DETAILED ACTION
This communication is in response to the Amendments and Arguments filed on 12/12/2025.
Claim(s) 1-14 are pending and have been examined. Hence, this action has been made FINAL.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments and Amendments
Amendments to the claims by the Applicant have been considered and addressed below.
With respect to the 35 USC § 102, and 103 rejections, the Applicant provides several arguments in which the Examiner will respond accordingly, below.
Claim Objection(s)
Arguments in page 5 of the Remarks filed on 12/12/2025
Examiner' s Response to Arguments:
Applicant' s arguments with respect to claims 2-10 have been fully considered and are persuasive. The claim objections of claims 2-10 have been withdrawn.
35 USC § 102 and 103 rejection(s)
Arguments in pages 5-7 of the Remarks filed on 12/12/2025
Examiner’s Response to Arguments:
Applicant’s arguments with respect to independent claim(s) 1 and 11 under 35 U.S.C. § 102, and 103 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of:
Winer (US 20140281944 A1) further in view of Best et al. (US 20120197628 A1), for independent claim 1; and
Winer (US 20140281944 A1) further in view of Best et al. (US 20120197628 A1) and Grieves et al. (US 20140267045 A1), for independent claim 11.
For more details, please refer to updated 35 U.S.C. § 103 rejections for claims 1-14, below.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-7, and 9-10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Winer (US 20140281944 A1) further in view of Best et al. (US 20120197628 A1).
As to independent claim 1, Winer teaches:
1. A system for providing suggested text in a digital communication (see ¶ [0002]: “The disclosed implementations relate generally to systems and methods for supplementing existing word correction dictionaries on electronic devices with additional dictionaries.” and ¶ [0005]: “Accordingly, there is a need to provide systems and methods for automatically supplementing on-device dictionaries to provide high quality spell-check and/or word-completion functions without placing undue storage and processing demands on the device.”), comprising:
a mobile device having a user interface with a keyboard and a ribbon (see ¶ [0005] citation as in limitation above and further ¶ [0034 and 0036]: “[0034] The I/O interface 206 couples input/output devices of the client computer 102, such as a display 214, a keyboard 216, a touch screen 218, a microphone 219, and a speaker 220 to the user interface module 226. The I/O interface 206 may also include other input/output components, such as physical buttons (e.g., push buttons, rocker buttons, etc.), dials, slider switches, joysticks, click wheels, and so forth.[…] [0036] The keyboard 216 allows a user to interact with the client computer 102 by inputting characters and controlling operational aspects of the client computer 102. In some implementations, the keyboard 216 is a physical keyboard with a fixed key set. In some implementations, the keyboard 216 is a touchscreen-based, or "virtual" keyboard, such that different key sets (corresponding to different alphabets, character layouts, etc.) may be displayed on the display 214, and input corresponding to selection of individual keys may be sensed by the touchscreen 218.” and ¶ [0063]: “The spell-check module 230 determines whether words that are input by the user are correctly spelled. […] In some implementations, the spell-check module 230 and the word suggestion module 232 operate in conjunction with the user interface module 226 to display misspelled words in a distinctive manner and to provide user interface objects for word suggestions (e.g., lists of suggested words, additional letters following those that are already entered, etc.). For example, in some implementations, the spell-check module 230 identifies, to the user interface module 226, which words are misspelled, and the user interface module 226 causes those words to be displayed in a distinctive manner (e.g., with a red underline). When the word is selected (e.g., by a finger press or mouse click), the user interface module 226 causes a list of selectable alternative spellings provided by the word suggestion module 232 to be displayed to the user (e.g., in a drop down menu or popup window) [i.e., ribbon].”);
a first dictionary, the first dictionary being a standard dictionary (see further ¶ [0005]: “…As described herein, existing on-device dictionaries are supplemented with supplemental dictionaries based on individual users' needs...”); and
a second dictionary, the second dictionary being a primary specialty dictionary (see further ¶ [0005]: “…As described herein, existing on-device dictionaries are supplemented with supplemental dictionaries based on individual users' needs [...] For example, in some implementations, a device determines that a user routinely inputs words relating to a certain subject (e.g., medical terms, legal terms, etc.), and will download, from a remote server, a supplemental dictionary of words related to that subject. Thus, the user receives robust spell-check and/or word suggestion functionality--even for highly specialized parlance--without requiring storage of thousands of arcane words for which they have no need.”);
