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 .
DETAILED ACTION
Claims 1-23 are present in this application. Claims 1-23 are pending in this office
action.
This office action is NON-FINAL.
Drawings
The Drawings filed on 09/02/25 are acceptable for examination purposes.
Specification
The Specification filed on 09/02/25 is acceptable for examination purposes.
Information Disclosure Statement
The information disclosure statements (IDS) filed on 09/02/25 has been considered by the Examiner and made of record in the application file.
Claim Rejections 35 U.S.C. §103
In the event the determination of the status of the application as subject to AIA 35
U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any
correction of the statutory basis for the rejection will not be considered a new ground of
rejection if the prior art relied upon, and the rationale supporting the rejection, would be
the same under either status.
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.
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:
Claims 1-20 and 22 are rejected under 35 U.S.C. 103 as being unpatentable over OU et al. (US 2016/0026258 A1) in view of WANG et al. (US 2017/0068655 A1).
Regarding claim 1, OU teaches One or more non-transitory, computer-readable storage media storing instructions that, (See OU paragraph [0165], computer-readable storage media, which is non-transitory or (2) a communication medium such as a signal or carrier wave), when executed by one or more hardware processors of a computing device, cause the computing device to perform operations comprising, (See OU paragraph [0005], a computer-readable storage medium is encoded with instructions that, when executed, cause at least one processor to output for display):
receiving an input string, (See OU paragraph [0164], Computing device 294 may receive a subsequent indication of user input to select candidate character string 300);
associating, in a lattice representation, each token with a coordinate set comprising, (See OU paragraph [0043], the token lattice may be a graph that includes vertexes that are connected by edges. Each vertex may be identified by an index),
interpreting at least one token from the plurality of tokens as a relative token, that identifies at least one referenced coordinate set using the coordinate set, (See OU paragraph [0103], determine an out-of-vocabulary candidate character string and model a corresponding candidate character string in the dictionary that is similar to the out-of-vocabulary candidate character string in token lattice 110), associated with the relative token and at least one predefined relative axis offset value associated with the relative token, (See OU paragraph [0045], determine one or more candidate words of a second language (e.g., Chinese) based on the candidate character strings modeled in the token lattice using a second lattice that indicates probabilities of one or more words of the second language based at least in part on the spatial probabilities of the plurality of candidate character strings);
retrieving a value associated with the referenced coordinate set, (See OU paragraph [0086], receives tap inputs, builder module 50 generates additional vertexes 102B, 102C, etc., and generates edges 104A-104D, etc. to the respective vertexes of character lattice 100. Each subsequent tap input may be modeled with a next incremental index value of a vertex);
substituting the retrieved value in place of the relative token in the lattice representation, (See OU paragraph [0086], receives indications of user input, builder module 50 may incrementally build word lattice 120. Builder module 50 may generate an edge that is associated with a single and/or multiple candidate character strings. That is, candidate character strings modeled on edges of token lattice 110); and
emitting an output string according to the lattice representation, (See OU paragraph [0104], The computing device may use the second lattice to determine probabilities that words of the second language correspond to the candidate character strings. In some examples, the computing device may output for display one or more words that are associated with probabilities that satisfy a threshold).
OU does not explicitly disclose parsing the input string into a plurality of tokens; a first-axis value determined by the count of occurrences of a first separator token preceding the token), and a second-axis value determined by the count of occurrences of a second separator token between the most-recent first separator token and the token.
However, Wang teaches parsing the input string into a plurality of tokens, (See Wang paragraph [0013], Each token is a string of one or more characters. The chart parser is configured to generate a chart parse of the input text string); a first-axis value determined by the count of occurrences of a first separator token preceding the token, (See WANG paragraph [0017, for each token in the dictionary data store, the associated score is based on frequency of occurrence of the token. In other features), and a second-axis value determined by the count of occurrences of a second separator token between the most-recent first separator token and the token, (See WANG paragraph [0017, for each token in the dictionary data store, the associated score is based on frequency of occurrence of the token. In other features).
