PERSONALIZING AN E-BOOK SEARCH QUERY

1 . A method for personalizing an e-Book search query, the method comprising:

receiving an e-Book search query;

searching an e-Book depository based on the query;

obtaining a set of search results from the depository;

obtaining personalized information about a user related to the query;

utilizing the personalized information to refine the set of search results into a set of user personalized e-Book search query results; and

presenting the set of user personalized e-Book search query results on a display of an e-reading device.

2 . The method as recited by claim 1 , wherein comprises:

organizing the set of search results according to a relevancy determination.

3 . The method as recited by claim 2 , wherein the relevancy determination utilizes one or more rules from the group consisting of: a popularity of clicking on a particular result, a level of match between the query and the e-Book, how often results are purchased, how often a preview is viewed or downloaded, and the popularity of an author.

4 . The method as recited by claim 1 , wherein the personalized information about the user related to the query is the personalized information of a user performing the e-Book search query.

5 . The method as recited by claim 1 , wherein the personalized information about the user related to the query is personalized information of someone other than a user performing the e-Book search query.

6 . The method as recited by claim 1 , wherein the personalized information about the user is selected from the group consisting of information about: an e-Book the user has purchased, an e-Book the user has written a review on, an e-Book the user has rated, an e-Book the user has read to completion, and an e-Book recommendation provided to the user.

7 . The method as recited by claim 6 , further comprising:

determining whether the user has already purchased the e-Book from a volume identification.

8 . The method as recited by claim 6 , further comprising:

determining whether the user has already purchased the e-Book from a work identification.

9 . The method as recited by claim 6 , further comprising:

receiving the e-Book recommendation from a personal recommendation system.

10 . A computing device comprising:

a memory that stores a set of instructions, an e-Book having digital content therein and metadata associated with the e-Book;

a processor that accesses the instructions in memory, the processor configured to:

receive an e-Book search query;

search a resource store based on said e-Book search query and obtain a set of search results from the search;

access a user account store comprising personalized information about a user related to the query;

utilize the personalized information to refine the set of search results into a set of user personalized e-Book search query results; and

provide the set of user personalized e-Book search query results on a display of an e-reading device.

11 . The computing device of claim 10 , wherein the search results are organized according to a relevancy determination.

12 . The computing device of claim 11 , wherein the relevancy determination utilizes one or more rules from the group consisting of: a popularity of clicking on a particular result, a level of match between the query and the e-Book, how often results are purchased, how often a preview is viewed or downloaded, and the popularity of an author.

13 . The computing device of claim 10 , wherein the personalized information about the user related to the query is the personalized information of a user performing the e-Book search query.

14 . The computing device of claim 10 , wherein the personalized information about the user related to the query is personalized information of someone other than a user performing the e-Book search query.

15 . The computing device of claim 10 , wherein the personalized information about the user is selected from the group consisting of information about: an e-Book the user has purchased, an e-Book the user has written a review on, an e-Book the user has rated, an e-Book the user has read to completion, and an e-Book recommendation provided to the user.

16 . A non-transitory computer-readable storage medium storing instructions that, when executed by a hardware processor of a computing device, cause the hardware processor to perform a method for personalizing an e-Book search query, the method comprising:

receiving an e-Book search query;

receiving personalized information about a user associated with the query;

searching an e-Book depository based on the query and the personalized information;

obtaining a set of user personalized e-Book search query results from the depository;

sorting the set of user personalized e-Book search query results according to a relevancy determination; and

displaying the sorted set of user personalized e-Book search query results on an e-reading device.

17 . The non-transitory computer-readable storage medium as recited by claim 16 , wherein the relevancy determination utilizes one or more rules from the group consisting of: a popularity of clicking on a particular result, a level of match between the query and the e-Book, how often results are purchased, how often a preview is viewed or downloaded, and the popularity of an author.

18 . The non-transitory computer-readable storage medium as recited by claim 16 , wherein the personalized information about the user related to the query is personalized information of someone other than a user performing the e-Book search query.

19 . The non-transitory computer-readable storage medium as recited by claim 16 , wherein the personalized information about the user is selected from the group consisting of information about: an e-Book the user has purchased, an e-Book the user has written a review on, an e-Book the user has rated, an e-Book the user has read to completion, and an e-Book recommendation provided to the user.

20 . The non-transitory computer-readable storage medium as recited by claim 19 , further comprising:

determining whether the user has already purchased the e-Book from a volume identification; and

determining whether the user has already purchased the e-Book from a work identification.