Processing Repetitive Data

• US 20130013597A1
• Filed: 06/14/2012
• Published: 01/10/2013
• Est. Priority Date: 06/17/2011
• Status: Abandoned Application

• Current Assignee: Alibaba Group Holding Ltd.
• Original Assignee: Alibaba Group Holding Ltd.
• Inventors: He, Yixin, Ye, Ruihai, Wu, Xieyao, Zhang, Wenbo
• Application Number:
  US13/522,579
• Publication Number:
  US 20130013597A1
• Time in Patent Office: Days
• US Class Current: 707/736
• CPC Class Codes: G06F 16/215 Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors
• CPC Class Codes: G06F 40/20 Natural language analysis semantic analysis of natural language G06F40/30
• CPC Class Codes: G06Q 30/00 Commerce

Abstract

The present disclosure introduces a method, an apparatus, and a system of processing repetitive data. In an example embodiment, the data structure of the comparison data to be compared is processed as having a same data structure of the data in the repetition database. The repetition database is formed by an internal memory mapping after processing data in a database according to a preset data structure. The processed comparison data is compared with data in the repetition database to determine whether the comparison data is repetitive data. After it is determined that the comparison data is not repetitive data, the comparison data is written into the database. The techniques described herein improve the efficiency of the servers for eliminating repetitive data and save the server resources.

Claims

1. A method performed by one or more processors configured with computer-executable instructions, the method comprising:

processing a data structure of comparison data to be same or substantially same as a data structure of data in a repetition database, the repetition database being formed by an internal memory mapping after data in a database is processed according to a preset data structure;

comparing the comparison data with the data in the repetition database to determine whether the comparison data is repetitive data; and

in response to a result that the comparison data is not repetitive data, storing the comparison data in the database.

2. The method as recited in claim 1, wherein the processed comparison data includes first information for complete matching and second information for similarity degree matching.

3. The method as recited in claim 2, wherein the comparing the comparison data with the data in the repetition database to determine whether the comparison data is repetitive data comprises:

if the first information of the comparison data is same or substantially same as first information of the data in the repetition database and a similarity degree between the second information of the comparison data and second information of the data in the repetition data is higher than a threshold, determining that the comparison data is repetition data.

4. The method as recited in claim 2, wherein the comparing the comparison data with the data in the repetition database to determine whether the comparison data is repetitive data comprises:

if the first information of the comparison data is same or substantially same as first information of the data in the repetition database and a similarity degree between the second information of the comparison data and second information of the data in the repetition data is higher than a threshold, determining a form of relationship between the comparison data and the data in the repetition database according to a relationship between sizes of one or more images in the comparison data and sizes of one or more images in the data in the repetition database.

5. The method as recited in claim 1, wherein the form of relationship between the comparison data and the data in the repetition database includes one of the following:

the comparison data is same as the data in the repetition database;

the comparison data contains the data in the repetition database;

the data in the repetition database contains the comparison data.

6. The method as recited in claim 2, wherein:

the first information includes at least a combination formed by one or more items in the comparison data that requires complete matching and a value of the combination after the combination is processed by a hashing algorithm or an encryption algorithm; and

the second information includes at least a value of a portion in the comparison data that requires similarity degree matching after the portion is processed by a compression algorithm.

7. The method as recited in claim 6, wherein the one or more items that form the combination are preset.

8. The method as recited in claim 2, wherein the data in the repetition database includes first information for complete matching and second information for similarity degree matching and the first information and the second information are stored in the repetition database in a form of key-value pair.

9. The method as recited in claim 1, further comprising, prior to comparing the comparison data with the data in the repetition database to determine whether the comparison data is repetitive data, pre-processing the comparison data.

10. The method as recited in claim 9, wherein the pre-processing includes at least one of the following:

an upper and lower case conversion;

a full and half-width conversion;

a special characters filtering;

an acrophonetic word replacement;

a simple and meaningless word replacement;

a keyword extraction;

a removal of HTML tags.

11. The method as recited in claim 1, further comprising, prior to comparing the comparison data with the data in the repetition database to determine whether the comparison data is repetitive data, receiving the comparison data through a processing of load-balancing.

