Detailed Action
This communication is in response to the Arguments and Amendments filed on 10/28/2025.
Claims 1-20 are pending and have been examined.
Claims 1-20 are rejected.
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 Amendment
The Applicants have amended the independent claims to include “receive the corpus of data generated by the wireless telecommunication network, wherein the corpus of data includes data generated at a base station of the wireless telecommunication network based on interactions between a mobile device and the wireless telecommunication network, and wherein the corpus of data is received as network packets: convert the network packets of the corpus of data to a text format:” and “of the”
Regarding the 35 USC § 101 rejection, The applicants’ arguments and amendments overcome the 35 USC § 101 rejection.
Regarding the 35 U.S.C. § 103 rejections, Applicant’s arguments with respect to claim(s) 1, 8 and 14 have been considered but are moot because the new ground of rejection does not rely on the primary reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Hence, new grounds for rejection have been made in view of Hence, new grounds for rejection have been made in view of He (US Patent Number US 20240163684 A1), in view of Copeland (US Patent Number US 20200118555 A1).
Claim Rejections - 35 USC § 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 (i.e., changing from AIA to pre-AIA ) 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.
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 1-4, 8-11, 14-17 are rejected under 35 U.S.C. 103 as being unpatentable over HE (US Patent Number US 20240163684 A1), in view of Copeland (US Patent Number US 20200118555 A1).
Regarding claim 1, HE teaches 1. A non-transitory, computer-readable storage medium comprising instructions recorded thereon to create a grammar representing multiple concepts and multiple relationships based on a corpus of data associated with a wireless telecommunication network, wherein the instructions, when executed by at least one processor of a system of the wireless telecommunication network, cause the system to: (see HE [0012-0013] “A third aspect of the disclosure relates to an electronic device, which includes a memory, a processor, and a computer program stored in the memory and runnable on the processor. The processor implements the method for constructing and analyzing the knowledge graph of the wireless communication network protocol in the above aspect when executing the program. [0013] A fourth aspect of the disclosure relates to a computer readable storage medium, on which a computer executable instruction is stored, and when executed by a processor, the computer executable instruction implements the method for constructing and analyzing the knowledge graph of the wireless communication network protocol in the above aspect.”) wherein a first element in a triple among the multiple triples indicates a first record among the corpus of data, (see He [0004] “A first aspect of the disclosure relates to a method for constructing and analyzing a knowledge graph of a wireless communication network protocol, which includes: [0005] defining entities and a relation between the entities according to endogenous factors of a wireless communication network protocol, the endogenous factors of the wireless communication network protocol comprising data fields and indicators, of a core network, which are specified by the wireless communication network protocol; [0006] defining a triplet based on the defined entities and the defined relation between the entities; [0007] constructing, according to the defined triplet, a knowledge graph of the endogenous factors of the wireless communication network protocol, the knowledge graph having a topology; and [0008] performing association analysis between any nodes in the knowledge graph to acquire an association relation hidden between the endogenous factors of the wireless communication network protocol.”) wherein a second element in the triple among the multiple triples indicates a second record among the corpus of data, (see He Figure 1, Element S11) wherein a third element in the triple among the multiple triples indicates a relationship between the first record and the second record, (see He Figure 1, Element S12) generate multiple grammars representing the multiple triples, wherein the grammar among the multiple grammars includes the multiple concepts and the multiple relationships, (see He [0024] At S14, the knowledge graph is constructed. The head entity and the tail entity of the triplet in S13 serve as the nodes of the knowledge graph. (examiner interprets multiple triples as nodes in the knowledge graph”)wherein the multiple concepts include a first concept representing the first record and a second concept representing the second record, wherein the multiple relationships represent the relationship between the first record and the second record; (see He [0022-0023] “At S12, a relation between the entities is defined. The relation between the entities is classified into a process relation, a conditional relation, and an algorithm relation according to the wireless communication network protocol, and the relation between the entities is defined as at least one of the process relation, the conditional relation, and the algorithm relation according to the endogenous factors of the wireless communication network protocol. The process relation describes the correlation between an entity of the data field type and an entity of the process type. The conditional relation describes specific values of the data fields associated with the entity of the statistical type data indicator when the entity of the statistical type data indicator takes effect. The