It would have been obvious to one with ordinary skill in the art before the
effective filing date of the claimed invention was made to modify parsing the input string into a plurality of tokens; a first-axis value determined by the count of occurrences of a first separator token preceding the token), and a second-axis value determined by the count of occurrences of a second separator token between the most-recent first separator token and the token of WANG in order to tokenizing a string of text and more particularly to tokenizing text in languages without inter-word separators.
Regarding claim 2, OU taught the non-transitory, computer-readable storage according to claim 1 as described. OU further teaches wherein the retrieved value is at least one token from the input string retrieved, (See OU Abstract, a probability that the at least one of the plurality of candidate character strings corresponds to at least one word included in the second language. The at least one processor may be configured to output for display, the one or more symbols representing at least one word), from the same non-transitory, computer-readable storage media, (See OU paragraph [0165], computer-readable media generally may correspond to (1) tangible computer-readable storage media, which is non-transitory).
Claim 8 recites the same limitations as claim 2 above. Therefore, claim
8 is rejected based on the same reasoning.
Regarding claim 3, OU taught the non-transitory, computer-readable storage according to claim 1 as described OU further teaches wherein the output string, (See OU Abstract, a probability that the at least one of the plurality of candidate character strings corresponds to at least one word included in the second language. The at least one processor may be configured to output for display, the one or more symbols representing at least one word), is executed against a datastore on the same non-transitory, computer-readable storage media, (See OU paragraph [0165], computer-readable media generally may correspond to (1) tangible computer-readable storage media, which is non-transitory).
Claim 9 recites the same limitations as claim 3 above. Therefore, claim
9 is rejected based on the same reasoning.
Regarding claim 4, OU taught the non-transitory, computer-readable storage according to claim 1 as described OU further teaches wherein the output string, (See OU 0034, a language model 12 to determine one or more characters and/and or words of a language based on candidate character strings that correspond to sequences of keys indicated by touch events. The candidate character strings may represent characters of different possible sequences of keys indicated by the touch event), is executed against a datastore on a distinct non-transitory, computer-readable storage media, (See OU paragraph [0165], computer-readable media generally may correspond to (1) tangible computer-readable storage media, which is non-transitory).
Claim 10 recites the same limitations as claim 4 above. Therefore, claim
10 is rejected based on the same reasoning.
Regarding claim 5, OU taught the non-transitory, computer-readable storage according to claim 1 as described OU further teaches wherein the retrieved value is retrieved, (See OU paragraph [0040], receiving the indication of at least one gesture detected at presence-sensitive display 4, keyboard module 8 may determine a group of one or more different candidate strings that correspond to the sequence of touch events), from a distinct non-transitory, computer-readable storage media, (See OU paragraph [0165], computer-readable media generally may correspond to (1) tangible computer-readable storage media, which is non-transitory).
Claim 11 recites the same limitations as claim 5 above. Therefore, claim
11 is rejected based on the same reasoning.
Regarding claim 6, OU taught the non-transitory, computer-readable storage according to claim 1 as described OU further teaches wherein retrieved value is interpreted as a plurality of values, each value forming a distinct output string, forming a plurality of output strings, See OU 0034, a language model 12 to determine one or more characters and/and or words of a language based on candidate character strings that correspond to sequences of keys indicated by touch events. The candidate character strings may represent characters of different possible sequences of keys indicated by the touch event), on one or more non-transitory, computer-readable storage media, (See OU paragraph [0165], computer-readable media generally may correspond to (1) tangible computer-readable storage media, which is non-transitory),
Claim 12 recites the same limitations as claim 6 above. Therefore, claim
12 is rejected based on the same reasoning.