wherein a suggested text is provided to a user based on a user keyboard input (see ¶ [0008]: “…The method includes receiving an at least partial word input by a user; determining that a use condition of the at least partial word is satisfied; and in response to determining that the use condition is satisfied, obtaining a supplemental word correction dictionary that includes words associated with a same subject matter as the at least partial word, wherein the supplemental word correction dictionary supplements an existing word correction dictionary. In some implementations, the at least partial word is included in a plurality of words input by a user…” and ¶ [0063]: “The spell-check module 230 determines whether words that are input by the user are correctly spelled. […] In some implementations, the spell-check module 230 and the word suggestion module 232 operate in conjunction with the user interface module 226 to display misspelled words in a distinctive manner and to provide user interface objects for word suggestions (e.g., lists of suggested words, additional letters following those that are already entered, etc.). For example, in some implementations, the spell-check module 230 identifies, to the user interface module 226, which words are misspelled, and the user interface module 226 causes those words to be displayed in a distinctive manner (e.g., with a red underline). When the word is selected (e.g., by a finger press or mouse click), the user interface module 226 causes a list of selectable alternative spellings provided by the word suggestion module 232 to be displayed to the user (e.g., in a drop down menu or popup window) [i.e., ribbon].”),
the suggested text being at least one of a corrective suggestion or a predictive suggestion (see ¶ [0002, 0005, 0008, 0034, 0036, and 0063] citations as in limitations above and further ¶ [0005]: “…provide high quality spell-check [i.e., corrective suggestion] and/or word-completion [i.e., predictive suggestion] functions…” and ¶ [0063]: “The spell-check module 230 determines whether words that are input by the user are correctly spelled. […] In some implementations, the spell-check module 230 and the word suggestion module 232 operate in conjunction with the user interface module 226 to display misspelled words in a distinctive manner and to provide user interface objects for word suggestions (e.g., lists of suggested words, additional letters following those that are already entered, etc.));
wherein the suggested text is provided in the ribbon (see ¶ [0063] citation as in limitation(s) above, more specifically: “…the user interface module 226 causes a list of selectable alternative spellings provided by the word suggestion module 232 to be displayed to the user (e.g., in a drop down menu or popup window) [i.e., ribbon].”);
However, Winer does not explicitly teach, but Best et al. does teach:
wherein at least one of the corrective suggestion or the predictive suggestion is a word provided from the second dictionary in each and every instance (see ¶ [0016 and 0021]: “[0016] … Further, for each suggested word in the prompt 150, a dictionary 130B in a secondary language can be consulted to include in the prompt 150 a foreign language equivalent for each suggestion. [0021] In even yet further illustration of the operation of the multi-lingual spell checker, FIG. 3 is a flow chart illustrating a process for multi-lingual spell checking of a block of text. Beginning in block 310, a spell check directive can be received for text in a text block of a source language. In block 320, the text can be spell checked in connection with a dictionary of the source language. In decision block 330, if the text is not misspelled, the process can end in block 340. Otherwise, in block 350, suggested correct spellings of the word can be determined from the dictionary of the source language. Further, in block 360 each suggested correctly spelled word in the source language can be translated into a secondary language by reference to a dictionary of the secondary language. Finally, in block 370 the suggested each correctly spelled word and its secondary language translation can be displayed.).
Winer and Best et al. are considered to be analogous to the claimed invention because they are in the same field of endeavor in text processing/prediction. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Winer to incorporate the teachings of Best et al. of wherein at least one of the corrective suggestion or the predictive suggestion is a word provided from the second dictionary in each and every instance which provides the benefit of suggesting correct text ([abstract] of Best et al.).
Regarding claim 2, Winer in combination with Best et al. teach the limitations as in claim 1, above.