algorithm relation describes a calculation method for converting the entity of the statistical type data indicator into the entity of the algorithm type data indicator. [0023] At S13, a triplet is defined. The entity includes a head entity and a tail entity. A universal triplet (head, relation, tail) for an entity wireless communication protocol is constructed based on the relation between the entities defined in S11 and S12, and the triplet has a connection relation, that is, the triplet is composed of the relation between the entities. Herein, head is the head entity in the triplet and tail is the tail entity in the triplet. The head entity and the tail entity in each triplet belong to one of the following entity types: process type, data field type, statistical type data indicator, or algorithm type data indicator. relation is the relation between the entities belongs to at least one of the following relations: process relation, conditional relation, or algorithm relation.”) apply each grammar among the multiple grammars to the multiple triples to obtain an indication of whether each triple among the multiple triples is correct; based on the indication of whether each triple among the multiple triples is correct, (See He [0031] “At S23, the structure of the knowledge graph is updated. The relation between the entities defined by the endogenous factors of the wireless communication network protocol in the original knowledge graph is replaced with the connection relation between the nodes quantified by the cosine similarity between the sparse representation vectors of the nodes, which updates the knowledge graph's structure. It is set that there is a connection relation between the nodes having cosine similarity values not lower than a cosine similarity threshold η and there is no connection relation between a node u and a node v having a cosine similarity value lower than the threshold η, and c(x.sub.u, x.sub.v)=0. The connection relation determined by the protocol in the original knowledge graph is replaced with the cosine similarity value to realize the quantification of the connection relation between the nodes in the knowledge graph. There is the cosine similarity between the sparse representation vectors of any entity nodes, that is, the nodes are connected in pairs, but some weakly connected nodes need to be disconnected if the cosine similarity value is lower than the cosine similarity threshold η, to realize the update of the structure of the graph. [0032] At S24, the degree of association between the nodes and the feature vectors of the nodes are calculated. An association vector of each node is calculated based on the updated structure of the knowledge graph and the cosine similarity, and the feature vector of the node is calculated through the association vector.”) determine an accuracy associated with the each grammar among the multiple grammars; and based on the accuracy associated with the each grammar among the multiple grammars, select a grammar having a highest accuracy among the multiple grammars. (see He [0025] At S2, association analysis is performed between any nodes in the knowledge graph to acquire an association relation hidden between the endogenous factors of the wireless communication network protocol. In one example, through the adoption of an association analysis model method, sparse representation vectors of the nodes are obtained by calculating random state weights of the nodes, the connection relation established between any nodes in the knowledge graph through the wireless communication network protocol is quantified and replaced with a cosine similarity between the sparse representation vectors, and then association vectors of the nodes are calculated. The association vectors are configured to calculate feature vectors of the nodes. The quantitative representation of the knowledge graph is completed by the feature vectors of the nodes, which facilitates mining the association relation between the nodes, and then the association relation hidden between the endogenous factors of the wireless communication network protocol is acquired. The association analysis based on the knowledge graph of the endogenous factors of the wireless communication network protocol aims to calculate the similarity that quantifies the connection relation between the nodes. It also aims to determine the degree of association between any node and all other nodes to support the representation learning of the feature vectors of the nodes. This further enables mining of the association relation between the intra-class nodes. To achieve the purpose, firstly, the sparse representation vectors of the nodes are obtained according to the topology of the knowledge graph constructed in S1, and then the quantification of the connection relation between the nodes is realized by calculating the cosine similarity between the sparse representation vectors. The relation determined in the original knowledge graph by the protocol is replaced with the quantified connection relation between the nodes to complete the update of the structure of the knowledge graph. The association vectors of the nodes are calculated in combination with the updated topology of the knowledge graph and the similarity, then the feature vectors of the nodes are calculated, and the quantitative representation of the knowledge graph is completed through the feature vectors of the nodes, which provides technical support for the subsequent deep mining of the association relation between the nodes. In calculating the connection relation between the nodes through cosine similarity quantification, the association between the nodes without direct connection relation in the original knowledge graph is also inferred.”)
