Pangenetic Web Search System

• US 20100169338A1
• Filed: 12/30/2008
• Published: 07/01/2010
• Est. Priority Date: 12/30/2008
• Status: Abandoned Application

• Current Assignee: 23andme Incorporated (23andMe Holding Co.)
• Original Assignee: Expanse Networks, Inc.
• Inventors: Eldering, Charles Anthony, Kenedy, Andrew Alexander
• Application Number:
  US12/346,679
• Publication Number:
  US 20100169338A1
• Time in Patent Office: Days
• US Class Current: 707/758
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation

Abstract

Computer based systems, methods, software and databases are presented in which correlations between web items and pangenetic (genetic and epigenetic) attributes of individuals are used for pangenetic based web search in which a user can request and receive personalized web search results that are based on the user'"'"'s pangenetic makeup. Data masking can be used to maintain privacy of sensitive portions of the pangenetic data.

Claims

1. A computer based method for providing internet search results for a user, comprising:

a) receiving non-pangenetic data associated with a user query;

b) accessing pangenetic data associated with the user;

c) accessing a dataset containing pangenetic data and non-pangenetic data correlated with web items;

d) determining for each web item, the quantity of non-pangenetic matches between the non-pangenetic data correlated with that web item and the non-pangenetic data associated with the user query and the quantity of pangenetic matches between the pangenetic data correlated with that web item and the pangenetic data associated with the user; and

e) transmitting as output, based on the quantity of non-pangenetic matches and the quantity of pangenetic matches determined for each web item, a listing of at least a portion of the web items as internet search results for the user.

2. The computer based method of claim 1, wherein the transmitting in step (e) is to at least one destination selected from the group consisting of the user, a database, a dataset, a computer readable memory, a computer readable medium, a computer processor, a computer network, a printout device, a visual display, and a wireless receiver.

3. The computer based method of claim 1, wherein the pangenetic data correlated with the web items is pangenetic metadata.

4. The computer based method of claim 1, wherein the dataset containing pangenetic data and non-pangenetic data is selected from the group consisting of an internet search engine document index, an internet search engine hitlist, and an internet search engine lexicon dataset.

5. The computer based method of claim 1, wherein the pangenetic data associated with the user constitutes a pangenetic profile of the user.

6. The computer based method of claim 1, further comprising acts of i) transmitting an authorization request for access to the pangenetic data associated with the user, and ii) receiving an authorization granting access to the pangenetic data associated with the user.

7. The computer based method of claim 1, wherein the receiving in step (a) is from a mobile computing device, and wherein the transmitting in step (e) is to the mobile computing device.

8. The computer based method of claim 1, wherein each web item represented in the listing was determined in step (d) to have at least one non-pangenetic match.

9. The computer based method of claim 1, wherein the dataset containing pangenetic data and non-pangenetic data in step (c) is a lexicon dataset with pointers to entries in an internet search engine document index containing a hitlist, and wherein determining the quantity of matches in step (d) comprises identifying, from the hitlist, the quantity of non-pangenetic hits and the quantity of pangenetic hits for each web item with respect to the non-pangenetic data associated with the user query and the pangenetic data associated with the user, wherein hits are matches.

10. The computer based method of claim 1, wherein the portion of the web items transmitted as output is determined by one or more predetermined thresholds applied to the quantity of non-pangenetic matches and the quantity of pangenetic matches determined for each web item.

11. The computer based method of claim 1, wherein the listing is a rank listing, and wherein the rank of each web item in the rank listing is based on the quantity of non-pangenetic matches and the quantity of pangenetic matches determined for each web item.

12. The computer based method of claim 11, wherein the portion of the web items transmitted as output consists of web items having a rank within a range defined by at least one predetermined threshold applied to rank.

13. The computer based method of claim 11, wherein the rank listing contains two sets of ranks for the web items in the rank listing, the first set of ranks being based on the quantity of non-pangenetic matches, and the second set of ranks being based on the quantity of non-pangenetic matches and the quantity of pangenetic matches.

14. The computer based method of claim 11, wherein the rank of each web item in the rank listing is determined by a score computed for each web item based on the quantity of non-pangenetic matches and the quantity of pangenetic matches for each web item.

15. The computer based method of claim 14, wherein a score for a web item is computed by using a quantitative similarity measure to determine a non-pangenetic similarity value based on the quantity of non-pangenetic matches and a pangenetic similarity value based on the quantity of pangenetic matches, and then averaging the non-pangenetic similarity value with the pangenetic similarity value to generate the score for the web item.