Winer further teaches:
2. The system for providing suggested text in a digital communication of claim 1, wherein the digital communication is an email (see ¶ [0043-0061]: “Applications 228 may include programs and/or modules that are configured to be executed by the client computer 102. In some implementations, the applications include the following modules (or sets of instructions), or a subset or superset thereof: [0044] contacts module (sometimes called an address book or contact list); [0045] telephone module; [0046] video conferencing module; [0047] e-mail client module; [0048] instant messaging (IM) module; [0049] text messaging module; [0050] workout support module; [0051] camera module for still and/or video images; [0052] image management module; [0053] browser module; [0054] calendar module; [0055] widget modules, which may include one or more of: weather widget, stocks widget, calculator widget, alarm clock widget, dictionary widget, and other widgets obtained by the user, as well as user-created widgets; [0056] widget creator module for making user-created widgets; [0057] search module; [0058] media player module, which may be made up of a video player module and a music player module; [0059] notes module; [0060] map module; and/or [0061] online video module.” and ¶ [0062]: “Examples of other applications 228 that may be stored in memory 202 include word processing applications, image editing applications, drawing applications, presentation applications, JAVA-enabled applications, encryption, digital rights management, voice recognition, and voice replication applications. In some implementations, these applications (and/or other applications not listed) work together with the spell-check module 230 and the word suggestion module 232 (described below) to provide spell check and/or word selection functions for text that is input into the applications.”).
Regarding claim 3, Winer in combination with Best et al. teach the limitations as in claim 1, above.
Winer further teaches:
3. The system for providing suggested text in a digital communication of claim 1, wherein the digital communication is a text message (see ¶ [0043-0062] citations as in claim 2, above. “text messaging module”).
Regarding claim 4, Winer in combination with Best et al. teach the limitations as in claim 1, above.
Winer further teaches:
4. The system for providing suggested text in a digital communication of claim 1, wherein the digital communication is a direct message (see ¶ [0043-0062] citations as in claim 2, above. “instant messaging (IM) module”).
Regarding claim 5, Winer in combination with Best et al. teach the limitations as in claim 1, above.
Winer further teaches:
5. The system for providing suggested text in a digital communication of claim 1, wherein the digital communication is a note to a record (see ¶ [0043-0062] citations as in claim 2, above. “notes module”).
Regarding claim 6, Winer in combination with Best et al. teach the limitations as in claim 1, above.
Winer further teaches:
6. The system for providing suggested text in a digital communication of claim 1, wherein the suggested text includes more than one corrective suggestion (see ¶ [0063]: “ … For example, in some implementations, the spell-check module 230 identifies, to the user interface module 226, which words are misspelled, and the user interface module 226 causes those words to be displayed in a distinctive manner (e.g., with a red underline). When the word is selected (e.g., by a finger press or mouse click), the user interface module 226 causes a list of selectable alternative spellings provided by the word suggestion module 232 to be displayed to the user (e.g., in a drop down menu or popup window).”).
Regarding claim 7, Winer in combination with Best et al. teach the limitations as in claim 1, above.
Winer further teaches:
7. The system for providing suggested text in a digital communication of claim 1, wherein the suggested text includes more than one predictive suggestion (see ¶ [0063]: “… In some implementations, the spell-check module 230 and the word suggestion module 232 operate in conjunction with the user interface module 226 to display misspelled words in a distinctive manner and to provide user interface objects for word suggestions (e.g., lists of suggested words, additional letters following those that are already entered, etc.)...”).
Regarding claim 9, Winer in combination with Best et al. teach the limitations as in claim 1, above.
Winer further teaches:
9. The system for providing suggested text in a digital communication of claim 1, wherein the corrective suggestion is provided after the system determines that the user input does not match a single entry in the second dictionary (see ¶ [0063 and 0065]: “[0063] The spell-check module 230 determines whether words that are input by the user are correctly spelled. In some implementations, the spell-check module 230 compares each word entered by the user against the words in the dictionaries 234 to determine whether a match exists. If no match exists for a respective word, the user is alerted that the word may be misspelled. For example, the word may be highlighted (e.g., in yellow), underlined, or otherwise displayed in a distinctive manner. In some implementations, if no match exists, the user is alerted during a spell-check operation, where the user is sequentially alerted to all of the misspelled words in a document or text input. In some implementations, the spell-check module 230 operates in conjunction with the word suggestion module 232 to provide alternative spellings for a misspelled word… [0065] The dictionaries 234 include an initial dictionary 236 and supplemental dictionaries 238-n... ”).
Regarding claim 10, Winer in combination with Best et al. teach the limitations as in claim 1, above.
