System and method for enhanced lookup in an online dictionary

• US 9,235,566 B2
• Filed: 03/30/2011
• Issued: 01/12/2016
• Est. Priority Date: 03/30/2011
• Status: Active Grant

• Current Assignee: Thinkmap Incorporated
• Original Assignee: Thinkmap Incorporated
• Inventors: Tinkler, Marc
• Primary Examiner(s): TAN, ALVIN H
• Application Number:
  US13/076,105
• Publication Number:
  US 20120254802A1
• Time in Patent Office: 1,749 Days
• Field of Search: 715/816
• US Class Current: 1/1
• CPC Class Codes: G06F 16/322 Trees
• CPC Class Codes: G06F 16/3322 using system suggestions G06F16/3325 takes precedence
• CPC Class Codes: G06F 16/36 Creation of semantic tools, e.g. ontology or thesauri
• CPC Class Codes: G06F 40/242 Dictionaries

Abstract

A system and method predictively generates words based on a user input, according to a frequency of lookup of each of the generated words. The system and method also allows for a user to add predictively generated words to a word list that assists in the facilitation of word and vocabulary comprehension for a user. Words in the online dictionary are grouped in word families where a user can navigate between different forms of a root word.

Claims

1. A computer-implemented method for predictively looking up words in an online dictionary, the method comprising:

executing, by a computer processor, a module that instructs the processor to respond to each new user input of a text string into a predetermined field by generating and outputting a respective initial presentation of a list of words that each contains the text string, the list of words including a first section and a second section;

filtering the list of words according to at least a partial definition that is user-selected; and

responsive to a user-input scroll instruction, dynamically updating the list of words to display different words of the list;

wherein;

the first section includes words arranged in descending order of frequency of lookup in the online dictionary;

the second section is reserved for inclusion of words based on alphabetical proximity;

the second section is displayed immediately below the first section; and

the module instructs that, for each of the initial presentations of the list, the first section includes more than one word and the second section includes only one word that is alphabetically closest to the text string.

2. The method of claim 1, further comprising:

responsive to selection of a word from the scrollable list, updating a frequency of lookup for the selected word.

3. The method of claim 1, further comprising:

filtering the list of words according to user-selected attributes, including at least one of;

part of speech, synonym, antonym, number of syllables, rhyme, prefix, at least a partial definition, hyponym, example, and meronym.

4. The method of claim 1, further comprising:

displaying, for a most frequently looked up one of displayed words of the scrollable list, a plurality of sentences including the most frequently looked up one of the displayed words, the plurality of sentences being obtained from a plurality of media sources, and being displayed in reverse chronological order with respect to a time at which the sentences are obtained.

5. The method of claim 1, further comprising:

displaying, for a most frequently looked up one of displayed words of the scrollable list, a plurality of sentences including the most frequently looked up one of the displayed words, the plurality of sentences being obtained from a plurality of media sources, and being displayed in reverse chronological order with respect to at least one of a date and a time associated by the media sources with the sentences.

6. The method of claim 5, wherein the sentences obtained from the media sources are included in dated articles of the media sources, the chronological order being based on the dates of the articles.

7. The method of claim 5, wherein the plurality of media sources is user-selectable and are included in accordance with respective categorizations of the sources as at least one of:

news, medicine, science, business, arts, culture, sports, fiction, and technology.

8. The method of claim 1, further comprising:

subsequent to the outputting of the scrollable list of words, receiving a character appended to the text string, forming an updated text string;

responsive to the receipt of the appended character, dynamically updating the scrollable list to include words that contain the updated text string.

9. The method of claim 1, further comprising:

displaying a hierarchical representation of a word family of a displayed word of the scrollable list for which a greatest look up frequency, compared to all other displayed words of the scrollable list, is recorded.

10. The method of claim 9, wherein the hierarchical representation includes a plurality of bars, one of the bars including a portion representing the displayed word for which the greatest look up frequency is selected, and each of the remaining bars including an ancestor word of the displayed word for which the greatest look up frequency is recorded, each of the ancestor words including a core text string from which the displayed word for which the greatest look up frequency is recorded, is formed.

11. The method of claim 1, further comprising responsive to a user-input add instruction, adding a word from the scrollable list of words to a word list.

12. The method of claim 1, wherein:

at least a portion of the list remains displayed regardless of an extent of the user-input scroll instruction; and

responsive to the user-input scroll instruction while the initial presentation is displayed, at least one word of the list is replaced by at least one other word of the list.

13. A computer-implemented method for predictively looking up words in an online dictionary, the method comprising:

executing, by a computer processor, a module that instructs the processor to respond to each new user input of a text string into a predetermined field by generating and outputting a respective initial presentation of a list of words, wherein;

the list includes a first section and a second section;

each of the words of the first section is included in the list based on at least a partial definition that is user-selected and at least one of (a) the respective word being a user-selected part of speech and (b) the text string being at least one of;

an antonym of the respective word, a hyponym of the respective word, an example of the respective word, and a meronym of the respective word;

each of the words of the second section is included in the list based on alphabetical proximity to the input text string; and

the module instructs that, for each of the initial presentations of the list, the first section includes more than one word and the second section includes only one word that is alphabetically closest to the text string.

14. The method of claim 13, wherein the words of the first section are arranged in descending order of frequency of lookup in the online dictionary.

15. The method of claim 13, wherein the respective word is included in the list based on the respective word being a user-selected part of speech.

16. The method of claim 13, wherein the respective word is included in the list based on the text string being an antonym of the respective word.

17. The method of claim 13, wherein the respective word is included in the list based on the text string being a hyponym of the respective word.

18. The method of claim 13, wherein the respective word is included in the list based on the text string being an example of the respective word.

19. The method of claim 13, wherein the respective word is included in the list based on the text string being a meronym of the respective word.

20. A computer-implemented method for predictively looking up words in an online dictionary, the method comprising:

executing, by a computer processor, a module that instructs the processor to respond to each new user input of a text string into a predetermined field by generating and outputting a respective initial presentation of a list of words that each contains the text string, the list of words including a first section and a second section;

filtering the list of words according to at least a partial definition that is user-selected; and

responsive to a user-input scroll instruction, dynamically updating the list of words to display different words of the list;

wherein;

the first section includes words arranged in descending order of frequency of lookup in the online dictionary;

the second section is reserved for inclusion of words with a closest alphabetical proximity to the text string;

the second section is displayed immediately below the first section; and

the module instructs that, for each of the initial presentations of the list, the first section includes more words than the second section.

21. The method of claim 20, wherein:

at least a portion of the second section remains displayed regardless of an extent of the user-input scroll instruction; and

responsive to the user-input scroll instruction while the initial presentation is displayed, at least one word of the first section is replaced by at least one of the additional words included in the list based on the descending order of frequency of lookup in the online dictionary.