Selective Display of Comprehension Guides

• US 20150310002A1
• Filed: 04/25/2014
• Published: 10/29/2015
• Est. Priority Date: 04/25/2014
• Status: Active Grant

• Current Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Original Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Inventors: King, Joseph, Yu, Wainwright Gregory Siady, Chuah, Joon Hao, Hullender, Gregory Nicholas, Poulin, James Joseph, Kanso, Mohammed, Natarajan, Manigandan, Watson, Brandon LaBranche, Roth, Robert Wayne
• Granted Patent: US 9,524,298 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/335 Filtering based on additional data, e.g. user or group profiles filtering in web context G06F16/9535, G06F16/9536
• CPC Class Codes: G06F 16/93 Document management systems
• CPC Class Codes: G06F 40/10 Text processing natural language analysis G06F40/20; semantic analysis G06F40/30; processing or translation of natural language G06F40/40
• CPC Class Codes: G06F 40/169 Annotation, e.g. comment data or footnotes
• CPC Class Codes: G06F 40/237 Lexical tools
• CPC Class Codes: G06F 40/242 Dictionaries
• CPC Class Codes: G06F 40/284 Lexical analysis, e.g. tokenisation or collocates
• CPC Class Codes: G06F 40/30 Semantic analysis
• CPC Class Codes: G09B 19/00 Teaching not covered by other main groups of this subclass teaching or practice apparatus for gun-aiming or gun-laying F41G3/26
• CPC Class Codes: G09B 5/02 with visual presentation of the material to be studied, e.g. using film strip

Abstract

Techniques are provided for selectively and dynamically determining one or more words of an electronic book to present with comprehension guides. For instance, an electronic device rendering an electronic book may determine whether to display some, all, or no words of the book with comprehension guides for words within the electronic book based on word difficulty, contextual importance or aspects of the user. Techniques are also provided for determining the content of comprehension guides to be presented with the words.

Claims

1. An system comprising:

one or more processors; and

memory, storing instructions that, when executed on the one or more processors, cause the one or more processors to perform acts comprising;

determining a score for a word of a plurality of words included in an electronic book, the score indicative of how difficult the word is for a particular user, wherein the determining the score is based at least in part on;

a frequency of occurrence of the word in a general corpus of writings of a first language, wherein the score is higher the lower the frequency of occurrence;

a contextual importance of the word within at least one of the electronic book or a subject matter area associated with the electronic book, wherein the score is higher the lower the contextual importance;

user information about the particular user that includes the user'"'"'s lookup history of definitions of words, wherein the score is lower if the word is included in the lookup history of the user; and

feedback from the particular user indicative of a level of familiarity of the user with a meaning of the word, wherein the score is lower when the feedback is indicative of familiarity with the meaning of the word; and

ranking the word among the plurality of words based at least in part on the score.

2. A system as recited in claim 1, wherein the contextual importance of the word is based at least in part on the frequency of occurrence of the word in a corpus of writings in the subject matter area of the electronic book, the contextual importance of the word being higher for a higher frequency of occurrence of the word in the corpus of writings in the subject matter area of the electronic.

3. A system as recited in claim 1, wherein:

the word is a compound word or idiom comprising a plurality of terms, the compound word or idiom having a meaning that is different from the literal meaning of the plurality of terms; and

the determining the score of the word comprises determining a score for the compound word or idiom based at least in part on a frequency of occurrence of the compound word in a corpus of writings.

4. A system as recited in claim 1, wherein the word is of a first language and the determining the score is further based at least in part on a relation of the first language to a second language that is the native language of the particular user, the relation of the first language to the second language indicating whether there is a similarity of the word in the first language to a translation of the word in the second language, the determining the score determining a higher score if there is the similarity between the word in the first language to a translation of the word in the second language.

5. A method comprising:

under control of an electronic device that is configured with executable instructions,

determining a difficulty value of a word of a plurality of words based at least in part on a frequency of occurrence of the word in a corpus of writings; and

determining a contextual importance of the word based at least in part on a subject matter area; and

calculating the score for the word at least from the determined difficulty value and the determined contextual importance value.

6. A method as recited in claim 5, further comprising:

calculating a score for each of the plurality of words; and

ranking each of the plurality of words based at least in part on respective scores

7. A method as recited in claim 5, wherein the determining the determined contextual importance of the word is based at least in part on a frequency with which the word occurs in a corpus of writings related to the subject matter area.

8. A method as recited in claim 5, wherein the calculating is further based at least in part on whether the word has multiple meanings in a first language.

9. A method as recited in claim 5, the calculating is further based at least in part on information received from or derived for one or more users.

10. A method as recited in claim 9, wherein the information received from or derived for the one or more users comprises receiving feedback from a user indicative of the user being unfamiliar with a meaning of the word.

11. A method as recited in claim 9, wherein the calculating further comprises determining that the one or more users are users that are similar to a particular other user.

12. A method as recited in claim 11, wherein the information received from or derived for one or more users comprises feedback from a user of the one or more users indicative of a prior score of the word being inaccurate.

13. A method as recited in claim 9, wherein the information received from or derived for one or more users is based at least in part on one or more lookup requests for a definition of the word from the one or more users.

14. One or more computer-readable media storing computer-executable instructions that, when executed on one or more processors, cause the one or more processors to perform acts comprising:

determining a score for a word of a plurality of words of an electronic book, wherein the determining is based at least in part on;

a difficulty value of the word based at least in part on a frequency of occurrence of the word in a corpus of writings; and

a contextual importance of the word within the electronic book.

15. One or more computer-readable media as recited in claim 14, the acts further comprising:

determining a score for each the plurality of words; and

ranking each of the plurality of words based at least in part on respective scores

16. One or more computer-readable media as recited in claim 14, wherein the contextual importance of the word is based at least in part on a frequency with which the word occurs in the electronic book.

17. One or more computer-readable media as recited in claim 14, the determining is further based at least in part on information received from or derived for one or more users comprising feedback from a user indicative of the user being unfamiliar with a meaning of the word and one or more lookup requests for a definition of the word from the one or more users.

18. One or more computer-readable media as recited in claim 14, wherein the determining the score is further based at least in part on a relationship of a first language to a second language that is the native language of a reader, the word being a word of the first language.

19. One or more computer-readable media as recited in claim 14, the acts further comprising determining a measure of occurrences of the word in books previously read by the user and wherein the determining the score is further based on the measure of occurrences of the word.

20. One or more computer-readable media as recited in claim 14, wherein the determining the score of a word is based at least in part on the word having two or more meanings in a first language that are present in the electronic book.