Regarding claim 7, OU teaches One or more non-transitory, computer-readable storage media storing instructions that, (See OU paragraph [0165], computer-readable media generally may correspond to (1) tangible computer-readable storage media, which is non-transitory), when executed by one or more hardware processors of a computing device, cause the computing device to perform operations comprising, (See OU paragraph [0062], One or more processors 40 may implement functionality and/or execute instructions within computing device 2):
receiving an input string, (See OU paragraph [0164], Computing device 294 may receive a subsequent indication of user input to select candidate character string 300);
associating, in a lattice representation, each token with a coordinate set comprising, (See OU paragraph [0043], the token lattice may be a graph that includes vertexes that are connected by edges. Each vertex may be identified by an index),
interpreting at least one token from the plurality of tokens as a relative token, that identifies at least one referenced coordinate set using the coordinate set, (See OU paragraph [0103], determine an out-of-vocabulary candidate character string and model a corresponding candidate character string in the dictionary that is similar to the out-of-vocabulary candidate character string in token lattice 110), associated with the relative token and at least one predefined relative axis offset value associated with the relative token, (See OU paragraph [0045], determine one or more candidate words of a second language (e.g., Chinese) based on the candidate character strings modeled in the token lattice using a second lattice that indicates probabilities of one or more words of the second language based at least in part on the spatial probabilities of the plurality of candidate character strings);
retrieving a value associated with the referenced coordinate set, (See OU paragraph [0086], receives tap inputs, builder module 50 generates additional vertexes 102B, 102C, etc., and generates edges 104A-104D, etc. to the respective vertexes of character lattice 100. Each subsequent tap input may be modeled with a next incremental index value of a vertex);
substituting the retrieved value in place of the relative token in the lattice representation, (See OU paragraph [0086], receives indications of user input, builder module 50 may incrementally build word lattice 120. Builder module 50 may generate an edge that is associated with a single and/or multiple candidate character strings. That is, candidate character strings modeled on edges of token lattice 110); and
emitting an output string according to the lattice representation, (See OU paragraph [0104], The computing device may use the second lattice to determine probabilities that words of the second language correspond to the candidate character strings. In some examples, the computing device may output for display one or more words that are associated with probabilities that satisfy a threshold).
OU does not explicitly disclose parsing the input string into a plurality of tokens, a first-axis value determined by the count of occurrences of a separator token, divided by a fixed axis-depth integer, and rounded down to an integer and a second-axis value determined by the count of occurrences of a separator token.
However, Wang teaches parsing the input string into a plurality of tokens, (See Wang paragraph [0013], Each token is a string of one or more characters. The chart parser is configured to generate a chart parse of the input text string); a first-axis value determined by the count of occurrences of a separator token, (See WANG paragraph [0017, for each token in the dictionary data store, the associated score is based on frequency of occurrence of the token. In other features), and divided by a fixed axis-depth integer, and rounded down to an integer, (See Wang paragraph [0151], Dividing that by 4,320 seconds the number of seconds in 1 hour and 12 minutes) results in a rate of approximately 2.91 million characters per second. However, this example is dependent on network latency and complexity of generating indices, so further enhancement may be possible), and a second-axis value determined by the count of occurrences of a separator token.
, (See WANG paragraph [0017, for each token in the dictionary data store, the associated score is based on frequency of occurrence of the token. In other features).
It would have been obvious to one with ordinary skill in the art before the
effective filing date of the claimed invention was made to modify parsing the input string into a plurality of tokens, a first-axis value determined by the count of occurrences of a separator token, divided by a fixed axis-depth integer, and rounded down to an integer and a second-axis value determined by the count of occurrences of a separator token.
of WANG in order to tokenizing a string of text and more particularly to tokenizing text in languages without inter-word separators.