He does not specifically teach receive the corpus of data generated by the wireless telecommunication network, wherein the corpus of data includes data generated at a base station of the wireless telecommunication network based on interactions between a mobile device and the wireless telecommunication network, However, Copeland does teach this limitation (see Copeland [0037] “In the example apparatus of FIG. 3, the speech-enabled device is coupled for data communication through a communications adapter (167), wireless connection (118), data communications network (100), and wireline connection (121) to a triple server (157). The triple server (157) provides large volume backup for triple stores (323, 325). The triple server is a configuration of automated computing machinery that serializes triples and stores serialized triples in relational databases, tables, files, or the like. The triple server retrieves upon request from non-volatile storage such serialized triples, parses the serialized triples into triple stores, and provides such triple stores upon request to speech-enabled devices for use in systems that utilize the triples in configuring computer memory according to embodiments of the present invention.”) and wherein the corpus of data is received as network packets: convert the network packets of the corpus of data to a text format: (see Copeland [0031] “VOIP stands for ‘Voice Over Internet Protocol,’ a generic term for routing speech over an IP-based data communications network. The speech data flows over a general-purpose packet-switched data communications network, instead of traditional dedicated, circuit-switched voice transmission lines. Protocols used to carry voice signals over the IP data communications network are commonly referred to as ‘Voice over IP’ or ‘VOIP’ protocols. VOIP traffic may be deployed on any IP data communications network, including data communications networks lacking a connection to the rest of the Internet, for instance on a private building-wide local area data communications network or ‘LAN.’”) wherein the first record and the second record are configured to indicate a data record of the mobile device associated with the wireless telecommunication network, or a process running on the mobile device associated with the wireless telecommunication network; (see Copeland [0037] “In the example apparatus of FIG. 3, the speech-enabled device is coupled for data communication through a communications adapter (167), wireless connection (118), data communications network (100), and wireline connection (121) to a triple server (157). The triple server (157) provides large volume backup for triple stores (323, 325). The triple server is a configuration of automated computing machinery that serializes triples and stores serialized triples in relational databases, tables, files, or the like. The triple server retrieves upon request from non-volatile storage such serialized triples, parses the serialized triples into triple stores, and provides such triple stores upon request to speech-enabled devices for use in systems that utilize the triples in configuring computer memory according to embodiments of the present invention.”)
He and Copeland are in the same field of endeavor of signal processing, therefore It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the storage medium of He to incorporate the teachings of Copeland to include receive the corpus of data generated by the wireless telecommunication network, wherein the corpus of data includes data generated at a base station of the wireless telecommunication network based on interactions between a mobile device and the wireless telecommunication network, and wherein the corpus of data is received as network packets: convert the network packets of the corpus of data to a text format: extract, from the corpus of data, multiple triples representing the corpus of data, wherein extract, from the corpus of data, multiple triples representing the corpus of data, wherein the first record and the second record are configured to indicate a data record, a mobile device associated with the wireless telecommunication network, or a process running on the mobile device associated with the wireless telecommunication network Doing so allows for query results in conversational real time as recognized by Copeland in [0026].
Regarding independent claim 8, claim 8 is a method claim with limitations similar to that of claim 1 and is rejected under the same rationale.
Regarding independent claim 14, Claim 14 is a system claim with limitations similar to that of claim 1 and is rejected under the same rationale. Furthermore teaches HE teaches A system comprising: at least one hardware processor; and at least one non-transitory memory storing instructions, which, when executed by the at least one hardware processor, cause the system to: (see He [0012] A third aspect of the disclosure relates to an electronic device, which includes a memory, a processor, and a computer program stored in the memory and runnable on the processor. The processor implements the method for constructing and analyzing the knowledge graph of the wireless communication network protocol in the above aspect when executing the program.”)
As to Claim 2, He in view of Copeland teaches 2. The non-transitory, computer-readable storage medium of claim 1, (see Claim 1).
Furthermore, Copeland teaches, comprising instructions to: wherein the corpus of data further includes multiple messages passed between multiple mobile devices associated with the wireless telecommunication network, wherein the first element in the triple among the multiple triples indicates a first mobile device, wherein the second element in the triple among the multiple triples indicates a second mobile device, wherein the third element in the triple among the multiple triples indicates a property of a message passed between the first mobile device and the second mobile device; obtain a first message passed between the first mobile device and the second mobile device, wherein the message is not among the multiple messages; create a first triple including the first mobile device, the second mobile device, and a property associated with the first message; apply the grammar to the first triple to obtain an indication of whether the first triple is correct; and upon obtaining the indication that the first triple is incorrect, determine that the message is a spam message. (see Copeland [0037] In the example apparatus of FIG. 3, the speech-enabled device is coupled for data communication through a communications adapter (167), wireless connection (118), data communications network (100), and wireline connection (121) to a triple server (157). The triple server (157) provides large volume backup for triple stores (323, 325). The triple server is a configuration of automated computing machinery that serializes triples and stores serialized triples in relational databases, tables, files, or the like. The triple server retrieves upon request from non-volatile storage such serialized triples, parses the serialized triples into triple stores, and provides such triple stores upon request to speech-enabled devices for use in systems that utilize the triples in configuring computer memory according to embodiments of the present invention.