Winer further teaches:
10. The system for providing suggested text in a digital communication of claim 1, wherein the predictive suggestion is provided after the system determines that the user input matches one or more entries in the second dictionary (see ¶ [0063 and 0065] citations as in claim 1 and 9, above and further ¶ [0006-0007]: “[0006] Providing supplemental dictionaries specific to a user's needs helps eliminate several inconveniences associated with traditional spell check and word-completion technologies. First, it prevents false positive errors, such as when correctly spelled words are marked as incorrect or are automatically replaced with other, incorrect words. False positives can be bothersome, as a user's text input can become riddled with nuisance underlines or highlights that are typical of spell checkers. In addition to simply looking unattractive, these make it difficult for a user to spot those words that are actually misspelled as opposed to those that are correctly spelled but are not found in the dictionary. Moreover, providing supplemental dictionaries helps prevent correctly spelled but out-of-dictionary words from being replaced with correctly spelled but incorrect words by an autocorrect feature. For example, autocorrect may convert the correctly spelled phrase "ex parte reexamination" to the nonsensical (though correctly spelled) "ex parts prefabrication." By providing supplemental dictionaries (for legal terms, in this example), such mistakes can be avoided. [0007] Second, by providing supplemental dictionaries, the device will actually identify misspellings of the user's specialized vernacular, and provide corrected spellings of those words (e.g., as part of a spell check or an autocorrect function). Thus, if a user enters the phrase "ex partr rexanimation," the device will offer the correct spelling of the misspelled words ("parte reexamination"), rather than offering no suggestions or only incorrect suggestions (e.g., "parts" and "reanimation").”).
Claim 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Winer (US 20140281944 A1) further in view of Best et al. (US 20120197628 A1) as applied to claim 1, above and further in view of Choi et al. (US 20170308292 A1).
Regarding claim 8, Winer in combination with Best et al. teach the limitations as in claim 1, above.
However, Winer does not explicitly teach, but Choi et al. does teach:
8. The system for providing suggested text in a digital communication of claim 1, wherein the suggested text includes at least one corrective suggestion and at least one predictive suggestion (see Fig. 4B (418: “tonight”, 404: emoji, 406: “Restaurants near me”) and ¶ [0037]: “For example, keyboard module 122 may configure suggestion region 118B to present suggested content (e.g., predicted search queries, predicted emoticons or so called “emojis”, other suggested content, or other iconography symbols) [i.e., associated with a secondary dictionary/list (e.g., emoticons/emojis/iconography symbols)] as selectable elements within search suggestion region 118B instead of predicted characters, words or phrases or other primarily linguistic information that keyboard module 122 derives from a language model, lexicon, or dictionary. In other words, rather than providing spelling or word suggestions from a dictionary within suggestion region 118B, computing device 110 may include, within suggestion region 118B, suggested search related content that computing device 110 determines may assist a user in providing input related to electronic communications.” and ¶ [0043]: “The keyboard module 122 may determine suggested queries based on the information about user input received from the UI module 120, but the suggested queries may also be determined based on an application the user is interacting with, the context of the user's activity, or some combination thereof. The keyboard module 122 may also determine the suggested queries based on historical information about the user. For example, in some examples, search query suggestions may come from chat conversations on computing device 110. The text message “do you want to get dinner?” may suggest a “Restaurants near me” query; the text message “did you watch the basketball game?” may suggest a “Team Name” query of a professional basketball team. In accordance with one or more aspects of the present disclosure, when computing device 110 may be displaying suggested search queries, the graphical keyboard 116B in FIG. 1 may be considered to be in search mode or suggest mode.”).
Winer and Choi et al. are considered to be analogous to the claimed invention because they are in the same field of endeavor in text processing/prediction. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Winer to incorporate the teachings of Choi et al. of wherein the suggested text includes at least one corrective suggestion and at least one predictive suggestion which provides the benefit of receiving fewer inputs, the computing device may process fewer user inputs, execute fewer operations, and as a result, consume less electrical power ([0046] of Choi et al.).
Claims 11-14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Winer (US 20140281944 A1) further in view of Best et al. (US 20120197628 A1) and Grieves et al. (US 20140267045 A1).