Regarding claim 13, OU teaches one or more non-transitory, computer-readable storage media storing instructions that, (See OU paragraph [0165], computer-readable media generally may correspond to (1) tangible computer-readable storage media, which is non-transitory), when executed by one or more hardware processors of a computing device, cause the computing device to perform operations comprising, (See OU paragraph [0062], One or more processors 40 may implement functionality and/or execute instructions within computing device 2):
receiving an input binary, (See OU paragraph [0164], Computing device 294 may receive a subsequent indication of user input to select candidate character string 300);
associating each word with a coordinate set comprising, (See OU paragraph [0043], the token lattice may be a graph that includes vertexes that are connected by edges. Each vertex may be identified by an index),
interpreting at least one word from the plurality of fixed-bit-length words as a relative word, that identifies at least one referenced coordinate set using the coordinate set, (See OU paragraph [0103], determine an out-of-vocabulary candidate character string and model a corresponding candidate character string in the dictionary that is similar to the out-of-vocabulary candidate character string in token lattice 110), associated with the relative word and at least one predefined relative axis offset value associated with the relative word, (See OU paragraph [0045], determine one or more candidate words of a second language (e.g., Chinese) based on the candidate character strings modeled in the token lattice using a second lattice that indicates probabilities of one or more words of the second language based at least in part on the spatial probabilities of the plurality of candidate character strings);
retrieving a value associated with the referenced coordinate set, (See OU paragraph [0086], receives tap inputs, builder module 50 generates additional vertexes 102B, 102C, etc., and generates edges 104A-104D, etc. to the respective vertexes of character lattice 100. Each subsequent tap input may be modeled with a next incremental index value of a vertex);
replacing, in the input binary, the retrieved value in place of the relative word, forming an output binary, (See OU paragraph [0086], receives indications of user input, builder module 50 may incrementally build word lattice 120. Builder module 50 may generate an edge that is associated with a single and/or multiple candidate character strings. That is, candidate character strings modeled on edges of token lattice 110); and
emitting the output binary, (See OU paragraph [0104], The computing device may use the second lattice to determine probabilities that words of the second language correspond to the candidate character strings. In some examples, the computing device may output for display one or more words that are associated with probabilities that satisfy a threshold).
OU does not explicitly disclose parsing the input binary into a plurality of fixed-bit-length words; a first-axis value determined by the order position of the word, divided by a fixed axis-depth integer, and rounded down to an integer and a second-axis value determined by the order position of the word, moduloed by the fixed axis-depth integer
However, Wang teaches parsing the input binary into a plurality of fixed-bit-length words, (See Wang paragraph [0151], the numerical length and the numerical end position within the input text string), a first-axis value determined by the order position of the word, divided by a fixed axis-depth integer, and rounded down to an integer, (See Wang paragraph [0151], Dividing that by 4,320 seconds the number of seconds in 1 hour and 12 minutes) results in a rate of approximately 2.91 million characters per second. However, this example is dependent on network latency and complexity of generating indices, so further enhancement may be possible), and a second-axis value determined by the order position of the word, moduloed by the fixed axis-depth integer, (See WANG paragraph [0021, identifying a string of consecutive characters in the input text string that ends at that position and matches one of the plurality of tokens…a numerical start position within the input text string and a numerical end position within the input text string).
It would have been obvious to one with ordinary skill in the art before the
effective filing date of the claimed invention was made to modify parsing the input binary into a plurality of fixed-bit-length words; a first-axis value determined by the order position of the word, divided by a fixed axis-depth integer, and rounded down to an integer and a second-axis value determined by the order position of the word, moduloed by the fixed axis-depth integer of WANG in order to tokenizing a string of text and more particularly to tokenizing text in languages without inter-word separators.
Regarding claim 14, OU taught the non-transitory, computer-readable storage according to claim 13 as described above. OU further teaches wherein the retrieved value is at least one word from the input binary retrieved, (See OU paragraph [0040], receiving the indication of at least one gesture detected at presence-sensitive display 4, keyboard module 8 may determine a group of one or more different candidate strings that correspond to the sequence of touch events), from the same non-transitory, computer-readable storage media, (See OU paragraph [0165], computer-readable media generally may correspond to (1) tangible computer-readable storage media, which is non-transitory).
Regarding claim 15, OU taught the non-transitory, computer-readable storage according to claim 13 as described. OU further teaches wherein the output binary is executed against a datastore, (See OU Abstract, a probability that the at least one of the plurality of candidate character strings corresponds to at least one word included in the second language. The at least one processor may be configured to output for display, the one or more symbols representing at least one word), on the same non-transitory, computer-readable storage media, (See OU paragraph [0165], computer-readable media generally may correspond to (1) tangible computer-readable storage media, which is non-transitory).