He and Copeland are in the same field of endeavor of signal processing, therefore It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of combination of He to incorporate the teachings of Copeland to include the corpus of data further includes multiple messages passed between multiple mobile devices associated with the wireless telecommunication network, wherein the first element in the triple among the multiple triples indicates a first mobile device, wherein the second element in the triple among the multiple triples indicates a second mobile device, wherein the third element in the triple among the multiple triples indicates a property of a message passed between the first mobile device and the second mobile device; obtain a first message passed between the first mobile device and the second mobile device, wherein the message is not among the multiple messages; create a first triple including the first mobile device, the second mobile device, and a property associated with the first message; apply the grammar to the first triple to obtain an indication of whether the first triple is correct; and upon obtaining the indication that the first triple is incorrect, determine that the message is a spam message. Doing so allows for query results in conversational real time as recognized by Copeland in [0026].
As to Claim 3, HE in view of Copeland teaches 3. The non-transitory, computer-readable storage medium of claim 1,
Furthermore, Copeland teaches comprising instructions to: wherein the corpus of data further includes multiple relationships between multiple components of the wireless telecommunication network, wherein the multiple components include a radio network, a core network, and an Internet protocol (IP) network, wherein the first element in the triple among the multiple triples indicates a first component of the wireless telecommunication network, wherein the second element in the triple among the multiple triples indicates a second component of the wireless telecommunication network, wherein the third element in the triple among the multiple triples indicates a relationship between the first component and the second component; obtain an indication of a failure associated with the wireless telecommunication network; obtain an interaction between the first component and the second component; create a first triple including the first component, the second component, and the interaction; (see Copeland [0058-0059] “The example voice server (151) of FIG. 4 includes a communications adapter (167) for data communications with other computers (182) and for data communications with a data communications network (100). Such data communications may be carried out serially through RS-232 connections, through external buses such as a Universal Serial Bus (‘USB’), through data communications data communications networks such as IP data communications networks, and in other ways as will occur to those of skill in the art. Communications adapters implement the hardware level of data communications through which one computer sends data communications to another computer, directly or through a data communications network. Examples of communications adapters useful for embodiments of the present invention include modems for wired dial-up communications, Ethernet (IEEE 802.3) adapters for wired data communications network communications, and 802.11 adapters for wireless data communications network communications. [0059] For further explanation, FIG. 5 sets forth a block diagram of automated computing machinery comprising an example of a computer useful as a triple server (157) for configuring computer memory according to embodiments of the present invention. The triple server (157) of FIG. 5 includes at least one computer processor (156) or ‘CPU’ as well as random access memory (168) (‘RAM’) which is connected through a high-speed memory bus (166) and bus adapter (158) to processor (156) and to other components of the triple server. The processor is connected through a video bus (164) to a video adapter (209) and a computer display (180). The processor is connected through an expansion bus (160) to a communications adapter (167), an I/O adapter (178), and a disk drive adapter (172). The processor is connected to a speech-enabled laptop (126) through data communications network (100) and wireless connection (118). Disposed in RAM is an operating system (154).”) (see Copeland [0064] Suppose a jargon is composed of 500-word families each of which includes three words so that the entire jargon is expressed in 1500 words each of which on average is composed of 10 bytes of storage for a total for the jargon of 15 kilobytes of storage. Some computer systems today support memory page sizes of a megabyte or more. Such a jargon can be stored in a single memory page, and, once that page is in RAM, operation of the jargon can proceed with no risk of page faults at all. Even if contiguous storage for such a jargon fell across a page boundary, the entire jargon can be loaded with only two page faults, and, after it is loaded into RAM, it can be operated with zero page faults going forward. Cache misses would still be required to load the contents into cache, but, except for the first one or two misses, none of the others would risk a page fault. The inventors estimate that after a short period of operation, the cache miss rate would be less than one percent. That is, when a jargon is disposed in contiguous memory according to embodiments of the present invention, memory access times generally will approximate cache access times, just a few nanoseconds, for more than 99% of memory access.”) apply the grammar to the first triple to obtain an indication of whether the first triple is correct; and upon obtaining the indication that the first triple is incorrect, determine that the interaction between the first component and the second component is associated with the failure associated with the wireless telecommunication network. (see Copeland [0066] “The thick-client speech-enabled device in the example of FIG. 7 is automated computer machinery that includes a processor (156), RAM (168), data buses (162, 164, 166, 160), video (180, 209), data communications (167), I/O (178), and disk storage (170). Disposed in RAM are a speech-enabled application program (195), a semantic query engine (298), a general language triple store (323), a jargon triple store (325), a triple parser/serializer (294), a triple converter (292), and one or more triple files (290). The speech-enabled application (195) accepts from user input semantic queries that it passes to the semantic query engine (298) for execution against the triple stores (323, 325). All pertinent triples are available in local RAM. All queries succeed or fail based on local storage alone. No queries are ever forwarded to the triple server (157). The triple server (157) provides long-term backup and synchronization functions when multiple client-side devices share the contents of triple stores, but, for any particular query, all responsive triples are available directly on the client side.”)