12. An apparatus comprising:

a processing module that processes a data structure of comparison data to be same or substantially same as a data structure of data in a repetition database, the repetition database being formed by an internal memory mapping after data in a database is processed according to a preset data structure;

a comparison module that compares the comparison data with the data in the repetition database to determine whether the comparison data is repetitive data; and

a writing module that, in response to a result that the comparison data is not repetitive data, stores the comparison data in the database.

13. The apparatus as recited in claim 12, wherein the processed comparison data includes first information for complete matching and second information for similarity degree matching and the comparison module, after determining that the first information of the comparison data is same or substantially same as first information of the data in the repetition database and a similarity degree between the second information of the comparison data and second information of the data in the repetition data is higher than a threshold, determines that the comparison data is repetition data.

14. The apparatus as recited in claim 13, wherein the comparison data includes one or more images and the comparison module, after determining that the first information of the comparison data is same or substantially same as first information of the data in the repetition database and the similarity degree between the second information of the comparison data and second information of the data in the repetition data is higher than the threshold, determines a form of relationship between the comparison data and the data in the repetition database according to a relationship between sizes of one or more images in the comparison data and sizes of one or more images in the data in the repetition database, the form of relationship between the comparison data and the data in the repetition database including one of the following:

the comparison data is same as the data in the repetition database;

the comparison data contains the data in the repetition database;

the data in the repetition database contains the comparison data.

15. The apparatus as recited in claim 13, wherein:

the first information includes at least a combination formed by one or more items in the comparison data that requires complete matching and a value of the combination after the combination is processed by a hashing algorithm or an encryption algorithm; and

the second information includes at least a value of a portion in the comparison data that requires similarity degree matching after the portion is processed by a compression algorithm.

16. The apparatus as recited in claim 13, wherein the data in the repetition database includes first information for complete matching and second information for similarity degree matching and the first information and the second information are stored in the repetition database in a form of key-value pair.

17. The apparatus as recited in claim 12, further comprising prior to comparing the comparison data with the data in the repetition database to determine whether the comparison data is repetitive data, pre-processing the comparison data, the pre-processing including at least one of the following:

an upper and lower case conversion;

a full and half-width conversion;

a special characters filtering;

an acrophonetic word replacement;

a simple and meaningless word replacement;

a keyword extraction;

a removal of HTML tags.

18. The apparatus as recited in claim 12, further comprising, prior to comparing the comparison data with the data in the repetition database to determine whether the comparison data is repetitive data, receiving the comparison data through a processing of load-balancing.

19. A system comprising:

a distribution device that sends comparison data to one or more apparatuses for processing repetitive data based on load-balance of the one or more apparatuses for processing repetitive data; and

at least one of the one or more apparatuses for processing repetitive data including;

a processing module that processes a data structure of comparison data to be same or substantially same as a data structure of data in a repetition database, the repetition database being formed by an internal memory mapping after data in a database is processed according to a preset data structure;

a comparison module that compares the comparison data with the data in the repetition database to determine that the comparison data is repetitive data after determining that first information of the comparison data is same or substantially same as first information of the data in the repetition database and a similarity degree between second information of the comparison data and second information of the data in the repetition data is higher than a threshold, the first information including at least a combination formed by one or more items in the comparison data that requires complete matching and a value of the combination after the combination is processed by a hashing algorithm or an encryption algorithm, the second information including at least a value of a portion in the comparison data that requires similarity degree matching after the portion is processed by a compression algorithm; and

a writing module that, in response to a result that the comparison data is not repetitive data, stores the comparison data in the database.

20. The system as recited in claim 19, wherein the comparison data includes one or more images and the comparison module, after determining that the first information of the comparison data is same or substantially same as first information of the data in the repetition database and the similarity degree between the second information of the comparison data and second information of the data in the repetition data is higher than the threshold, determines a form of relationship between the comparison data and the data in the repetition database according to a relationship between sizes of one or more images in the comparison data and sizes of one or more images in the data in the repetition database, the form of relationship between the comparison data and the data in the repetition database including one of the following:

the comparison data is same as the data in the repetition database;

the comparison data contains the data in the repetition database;

the data in the repetition database contains the comparison data.