Regarding claim 16, OU taught the non-transitory, computer-readable storage according to claim 13 as described. OU further teaches wherein the output binary is executed against a datastore, , (See OU 0034, a language model 12 to determine one or more characters and/and or words of a language based on candidate character strings that correspond to sequences of keys indicated by touch events. The candidate character strings may represent characters of different possible sequences of keys indicated by the touch event), on a distinct non-transitory, computer-readable storage media, (See OU paragraph [0165], computer-readable media generally may correspond to (1) tangible computer-readable storage media, which is non-transitory).
Regarding claim 17, OU taught the non-transitory, computer-readable storage according to claim 13 as described. OU further teaches wherein the retrieved value is retrieved, (See OU paragraph [0040], receiving the indication of at least one gesture detected at presence-sensitive display 4, keyboard module 8 may determine a group of one or more different candidate strings that correspond to the sequence of touch events), from a distinct non-transitory, computer-readable storage media, (See OU paragraph [0165], computer-readable media generally may correspond to (1) tangible computer-readable storage media, which is non-transitory).
Regarding claim 18, OU taught the non-transitory, computer-readable storage according to claim 13 as described. OU further teaches wherein retrieved value is interpreted as a plurality of values, each value forming a distinct output binary, forming a plurality of output binaries, (See OU 0034, a language model 12 to determine one or more characters and/and or words of a language based on candidate character strings that correspond to sequences of keys indicated by touch events. The candidate character strings may represent characters of different possible sequences of keys indicated by the touch event), on one or more non-transitory, computer-readable storage media, (See OU paragraph [0165], computer-readable media generally may correspond to (1) tangible computer-readable storage media, which is non-transitory).
Regarding claim 19, OU teaches one or more non-transitory, computer-readable storage media storing instructions that, (See OU paragraph [0165], computer-readable media generally may correspond to (1) tangible computer-readable storage media, which is non-transitory), when executed by one or more hardware processors of a computing device, cause the computing device to perform operations comprising, (See OU paragraph [0062], One or more processors 40 may implement functionality and/or execute instructions within computing device 2):
receiving an input token stream comprising at least one separator token and at least two datum tokens, (See OU paragraph [0164], Computing device 294 may receive a subsequent indication of user input to select candidate character string 300).
OU does not explicitly disclose mapping, in a single deterministic pass without backtracking, each datum token to coordinates of a multi-axis lattice according to axis-index semantics driven by separator token positions, padding at least one omitted axis by currying at least one datum token mapped to a corresponding prior axis; and writing the lattice to non-transitory, computer-readable storage media.
However, Wang teaches mapping, in a single deterministic pass without backtracking, (See WANG paragraph [0109], With this reversal, some optimizations may be possible. To give a specific example, assume that starting at a certain character in a string, a three-character token is identified in the hash-map. Assume also that there are no longer tokens in the hash-map that begin with those three characters), each datum token to coordinates of a multi-axis lattice according to axis-index semantics driven by separator token positions, (See WANG paragraph [0164], The search module 128 may also include a tokenizer according to the principles of the present disclosure, which splits the search query into separate tokens for querying the search data store 124), padding at least one omitted axis by currying at least one datum token mapped to a corresponding prior axis; (See WANG paragraph [0108], the chart parse creation may be modified to be “greedy”—that is, omitting any chart parse entries that are not the longest possible token for a given position), and writing the lattice to non-transitory, computer-readable storage media, (See WANG paragraph [0161], a non-transitory computer-readable medium are nonvolatile memory devices (such as a flash memory device).
It would have been obvious to one with ordinary skill in the art before the
effective filing date of the claimed invention was made to modify mapping, in a single deterministic pass without backtracking, each datum token to coordinates of a multi-axis lattice according to axis-index semantics driven by separator token positions, padding at least one omitted axis by currying at least one datum token mapped to a corresponding prior axis; and writing the lattice to non-transitory, computer-readable storage media of WANG in order to tokenizing a string of text and more particularly to tokenizing text in languages without inter-word separators.