He and Copeland are in the same field of endeavor of signal processing, therefore It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of combination of He and Copeland to incorporate the teachings of Copeland to include comprising instructions to: wherein the corpus of data further includes multiple relationships between multiple components of the wireless telecommunication network, wherein the multiple components include a radio network, a core network, and an Internet protocol (IP) network, wherein the first element in the triple among the multiple triples indicates a first component of the wireless telecommunication network, wherein the second element in the triple among the multiple triples indicates a second component of the wireless telecommunication network, wherein the third element in the triple among the multiple triples indicates a relationship between the first component and the second component; obtain an indication of a failure associated with the wireless telecommunication network; obtain an interaction between the first component and the second component; create a first triple including the first component, the second component, and the interaction; apply the grammar to the first triple to obtain an indication of whether the first triple is correct; and upon obtaining the indication that the first triple is incorrect, determine that the interaction between the first component and the second component is associated with the failure associated with the wireless telecommunication network. Doing so allows for the quality of the audio to be monitored to ensure that each speaking participant is heard as recognized by Copeland in [0003-0005].
As to Claim 4, HE in view of Copeland teaches 4. The non-transitory, computer-readable storage medium of claim 1,
Furthermore Copeland teaches, comprising instructions to: wherein the corpus of data further includes multiple interactions between a user of a mobile device and a first component associated with the wireless telecommunication network, wherein the first element in the triple among the multiple triples indicates the mobile device, wherein the second element in the triple among the multiple triples indicates the first component associated with the wireless telecommunication network, wherein the third element in the triple among the multiple triples indicates an interaction between the mobile device and the first component associated with the wireless telecommunication network; see Copeland [0058-0059] “The example voice server (151) of FIG. 4 includes a communications adapter (167) for data communications with other computers (182) and for data communications with a data communications network (100). Such data communications may be carried out serially through RS-232 connections, through external buses such as a Universal Serial Bus (‘USB’), through data communications data communications networks such as IP data communications networks, and in other ways as will occur to those of skill in the art. Communications adapters implement the hardware level of data communications through which one computer sends data communications to another computer, directly or through a data communications network. Examples of communications adapters useful for embodiments of the present invention include modems for wired dial-up communications, Ethernet (IEEE 802.3) adapters for wired data communications network communications, and 802.11 adapters for wireless data communications network communications. [0059] For further explanation, FIG. 5 sets forth a block diagram of automated computing machinery comprising an example of a computer useful as a triple server (157) for configuring computer memory according to embodiments of the present invention. The triple server (157) of FIG. 5 includes at least one computer processor (156) or ‘CPU’ as well as random access memory (168) (‘RAM’) which is connected through a high-speed memory bus (166) and bus adapter (158) to processor (156) and to other components of the triple server. The processor is connected through a video bus (164) to a video adapter (209) and a computer display (180). The processor is connected through an expansion bus (160) to a communications adapter (167), an I/O adapter (178), and a disk drive adapter (172). The processor is connected to a speech-enabled laptop (126) through data communications network (100) and wireless connection (118). Disposed in RAM is an operating system (154).”) (see Copeland [0064] Suppose a jargon is composed of 500-word families each of which includes three words so that the entire jargon is expressed in 1500 words each of which on average is composed of 10 bytes of storage for a total for the jargon of 15 kilobytes of storage. Some computer systems today support memory page sizes of a megabyte or more. Such a jargon can be stored in a single memory page, and, once that page is in RAM, operation of the jargon can proceed with no risk of page faults at all. Even if contiguous storage for such a jargon fell across a page boundary, the entire jargon can be loaded with only two page faults, and, after it is loaded into RAM, it can be operated with zero page faults going forward. Cache misses would still be required to load the contents into cache, but, except for the first one or two misses, none of the others would risk a page fault. The inventors estimate that after a short period of