As to independent claim 11, Winer teaches:
11. A method for providing a suggested text in a digital communication (see ¶ [0002]: “The disclosed implementations relate generally to systems and methods for supplementing existing word correction dictionaries on electronic devices with additional dictionaries.” and ¶ [0005]: “Accordingly, there is a need to provide systems and methods for automatically supplementing on-device dictionaries to provide high quality spell-check and/or word-completion functions without placing undue storage and processing demands on the device.”), comprising:
receiving user input on a mobile device through use of a keyboard on a user interface (see ¶ [0005] citation as in limitation above and further ¶ [0034 and 0036]: “[0034] The I/O interface 206 couples input/output devices of the client computer 102, such as a display 214, a keyboard 216, a touch screen 218, a microphone 219, and a speaker 220 to the user interface module 226. The I/O interface 206 may also include other input/output components, such as physical buttons (e.g., push buttons, rocker buttons, etc.), dials, slider switches, joysticks, click wheels, and so forth.[…] [0036] The keyboard 216 allows a user to interact with the client computer 102 by inputting characters and controlling operational aspects of the client computer 102…”);
comparing the user input to the words in a first dictionary (see further ¶ [0005]: “…As described herein, existing on-device dictionaries are supplemented with supplemental dictionaries based on individual users' needs...” and ¶ [0063]: “The spell-check module 230 determines whether words that are input by the user are correctly spelled. In some implementations, the spell-check module 230 compares each word entered by the user against the words in the dictionaries 234 to determine whether a match exists…”),
the first dictionary being a standard dictionary (see ¶ [0005 and 0063] citations as in limitation above: “on-device dictionaries” or “initial dictionary” associated with spell-check);
comparing the user input to the words in a second dictionary (¶ [0064]: “The word suggestion module 232 determines alternative spellings (e.g., words that the user likely intended to enter) for user-entered words or text sequences that do not appear in the dictionaries 234. For example, in some implementations, when the spell-check module 230 determines that a user-entered word does not appear in the dictionaries 234, the word suggestion module 232 identifies one or more words from the dictionaries 234 that are similar to the misspelled word…” and ¶ [0065]: “The dictionaries 234 include an initial dictionary 236 and supplemental dictionaries 238-n. The dictionaries 234 include lists of words, and are accessible to and/or used by the spell-check module 230 and the word suggestion module 232 (and/or any other programs or modules of the client computer 102). In some implementations, the dictionaries 234 include additional information, such as pronunciation guides (human and/or machine readable), subject matter identifiers, definitions, part-of-speech information, common misspellings, usage statistics, etc. In some implementations, the supplemental dictionaries 238-n relate to particular subjects. For example, supplemental dictionaries may be dictionaries of words related to legal terms, medical terms, sports terms (including, for example, team names, player rosters, etc.), music terms (including, for example, band names, artist names, song/album names, etc.), scientific terms, computer terms, and the like. Of course, dictionaries for other subjects (and sub-categories and super-categories of the listed subjects) may be provided as well. For example, there may be numerous different supplemental dictionaries for sports terms, such as dictionaries for specific sports (e.g., including team names and player rosters for all professional and college football teams), dictionaries for sports associated with a particular region (e.g., including team names and player rosters for all California professional sports teams), etc. In some implementations, the supplemental dictionaries 238-n include words from different languages (e.g., Latin words may commonly appear in Medical and Legal supplemental dictionaries).”
[i.e., supplemental dictionaries associated with the second dictionary (i.e., specialty dictionary)]),
the second dictionary being a primary specialty dictionary (see ¶ [0064-0065] citations as in limitation above: “supplemental dictionaries”);
providing the suggested text in a ribbon on the user interface (see ¶ [0063] citation as in limitation(s) above, more specifically: “…the user interface module 226 causes a list of selectable alternative spellings provided by the word suggestion module 232 to be displayed to the user (e.g., in a drop down menu or popup window) [i.e., ribbon].”),
However, Winer does not explicitly teach, but Best et al. does teach:
the suggested text being at least one of a predictive suggestion or corrective suggestion in each and every instance (see ¶ [0016 and 0021]: “[0016] … Further, for each suggested word in the prompt 150, a dictionary 130B in a secondary language can be consulted to include in the prompt 150 a foreign language equivalent for each suggestion. [0021] In even yet further illustration of the operation of the multi-lingual spell checker, FIG. 3 is a flow chart illustrating a process for multi-lingual spell checking of a block of text. Beginning in block 310, a spell check directive can be received for text in a text block of a source language. In block 320, the text can be spell checked in connection with a dictionary of the source language. In decision block 330, if the text is not misspelled, the process can end in block 340. Otherwise, in block 350, suggested correct spellings of the word can be determined from the dictionary of the source language. Further, in block 360 each suggested correctly spelled word in the source language can be translated into a secondary language by reference to a dictionary of the secondary language. Finally, in block 370 the suggested each correctly spelled word and its secondary language translation can be displayed.).
