Method and a system for selecting advertising spots

• US 9,117,219 B2
• Filed: 12/31/2008
• Issued: 08/25/2015
• Est. Priority Date: 12/31/2007
• Status: Expired due to Fees

• Current Assignee: Sizmek Technologies Inc (Sizmek, Inc.)
• Original Assignee: PEER 39 Incorporated
• Inventors: Solomon, Amiad, Koppel, Moshe
• Primary Examiner(s): DANG, THANH HA T
• Application Number:
  US12/347,027
• Publication Number:
  US 20090171948A1
• Time in Patent Office: 2,428 Days
• Field of Search: 707/706, 707/723, 707/710, 707/736, 707/737, 707/758, 707/727, 705/14.4
• US Class Current: 1/1
• CPC Class Codes: G06F 16/435 Filtering based on additional data, e.g. user or group profiles
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

A method for selecting advertisement spots that comprises providing parameters, each associated with one or more references to web documents which are retrieved by it, receiving a description of a product, identifying a match between the received description and at least one of the parameters, and generating a list of references which are associated with the at least one parameter.

Claims

1. A computerized method for selecting advertisement spots for promotional content pertaining to a product using a processor, comprising:

automatically browsing, by a crawler program, a network or any segment thereof in a methodical manner to identify a plurality of web documents having a plurality of advertising spots;

automatically extracting at a content analysis module, a plurality of content identifiers from a content of each of said plurality of web documents having said plurality of advertising spots according to a content analysis, said content is set to be displayed in association with respective said advertising spot, said content identifiers stored in a repository;

receiving, from an advertisement entity promoting or enhancing the exposure of browsing users to a certain product, a product description indicative of a plurality of properties of said product at a matching unit having a processor;

automatically identifying at said matching unit, a match between said product description and each member of an identified cluster of web documents selected from said plurality of web documents according to said plurality of content identifiers;

after said identifying said cluster of web documents, forwarding by at output unit, said cluster of web documents to an advertisement server; and

selecting, by said advertisement server, specific promotional content pertaining to said certain product to be advertised to said browsing users who access a member of said cluster;

wherein said advertisement server provides each one of said plurality of browsing users with said specific promotional content in response to a request to load said member.

2. The computerized method of claim 1, wherein said product is selected from a group consisting of:

a product, a service, a website, a movie, and a show.

3. The computerized method of claim 1, wherein said access consists of:

a reference to a web document linking to said web document and a reference to a web document linked from said web document.

4. The computerized method of claim 1, wherein said extracting comprises, for each said plurality of content identifiers, estimating a relevancy weight of each said advertising spot, said identifying comprising generating said cluster according to respective said relevancy weights.

5. The computerized method of claim 4, wherein said extracting further comprises:

tracing a plurality of referrers to a plurality of web documents; and

weighting each said web document according to said tracing;

wherein said estimating is performed according to said weighting.

6. The computerized method of claim 4, wherein said extracting further comprises analyzing content of a plurality of web documents, wherein said estimating is performed according to said analyzing.

7. The computerized method of claim 1, wherein said extracting further comprises:

tracing a plurality of referrers to a plurality of web documents; and

selecting said plurality of content identifiers according to said tracing.

8. The computerized method of claim 1, wherein said web document is selected from a group consisting of:

a webpage, a video file, an audio file, a podcast, a word processor document, a portable document format (PDF) document, an excel spreadsheet document, an extensible markup language (XML) page, a hypertext markup language (HTML) page, and a content file being accessible via a communication network.

9. The computerized method of claim 1, wherein said extracting comprises clustering a plurality of websites in a plurality of clusters each said cluster being associated with at least one of said plurality of content identifiers and being identified from said plurality of clusters according to a match between said product description and said at least one associated content identifier.

10. The computerized method of claim 9, wherein each said cluster indicating a product type, each said website being clustered according to a match between said respective at least one content identifier and a respective said product type, said selecting being perform from said plurality of clusters.

11. The computerized method of claim 1, wherein said extracting further comprises providing a list of a plurality of undesirable content elements, said identifying comprises identifying a match between said plurality of undesirable content elements and at least one content element of each said web document.

12. The computerized method of claim 11, wherein said undesirable content element is selected from a group consisting of:

an objectionable word, an objectionable paragraph, an objectionable image, an objectionable phrase, and an objectionable word combination.

13. The computerized method of claim 11, further comprising identifying at least one additional undesirable content element in each said web document by analyzing a sub-group of each said web document, each member of said sub-group having at least one of the said plurality of undesirable content elements, said identifying being performed according to a match between said at least one additional undesirable content and at least one content element of each said web document.

14. The method of claim 1, wherein said product description has at least one term in excess to said promotional content.

15. The method of claim 1, wherein at least one of said plurality of properties of a product is absent from said promotional content.

