing the first address by varying a writing order of the first address to account for regional differences.