Winer and Best et al. are considered to be analogous to the claimed invention because they are in the same field of endeavor in text processing/prediction. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Winer to incorporate the teachings of Best et al. of wherein at least one of the corrective suggestion or the predictive suggestion is a word provided from the second dictionary in each and every instance which provides the benefit of suggesting correct text ([abstract] of Best et al.).
However, Winer in combination with Best et al. do not explicitly teach, but Grieves et al. does teach:
creating a weighted scoring of the words in at least the second dictionary based on at least one pre-determined criteria (see ¶ [0013 and 0057-0058]: “[0013] FIG. 7 depicts an example procedure in which text prediction candidates are selected using a weighted combination of scoring data from multiple dictionaries in accordance with one or more implementations. [0057] FIG. 7 depicts a procedure 700 in which text prediction candidates are selected using a weighted combination of scoring data from multiple dictionaries in accordance with one or more implementations. Multiple dictionaries are identified to use as sources of words for prediction of text based on one or more detected text characters (block 702). For example, dictionaries to apply for a given interaction may be selected according to an adaptive language model 128 as previously described. For instance, the text prediction engine 122 may identify dictionaries according to one or more usage parameters that match detected text characters. If available, user-specific and/or interaction specific dictionaries may be identified and used by the text prediction engine 122 as components in generating text predictions. If not, then the text prediction engine 122 may default to using the general population dictionary 402 by itself. [0058] Words are ranked one to another as prediction candidates for the detected text characters using a weighted combination of scoring data associated with words contained in the multiple dictionaries (block 704). One or more top ranking words are selected according to the ranking as prediction candidates for the detected text characters (Block 706). The ranking and selection of candidates may occur in various ways. Generally, scores for ranking prediction candidates may be computed by combining contributions from multiple dictionaries. For example, the text prediction engine 122 and adaptive language model 128 may be configured to implement a ranking or scoring algorithm that computes a weighted combination of scoring data. The weighted combination may be designed to interpolate predictions from a general population dictionary and at least one other dictionary. The other dictionary may be a personalized dictionary, an interaction-specific dictionary, or even another general population dictionary for a different language.”);
Winer, Best et al. and Grieves et al. are considered to be analogous to the claimed invention because they are in the same field of endeavor in text processing/prediction. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Winer in combination with Best et al. to incorporate the teachings of Grieves et al. of creating a weighted scoring of the words in at least the second dictionary based on at least one pre-determined criteria which provides the benefit of facilitating text entry ([0070] of Grieves et al.).
Regarding claim 12, Winer in combination with Best and Grieves et al. teach the limitations as in claim 11, above.
Winer further teaches:
12. The method of claim 11 wherein the corrective suggestion is provided at times when the user input matches fewer than two entries in the second dictionary (see ¶ [0063 and 0065]: “[0063] The spell-check module 230 determines whether words that are input by the user are correctly spelled. In some implementations, the spell-check module 230 compares each word entered by the user against the words in the dictionaries 234 to determine whether a match exists. If no match exists for a respective word, the user is alerted that the word may be misspelled. For example, the word may be highlighted (e.g., in yellow), underlined, or otherwise displayed in a distinctive manner. In some implementations, if no match exists, the user is alerted during a spell-check operation, where the user is sequentially alerted to all of the misspelled words in a document or text input. In some implementations, the spell-check module 230 operates in conjunction with the word suggestion module 232 to provide alternative spellings for a misspelled word… [0065] The dictionaries 234 include an initial dictionary 236 and supplemental dictionaries 238-n... ”
Here, the Examiner notes that “user input matches fewer than two entries…” (i.e., one or zero matches) is similar to language in claim 9 of “user input does not match a single entry…” (i.e., zero matches).).
Regarding claim 13, Winer in combination with Best and Grieves et al. teach the limitations as in claim 11, above.