16. A computerized method for selecting advertisement spots for promotional content pertaining to a product using a processor, comprising:

automatically browsing, by a crawler program, a network or any segment thereof in a methodical manner to identify a plurality of web documents having a plurality of advertising spots;

associating, between a plurality of references of said plurality of web documents and a plurality of content identifiers automatically extracted at a content analysis module, each said web document being associated according to a content analysis of a content thereof which is set to be displayed in association with at least one advertisement of said plurality of advertising spots;

receiving, from an advertisement entity promoting or enhancing the exposure of browsing users to a certain product, a product description indicative of a plurality of properties of said product at a matching unit having the processor;

automatically selecting at said matching unit a cluster of references from said plurality of references according to a match between said product description and said plurality of content identifiers using said matching unit;

after selecting said cluster of references, forwarding said cluster of references to an advertisement server; and

selecting, by said advertisement server, specific promotional content pertaining to said certain product to be advertised to said browsing users who access a member of said cluster;

wherein said advertisement server provides each one of said plurality of browsing users with said specific promotional content in response to a request to load said member.

17. A system having a processor for selecting advertisement spots, comprising:

a crawler program configured to browse a network or any segment thereof in a methodical manner to identify a plurality of web documents having a plurality of advertising spots;

a repository which stores for each of said plurality of web documents a plurality of content identifiers which are automatically extracted at a content analysis module by a content analysis of a content thereof which is set to be displayed in association with at least one advertisement of said plurality of advertising spots;

a receiving unit configured for receiving, from an advertisement entity promoting or enhancing the exposure of browsing users to a certain product, a product description indicative of a plurality of properties of said product;

a matching unit which uses the processor for automatically identifying a match between said product description and at least one of said plurality of content identifiers; and

an output unit which generates each member of a cluster of web documents according to said match and after generating said cluster of web documents, forwards a list of web document advertisement spots to an advertisement server, each member of said list of web document advertisement spots being associated with said at least one content identifier;

wherein said advertisement server selects specific promotional content pertaining to said certain product to be advertised to said browsing users who access a certain web document of said plurality of web documents, said certain web document having at least one member of said list of advertisement spots;

wherein said advertisement server provides each one of said browsing users with said specific promotional content in response to a request to load said certain web document.

18. The system of claim 17, further comprising at least one tracing module configured for tracing a plurality of referrers to a plurality of web documents and weighting each said web document according to said tracing, wherein said list of advertisement spots is generated according to said weighting.

19. The system of claim 17, wherein said content analysis module is configured for analyzing a content of said web document, said matching unit being configured for identifying a match between at least one of said product description and said at least one content identifier and said content.

20. The system of claim 17, further comprising a reputation protection module configured for probing a plurality of undesirable content elements in said web document, said output module unit being configured for filtering said list of advertisement spots according to said probing.

21. The system of claim 17, wherein said repository maps an ad exchange network.

22. The system of claim 17, wherein said output unit being configured for forwarding said list of references to an advertising server for allowing the advertising of said product in at least one web document referred to by said list of advertisement spots.

23. A computerized method for advertising according to a content of communication content messages using a processor, comprising:

automatically browsing, by a crawler program, a network or any segment thereof in a methodical manner to identify a plurality of web documents having a plurality of advertising spots;

providing a plurality of content identifiers associated with a plurality of references of said plurality of web documents according to content analysis of a content of said plurality of web documents which is set to be displayed in association with at least one advertisement of said plurality of advertising spots, said content identifiers automatically extracted at a content analysis module;

receiving, from an advertisement entity promoting or enhancing the exposure of at least one of a sender and a receiver to a certain product, a product description indicative of a plurality of properties of said product at a matching unit having the processor;

automatically identifying a match between said product description and at least one of said plurality of content identifiers using said matching unit; and

sending specific promotional content pertaining to said certain product description to at least one of a sender and a receiver of a communication content message including at least one of matched said plurality of content identifiers;

wherein said communication content message comprises a member of a group consisting of a short message service (SMS) message, an instant messaging (IM) message, a multimedia messaging service (MMS) message, and a wireless application protocol (WAP) message.

24. The computerized method of claim 23, wherein said plurality of content identifiers comprises at least one member of a group consisting of a word, a paragraph, a link, a combination of paragraphs and a combination of words.

25. The computerized method of claim 23, wherein said sending is performed concurrently to at least one of a sending of said communication content message and a receiving of said communication content message.

26. The computerized method of claim 23, wherein said sending comprises personalizing said promotional content according to at least one characteristic of said at least one sender and receiver.

27. A computerized method for advertising according to content analysis, comprising:

automatically browsing, by a crawler program, a network or any segment thereof in a methodical manner to identify a plurality of web pages having a plurality of advertisement spots;

receiving a plurality of certain product descriptions from an advertising entity promoting or enhancing the exposure of browsing users to certain products;

automatically analyzing at a content analysis module, a textual content of each one of said plurality of web pages to identify a plurality of content identifiers;

clustering said plurality of web pages in a plurality of clusters by adding each one of said plurality of web pages to one of said plurality of clusters according to respective said plurality of content identifiers;

automatically associating at a matching unit said plurality of clusters of web pages with said plurality of product descriptions;

after creating said cluster of web documents, selecting specific promotional content for each one of said plurality of clusters according to a match with respective associated certain product description from said plurality of certain product descriptions.