METHOD AND SYSTEM FOR CLASSIFICATION OF VENUE BY ANALYZING DATA FROM VENUE WEBSITE

• US 20090307238A1
• Filed: 06/05/2008
• Published: 12/10/2009
• Est. Priority Date: 06/05/2008
• Status: Active Grant

• Current Assignee: Craze, Inc.
• Original Assignee: Craze, Inc.
• Inventors: Sanguinetti, Dave T., Sanguinetti, Thomas V., Ploetner, Jeffrey S.
• Granted Patent: US 8,918,369 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/00 Information retrieval; Database structures therefor; File system structures therefor
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0627 using item specifications
• CPC Class Codes: G06Q 50/12 Hotels or restaurants

Abstract

A method and system classifies a venue by analyzing venue data from a venue website. The method includes receiving preliminary venue-related data. The method includes scanning the venue website to retrieve venue data, wherein scanning the venue website includes retrieving the venue data from HTML pages, text documents, PDF documents, and images. The method includes retrieving verifiable venue data from the venue data. The verifiable venue data is a subset of the venue data. The method includes analyzing the verifiable venue data by comparing the verifiable venue data to the preliminary venue-related data and determining a probability level for the venue URL from the comparison. If the probability level for the venue URL is equal or greater than a first probability level, the venue website data is further analyzed to extract attributes and attribute counts in a robust and context-sensitive way. The method includes determining the percentage of the attribute representation from the total number of preselected attributes in the venue data and classifying the venue based on the percentage of the attribute representation.

Claims

1. A method for classifying a venue by analyzing venue data from a venue website, comprising:

receiving preliminary venue-related data including a venue URL;

scanning the venue website to retrieve venue data;

retrieving verifiable venue data from the venue data, the verifiable venue data being a subset of the venue data;

analyzing the verifiable venue data by comparing the verifiable venue data to the preliminary venue-related data;

determining a probability level for the venue URL from the comparison;

if the probability level for the venue URL is equal or greater than a first probability level, determining the number of selected attributes in the venue data;

determining the percentage of the attribute representation from the total number of preselected attributes in the venue data;

classifying the venue based on the percentage of the attribute representation.

2. The method of claim 1, further comprising:

determining attribute distance association by identifying correlation of attributes;

quantifying attribute similarities from the attribute distance association;

comparing the classified venue to other venues based on quantified attribute similarities.

3. The method of claim 1, further comprising classifying the atmosphere of the venue based on the attributes.

4. The method of claim 1, wherein the preliminary venue-related data comprises venue address, venue phone number, and venue category.

5. The method of claim 1, wherein scanning the venue website comprises retrieving the venue data from HTML pages, text documents, PDF documents and images.

6. The method of claim 1, wherein the verifiable venue data includes venue name, venue address, and venue phone number.

7. The method of claim 1, further comprising:

comparing selected verifiable venue data to corresponding preliminary venue-related data;

determining if the selected verifiable venue data is different from the corresponding preliminary venue-related data;

assigning a probability level lower than the first probability level if the selected verifiable venue data is different from the corresponding preliminary venue-related data.

8. The method of claim 7, wherein the selected verifiable venue data is the venue address.

9. The method of claim 7, wherein the selected verifiable venue data is the venue phone number.

10. The method of claim 1, wherein the selected attributes include attribute synonyms.

11. The method of claim 1, wherein the classification of the venue further comprises:

assigning a classifier factor for each selected attribute in the venue data;

classifying the venue from the assigned classifier factors.

12. The method of claim 11, wherein the classifier factor is a fanciness factor.

13. The method of claim 11, wherein the classifier factor is an outdoorsy factor.

14. The method of claim 11, wherein the classifier factor is an activity factor.

15. A method for classifying a venue by analyzing venue data from a venue website, comprising:

receiving venue data from the venue website;

determining the number of preselected attributes in the venue data;

determining a percentage of each preselected attribute representation from the total number of preselected attributes in the venue data;

assigning a classifier factor for each preselected attribute in the venue data;

classifying the venue based on the percentage of each attribute representation and the classifier factor.

16. The method of claim 15, wherein the receiving venue data comprises scanning and retrieving information from the venue website'"'"'s HTML pages, text documents, PDF documents and images.

17. The method of claim 15, further comprising:

receiving preliminary venue-related data;

retrieving verifiable venue data from the venue data;

analyzing verifiable venue data by comparing the verifiable venue data to preliminary venue-related data;

determining a probability level for the venue'"'"'s URL from the comparison;

verifying the venue from the probability level for the URL.

18. The method of claim 15, further comprising:

determining attribute distance association for the preselected attributes in the venue data;

quantifying attribute similarities from the attribute distance association;

comparing the venue to other venues based on quantified attribute similarities.

19. A method for classifying a venue by analyzing selected attributes in a venue website, comprising:

entering the venue website using a URL corresponding to the website;

receiving venue data from the venue website;

determining the number of selected attributes in the venue website;

determining a percentage of each selected attribute representation from the total number of preselected attributes in the URL data;

assigning a classifier factor for each selected attribute in the URL data;

classifying the venue based on the percentage of each attribute representation and the classifier factor.

20. The method of claim 19, wherein the receiving venue data comprises scanning and retrieving information from the venue website'"'"'s HTML pages, text documents, PDF documents and images.

21. The method of claim 19, further comprising:

receiving preliminary venue-related data;

retrieving verifiable venue data from the venue data;

analyzing verifiable venue data by comparing the verifiable venue data to preliminary venue-related data;

determining a probability level for the venue'"'"'s URL from the comparison;

verifying the venue from the probability level for the URL.

22. The method of claim 19, further comprising:

determining attribute distance association for the selected attributes in the venue data;

quantifying attribute similarities from the attribute distance association;

comparing the venue to other venues based on quantified attribute similarities.

23. A system for classifying a venue by analyzing venue data from a venue website, comprising:

a server having a central processing unit, the server receiving the venue data from the venue website;

a venue classification application having program code for executing a plurality of steps to analyze the venue data and classify the venue data;

a communication network enabling the server to access the venue website to receive the venue data;

the central processing unit executing the steps of;

determining the number of selected attributes in the venue data;

determining a percentage of each selected attribute representation from the total number of selected attributes in the venue data;

assigning a classifier factor for each selected attribute in the venue data;

classifying the venue based on the percentage of each attribute representation and the classifier factor.

24. The system of claim 23, wherein the communication network is the Internet.