operation, the cache miss rate would be less than one percent. That is, when a jargon is disposed in contiguous memory according to embodiments of the present invention, memory access times generally will approximate cache access times, just a few nanoseconds, for more than 99% of memory access.”) obtain an information campaign associated with the wireless telecommunication network, and a second component associated with the wireless telecommunication network and associated with the information campaign; determine whether the first component and the second component correspond to each other; and upon determining that the first component and the second component correspond to each other, present the information campaign to the user of the mobile device. (see Copeland [0037] “In the example apparatus of FIG. 3, the speech-enabled device is coupled for data communication through a communications adapter (167), wireless connection (118), data communications network (100), and wireline connection (121) to a triple server (157). The triple server (157) provides large volume backup for triple stores (323, 325). The triple server is a configuration of automated computing machinery that serializes triples and stores serialized triples in relational databases, tables, files, or the like. The triple server retrieves upon request from non-volatile storage such serialized triples, parses the serialized triples into triple stores, and provides such triple stores upon request to speech-enabled devices for use in systems that utilize the triples in configuring computer memory according to embodiments of the present invention.”)
He and Copeland are in the same field of endeavor of signal processing, therefore It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the storage medium of He to incorporate the teachings of Copeland to include comprising instructions to: wherein the corpus of data further includes multiple interactions between a user of a mobile device and a first component associated with the wireless telecommunication network, wherein the first element in the triple among the multiple triples indicates the mobile device, wherein the second element in the triple among the multiple triples indicates the first component associated with the wireless telecommunication network, wherein the third element in the triple among the multiple triples indicates an interaction between the mobile device and the first component associated with the wireless telecommunication network; obtain an information campaign associated with the wireless telecommunication network, and a second component associated with the wireless telecommunication network and associated with the information campaign; determine whether the first component and the second component correspond to each other; and upon determining that the first component and the second component correspond to each other, present the information campaign to the user of the mobile device. Doing so allows for query results in conversational real time as recognized by Copeland in [0026].
As to Claim 9, claim 9 is a device claim with limitations similar to that of claim 2 and is rejected under the same rationale.
As to Claim 10, claim 10 is a device claim with limitations similar to that of claim 3 and is rejected under the same rationale.
As to Claim 11, claim 11 is a device claim with limitations similar to that of claim 4 and is rejected under the same rationale.
Regarding Claim 15, claim 15 is a device claim with limitations similar to that of claim 2 and is rejected under the same rationale.
Regarding Claim 16, claim 16 is a device claim with limitations similar to that of claim 3 and is rejected under the same rationale.
Regarding claim 17, claim 17 is a device claim with limitations similar to that of claim 4 and is rejected under the same rationale.
Claims 5-7, 12, 13, 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over HE (US Patent Number US 20240163684 A1), in view of Copeland (US Patent Number US 20200118555 A1) and further in view of AKIMA (US Patent Number US-20230297782-A1),
As to Claim 5, HE in view of Copeland teaches 5. The non-transitory, computer-readable storage medium of claim 1,
HE in view of Copeland do not specifically teach comprising instructions to: apply the grammar to the multiple triples representing the corpus of data to identify a subset of the multiple triples that are incorrect according to the grammar; and tag the subset of the multiple triples as invalid data. (However, AKIMA does teach this limitation (see AKIMA [0039-0041] “Then, the triple generation unit 11 creates a verb list (VL) by referring to the part-of-speech tags in the AMR syntax analysis result 10a (S3). Then, the triple generation unit 11 determines whether or not the verb list VL is empty (S4) and, when the verb list VL is not empty (S4: No), performs the processes in S5 to S7. [0040] For example, the triple generation unit 11 takes out a verb V from the verb list VL (S5). Then, the triple generation unit 11 extracts the arguments (ARG_m (head) and ARG_n (tail)) of the verb V with reference to the AMR syntax analysis result 10a (S6). For example, in S6, the triple generation unit 11 extracts the subject and the object with respect to the verb V. [0041] Then, the triple generation unit 11 adds the triple (head, V, tail) to a triple list (TL) (S7) and returns the process to S4.”)