16. The computer based method of claim 11, wherein the dataset of step (c) also contains context of occurrence values for the pangenetic data and non-pangenetic data correlated with each web item, the method further comprising:

i) identifying, with respect to a web item, the non-pangenetic context of occurrence values for each of the non-pangenetic data correlated with the web item which match non-pangenetic data associated with the user query;

ii) computing a non-pangenetic score for the web item by combining the non-pangenetic context of occurrence values with the quantity of matches determined for the corresponding non-pangenetic data;

iii) identifying, with respect to the web item, the pangenetic context of occurrence values for each of the pangenetic data correlated with the web item which match pangenetic data associated with the user query;

iv) computing a pangenetic score for the web item by combining the pangenetic context of occurrence values with the quantity of matches determined for the corresponding pangenetic data;

v) determining a final score for the web item by averaging the non-pangenetic score with the pangenetic score;

vi) repeating steps (i) to (v) for each of the web items; and

vii) determining the rank of each web item based on the final scores determined for the web items.

17. The computer based method of claim 1, wherein the pangenetic data correlated with the web items are derived from statistical associations between item preferences and pangenetic data associated with a group of individuals.

18. The computer based method of claim 1, wherein the pangenetic data correlated with the web items are derived by computing statistical associations which indicate the strength of association between the item preferences and pangenetic data associated with a group of individuals.

19. The computer based method of claim 1, wherein the pangenetic data correlated with the web items are derived from statistical associations between pangenetic data associated with individuals and online behaviors the individuals exhibit while interacting with the web items.

20. The computer based method of claim 1, wherein the pangenetic data correlated with the web items are derived from an item feedback matrix containing correlations between item preferences and pangenetic data associated with a group of individuals.

21. The computer based method of claim 20, further comprising:

i) receiving item preference data associated with a plurality of individuals, wherein the item preference data indicates item preferences of the plurality of individuals;

ii) accessing pangenetic data associated with the plurality of individuals;

iii) determining correlations between the item preference data and the pangenetic data associated with the plurality of individuals; and

iv) storing the correlations between the item preference data and the pangenetic data to generate an item feedback matrix.

22. The computer based method of claim 1, wherein the accessing in step (b) is in accordance with an applied data mask, the method further comprising:

i) transmitting an authorization request for access to the pangenetic data associated with the user;

ii) receiving an authorization which grants access to the pangenetic data;

iii) accessing a data mask, wherein the data mask'"'"'s parameters are associated with the authorization; and

iv) applying the data mask to the pangenetic data.

23. The computer based method of claim 1, further comprising receiving feedback from the user with respect to one or more of the web items represented in the listing.

24. The computer based method of claim 15, wherein the averaging is weighted averaging.

25. A program storage device readable by a machine and containing a set of instructions which, when read by the machine, causes execution of a computer based method for providing internet search results for a user, comprising:

a) receiving non-pangenetic data associated with a user query;

b) accessing pangenetic data associated with the user;

c) accessing a dataset containing pangenetic data and non-pangenetic data correlated with web items;

d) determining for each web item, the quantity of non-pangenetic matches between the non-pangenetic data correlated with that web item and the non-pangenetic data associated with the user query and the quantity of pangenetic matches between the pangenetic data correlated with that web item and the pangenetic data associated with the user; and

e) transmitting as output, based on the quantity of non-pangenetic matches and the quantity of pangenetic matches determined for each web item, a listing of at least a portion of the web items as internet search results for the user.

26. The program storage device of claim 25, wherein the transmitting in step (e) is to at least one destination selected from the group consisting of the user, a database, a dataset, a computer readable memory, a computer readable medium, a computer processor, a computer network, a printout device, a visual display, and a wireless receiver.

27. A computer database system for providing internet search results for a user, comprising:

a) a memory containing;

i) a first data structure containing pangenetic data associated with the user;

ii) a second data structure containing pangenetic data and non-pangenetic data correlated with web items;

b) a processor for;

i) receiving non-pangenetic data associated with a user query;

ii) accessing the first data structure;

iii) accessing the second data structure;

iv) determining for each web item, the quantity of non-pangenetic matches between the non-pangenetic data correlated with that web item and the non-pangenetic data associated with the user query and the quantity of pangenetic matches between the pangenetic data correlated with that web item and the pangenetic data associated with the user; and

v) transmitting as output, based on the quantity of non-pangenetic matches and the quantity of pangenetic matches determined for each web item, a listing of at least a portion of the web items as internet search results for the user.

28. The computer database system of claim 27, wherein the transmitting in part (v) is to at least one destination selected from the group consisting of the user, a database, a dataset, a computer readable memory, a computer readable medium, a computer processor, a computer network, a printout device, a visual display, and a wireless receiver.