Regarding claim 20, OU taught the non-transitory, computer-readable storage according to claim 19 as described OU further teaches wherein padding the omitted axis comprises inserting a symbolic reference token that dereferences to prior coordinates, (See WANG paragraph [0164], The search module 128 may also include a tokenizer according to the principles of the present disclosure, which splits the search query into separate tokens for querying the search data store 124).
Regarding claim 22, OU taught the non-transitory, computer-readable storage according to claim 19 as described OU further teaches wherein the operations
further comprise emitting the stored lattice as a token stream in the same syntax as the input token stream, (See OU paragraph [0046], word lattice 120 may include vertexes with the same vertex indexes as token lattice 110. Further examples are illustrated in FIG. 9. As further described in FIG. 4 keyboard module 8 may implement the word lattice using any number of suitable data structures that store state information about edges, vertexes and other corresponding information of the token lattice).
Claims 21 and 23 are rejected under 35 U.S.C. 103 as being unpatentable over OU et al. (US 2016/0026258 A1) in view of WANG et al. (US 2017/0068655 A1) and further in view of Donaldson et al. (US 2015/0017271 A1)
Regarding claim 21, OU taught the non-transitory, computer-readable storage according to claim 19 as described.
OU together with WANG does not explicitly disclose wherein the separator tokens are interpreted by mixed-radix axis-index arithmetic with carry between axis counters.
However, Donaldson teaches wherein the separator tokens are interpreted by mixed-radix axis-index arithmetic with carry between axis counters, (See Donaldson paragraph [0024, The encoder 50 is configured to generate a series of periodic signals indicative of an angular position of an index mark of the hollow member 24 as the index mark rotates about the axis 30…The monitoring system also includes a counter for accumulating the number of integral encoder signal cycles completed and an arithmetic logic unit).
It would have been obvious to one with ordinary skill in the art before the
effective filing date of the claimed invention was made to modify wherein the separator tokens are interpreted by mixed-radix axis-index arithmetic with carry between axis counters of WANG in order to tokenizing a string of text and more particularly to tokenizing text in languages without inter-word separators.
Regarding claim 23, OU taught the non-transitory, computer-readable storage according to claim 19 as described OU further teaches wherein the operations further comprise emitting the stored lattice as a token stream in the same syntax as the input token stream, (See OU paragraph [0046], word lattice 120 may include vertexes with the same vertex indexes as token lattice 110. Further examples are illustrated in FIG. 9. As further described in FIG. 4 keyboard module 8 may implement the word lattice using any number of suitable data structures that store state information about edges, vertexes and other corresponding information of the token lattice).
Conclusions/Points of Contacts
The prior art made of record and not relied upon is considered pertinent to
applicant’s disclosure. See form PTO-892.
Davidovich et al. (US Patent No. 10, 817, 576 B1). receiving a query comprising
a value for a first token of a triplet, and a value for a relation term defining a relationship
between the first token and a second token of the triplet, wherein the second token is
defined as a variable element set with an undefined value, creating a plurality of
enhanced queries for the query, each one of the plurality of enhanced queries including
variations of the relation term, providing the plurality of enhanced queries for search by
a search engine on at least one dataset of unstructured text-based data.
QIU et al. (US 2018/0046638 A1) method for storing data of an embodiment according to the present invention comprises: receiving Resource Description Framework (RDF) data to be stored; obtaining triplet information from the RDF data to be stored; wherein the triplet information comprises three pieces of information: the resource name of a specific resource, the attribute of a specific resource, and the attribute value of a specific resource represented by the RDF data to be stored.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MULUEMEBET GURMU whose telephone number is (571)270-7095. The examiner can normally be reached M-F 9am - 5pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Tony Mahmoudi can be reached at 5712724078. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MULUEMEBET GURMU/Primary Examiner, Art Unit 2163
Prosecution Insights