HE in view of Copeland and Akima are in the same field of endeavor of signal processing, therefore It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of combination of HE and Copeland to incorporate the teachings of Akima to include comprising instructions to: apply the grammar to the multiple triples representing the corpus of data to identify a subset of the multiple triples that are incorrect according to the grammar; and tag the subset of the multiple triples as invalid data. Doing so allows for analysis of the text corpus as recognized by Akima in [0038].
Regarding claim 6, HE in view of Copeland teaches 6. The non-transitory, computer-readable storage medium of claim 1,
HE in view of Copeland do not specifically teach wherein the instructions to extract the multiple triples comprise instructions to: obtain a second corpus of data; extract, from the second corpus of data, a second multiplicity of triples representing the second corpus of data; apply the grammar to the second corpus of data to obtain a second accuracy associated with the grammar and the second corpus of data; and adjust the grammar based on the second accuracy. (However, AKIMA does teach this limitation (see AKIMA [0039-0041] Then, the triple generation unit 11 creates a verb list (VL) by referring to the part-of-speech tags in the AMR syntax analysis result 10a (S3). Then, the triple generation unit 11 determines whether or not the verb list VL is empty (S4) and, when the verb list VL is not empty (S4: No), performs the processes in S5 to S7. [0040] For example, the triple generation unit 11 takes out a verb V from the verb list VL (S5). Then, the triple generation unit 11 extracts the arguments (ARG_m (head) and ARG_n (tail)) of the verb V with reference to the AMR syntax analysis result 10a (S6). For example, in S6, the triple generation unit 11 extracts the subject and the object with respect to the verb V.[0041] Then, the triple generation unit 11 adds the triple (head, V, tail) to a triple list (TL) (S7) and returns the process to S4.”)
HE in view of Copeland and Akima are in the same field of endeavor of signal processing, therefore It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of combination of HE and Copeland to incorporate the teachings of Akima to include wherein the instructions to extract the multiple triples comprise instructions to: obtain a second corpus of data; extract, from the second corpus of data, a second multiplicity of triples representing the second corpus of data; apply the grammar to the second corpus of data to obtain a second accuracy associated with the grammar and the second corpus of data; and adjust the grammar based on the second accuracy. Doing so allows for analysis of the text corpus as recognized by Akima in [0038].
Regarding claim 7, HE in view of Copeland teaches 7. The non-transitory, computer-readable storage medium of claim 1,
HE in view of Copeland do not specifically teach, wherein the instructions to extract the multiple triples comprise instructions to: use artificial intelligence (AI) to extract, from the corpus of data, the multiple triples. (However, AKIMA does teach this limitation (see AKIMA [0033] As an example, the text 30a acquired from the text corpus DB 30 is assumed as “Because Taro opened the window, the wind came into the room”. The AMR syntax analysis unit 10 obtains the AMR syntax analysis result 10a by analyzing the text 30a using a known technique such as StoG. (examiner interprets AI as “SToG”)
HE in view of Copeland and Akima are in the same field of endeavor of signal processing, therefore It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of combination of HE and Copeland to incorporate the teachings of Akima to include wherein the instructions to extract the multiple triples comprise instructions to: use artificial intelligence (AI) to extract, from the corpus of data, the multiple triples. Doing so allows for analysis of the text corpus as recognized by Akima in [0038].
As to Claim 12, claim 12 is a device claim with limitations similar to that of claim 5 and is rejected under the same rationale.
As to Claim 13, claim 13 is a device claim with limitations similar to that of claim 6 and is rejected under the same rationale.
Regarding claim 18, claim 18 is a device claim with limitations similar to that of claim 5 and is rejected under the same rationale.
Regarding claim 19, claim 19 is a device claim with limitations similar to that of claim 6 and is rejected under the same rationale.
Regarding claim 20, claim 20 is a device claim with limitations similar to that of claim 7 and is rejected under the same rationale.
Conclusion
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).
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/KRISTEN MICHELLE MASTERS/Examiner, Art Unit 2659
/PIERRE LOUIS DESIR/Supervisory Patent Examiner, Art Unit 2659