Winer further teaches:
13. The method of claim 11, wherein the predictive suggestion is provided at times when the user input matches more than one entry in the second dictionary (see ¶ [0063 and 0065] citations as in claims 1 and 12, above and further ¶ [0006-0007]: “[0006] Providing supplemental dictionaries specific to a user's needs helps eliminate several inconveniences associated with traditional spell check and word-completion technologies. First, it prevents false positive errors, such as when correctly spelled words are marked as incorrect or are automatically replaced with other, incorrect words. False positives can be bothersome, as a user's text input can become riddled with nuisance underlines or highlights that are typical of spell checkers. In addition to simply looking unattractive, these make it difficult for a user to spot those words that are actually misspelled as opposed to those that are correctly spelled but are not found in the dictionary. Moreover, providing supplemental dictionaries helps prevent correctly spelled but out-of-dictionary words from being replaced with correctly spelled but incorrect words by an autocorrect feature. For example, autocorrect may convert the correctly spelled phrase "ex parte reexamination" to the nonsensical (though correctly spelled) "ex parts prefabrication." By providing supplemental dictionaries (for legal terms, in this example), such mistakes can be avoided. [0007] Second, by providing supplemental dictionaries, the device will actually identify misspellings of the user's specialized vernacular, and provide corrected spellings of those words (e.g., as part of a spell check or an autocorrect function). Thus, if a user enters the phrase "ex partr rexanimation," the device will offer the correct spelling of the misspelled words ("parte reexamination"), rather than offering no suggestions or only incorrect suggestions (e.g., "parts" and "reanimation").”
Here, the Examiner notes that “user input matches more than one entry…” (i.e., one or two matches) is similar to language in claim 10 of “user input matches one or more entries…” (i.e., one or two matches). For example, "ex partr rexanimation" user input (i.e., 2 words misspelled) being suggested "parte reexamination" (i.e., 2 words matching in legal dictionary).).
Regarding claim 14, Winer in combination with Best and Grieves et al. teach the limitations as in claim 11, above.
Winer further teaches:
14. The method of claim 11, wherein more than one predictive suggestion is provided, and at least one of the predictive suggestions is provided from the first dictionary (see ¶ [0007-0008, 0063 and 0065] citations as in claims 1 and 12-13 above, and further ¶ [0063]: “The spell-check module 230 determines whether words that are input by the user are correctly spelled. In some implementations, the spell-check module 230 compares each word entered by the user against the words in the dictionaries 234 to determine whether a match exists…”, ¶ [0064]: “The word suggestion module 232 determines alternative spellings (e.g., words that the user likely intended to enter) for user-entered words or text sequences that do not appear in the dictionaries 234. For example, in some implementations, when the spell-check module 230 determines that a user-entered word does not appear in the dictionaries 234, the word suggestion module 232 identifies one or more words from the dictionaries 234 that are similar to the misspelled word…” and ¶ [0065]: “The dictionaries 234 include an initial dictionary 236 and supplemental dictionaries 238-n.
[i.e., spell-check associated dictionaries are associated with the first dictionary (i.e., initial dictionary)]), and at least one of the predictive suggestions is provided from the second dictionary (see ¶ [0007-0008, 0063-0065] citations as in claims 1 and 12-13 and limitation above, and further ¶ [0065]: “The dictionaries 234 include an initial dictionary 236 and supplemental dictionaries 238-n. The dictionaries 234 include lists of words, and are accessible to and/or used by the spell-check module 230 and the word suggestion module 232 (and/or any other programs or modules of the client computer 102). In some implementations, the dictionaries 234 include additional information, such as pronunciation guides (human and/or machine readable), subject matter identifiers, definitions, part-of-speech information, common misspellings, usage statistics, etc. In some implementations, the supplemental dictionaries 238-n relate to particular subjects. For example, supplemental dictionaries may be dictionaries of words related to legal terms, medical terms, sports terms (including, for example, team names, player rosters, etc.), music terms (including, for example, band names, artist names, song/album names, etc.), scientific terms, computer terms, and the like. Of course, dictionaries for other subjects (and sub-categories and super-categories of the listed subjects) may be provided as well. For example, there may be numerous different supplemental dictionaries for sports terms, such as dictionaries for specific sports (e.g., including team names and player rosters for all professional and college football teams), dictionaries for sports associated with a particular region (e.g., including team names and player rosters for all California professional sports teams), etc. In some implementations, the supplemental dictionaries 238-n include words from different languages (e.g., Latin words may commonly appear in Medical and Legal supplemental dictionaries).”
[i.e., supplemental dictionaries associated with the second dictionary (i.e., specialty dictionary)]).
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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Keisha Y. Castillo-Torres
Examiner
Art Unit 2659
/Keisha Y. Castillo-Torres/Examiner, Art Unit 2659
/PIERRE LOUIS DESIR/Supervisory Patent Examiner, Art Unit 2659