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 .
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 1-20 are pending in this office action.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly
pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 1, 8, 15 recite the limitations “the appropriate superblocks” and “the connected components”. There is insufficient antecedent basis for these limitations in the claims.
The dependent claims 2-7, 9-14, 16-20 of claims 1, 8, 15 are rejected under the same reason as discussed in claims 1, 8, 15.
Claim 4 recite the limitation “the alphabet”. There is insufficient antecedent basis for this limitation in the claim.
Claim 5 recite the limitation “the deletion of the first character”. There is insufficient antecedent basis for this limitation in the claim.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 (The Statutory Categories): Is the claim to a process, machine, manufacture or composition of matter? MPEP 2106.03
Per Step 1, claim 1 is directed to a computer implemented method, claim 8 to non-transitory computer readable medium, and claim 15 to an apparatus, which are statutory categories of invention per Step 1. However, the claims are rejected under 35 U.S.C. 101 because they are directed to an abstract idea, a judicial exception, without reciting additional elements that integrate the judicial exception into a practical application or are significantly more.
Step 2A:
a) In analyzing under step 2A Prong One, Does the claim recite an abstract idea law of nature or natural phenomenon? Yes.
Claims 1, 8, 15 similarly recite abstract idea of
(creating superblocks based upon one or more blocking attributes;
generating k-mers for all the records based upon a selected k value;
performing blocking on the records and placing any records with matching k-mers in the appropriate superblocks;
defining a graph G(V, E) where there is a node per record and connecting records via an edge in the graph when records are found together in at least one of the superblocks and an edit distance between the records is within a given threshold value; or
defining a graph G(V, E) where there is a node per record and connecting records via an edge in the graph if they are found together in at least one of the superblocks and an edit distance between the records is within a given threshold value) as drafted, is a process or system or medium that, under its broadest reasonable interpretation, covers performance of the limitations in the mind but for the recitation of generic computer components. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. The human mind can perform steps of creating, generating, performing blocking, placing, and defining. Accordingly, the claims recite an abstract idea.
b) In analyzing under step 2A Prong Two, Does the claim recite additional elements that integrate the judicial exception into a practical application? NO.
Claims do not recite additional elements that integrate the judicial exception into a practical application because the additional limitations of program instructions stored thereon for sorting diverse sets of data which, when executed by a processor, causes the processor to carry out the steps (in claim 8); and one or more processors, and memory accessible by the one or more processors, the memory storing instructions that when executed by the one or more processors, cause the apparatus to perform the method (in claim 15) that are recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using a generic computer component.
The additional limitations of (receiving a plurality of records from one or more data sources; finding and outputting the connected components of graph G(V, E) as final clusters.) that represent well-understood, routine, conventional activity (See MPEP 2106.05(g) or 2106.05(d) for Presenting offers and gathering statistics, OIP Techs and Receiving or transmitting data over a network, e.g. see Intellectual Ventures v. Symantec; Storing and retrieving information in memory: Versata; Analyzing data: Genetic Techs; Determining: OIP Techs; Electronic recordkeeping: Alice Corp).
The additional limitation of (wherein each record includes one or more attributes associated with an entity that just indicates definition of record
Accordingly, these additional elements do not recite additional elements that integrate the judicial exception into a practical application. The claims are not patent eligible.
c) In analyzing under step 2B, does the claim recite additional elements that amount to significantly more than the judicial exception? NO
Claims do not recite any additional elements that amount to significantly more than the judicial because additional limitation of program instructions stored thereon for sorting diverse sets of data which, when executed by a processor, causes the processor to carry out the steps (in claim 8); and one or more processors, and memory accessible by the one or more processors, the memory storing instructions that when executed by the one or more processors, cause the apparatus to perform the method (in claim 15) that are recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using a generic computer component.
The additional limitations of (receiving a plurality of records from one or more data sources; finding and outputting the connected components of graph G(V, E) as final clusters.) that represent well-understood, routine, conventional activity (See MPEP 2106.05(g) or 2106.05(d) for Presenting offers and gathering statistics, OIP Techs and Receiving or transmitting data over a network, e.g. see Intellectual Ventures v. Symantec; Storing and retrieving information in memory: Versata; Analyzing data: Genetic Techs; Determining: OIP Techs; Electronic recordkeeping: Alice Corp).
The additional limitation of (wherein each record includes one or more attributes associated with an entity that just indicates definition of record
Accordingly, these additional elements do not amount to significantly more than the judicial exception. The claims are not patent eligible.
Dependent claims include all the limitations of claims 1, 8, 15. Therefore, claims 2-7, 9-14, 16-20 recite the same abstract idea being performed in the mind, and the analysis must therefore proceed to Step 2A Prong Two.
In particularly:
Claim 2 recites limitation of (wherein each record is a string of characters and a record is in multiple blocks) that just indicates definition of the record.
Claim 3 recites limitation of (wherein the superblocks are defined based upon predefined criteria, the value of some parameter, or some other characteristic of the problem being solved) that just indicates superblocks defined based on criteria.
Claim 4 recites limitation of (wherein blocking on the records is comprised of a total of s blocks, where s is the size of the alphabet and k is the selected value for k-mers) that just indicates definition of blocking on records.
Claim 5 recites limitation of (wherein blocking on the records are adjusted to account for the deletion of the first character in a record when determining whether to add records to a superblock) that just indicates blocking is modified to account for deletion.
Claim 6 recites limitation of (wherein the edit distance can be adjusted so the edit distance between records in the blocking attributes is no more than a selected value) that just indicates distance adjusted.
Claim 7 recites limitation of (wherein the threshold value is calculated using an empirical ground truth error rate for a sample of the records) that just indicates value calculated using error rate.
Claim 9 recites limitation of (the one or more data sources include call data records (CDRs), network traffic, customer support interactions, geolocation data) that just indicates definition of data source.
Claim 10 recites limitation of (wherein the one or more data sources include purchase history, clickstreams, inventory logs, customer profiles, supply chain data) that just indicates source including data.
Claim 11 recites limitation of (wherein the one or more data sources include one or more of data from the Census Bureau, Social Security Administration, hospitals, healthcare providers, traffic data, transactional data, and forensic data) that just indicates source including data from businesses.
Claim 12 recites limitation of (wherein the one or more data sources include financial records, banking records, transaction logs, market feeds, risk models, fraud detection data, customer behavior) that just indicates source including types of records.
Claim 13 recites limitation of (wherein at least one of the one or more data sources includes genomic sequences, electronic health records, imaging data, clinical trials, wearable device data) that just indicates definition of sources.
Claim 14 recites abstract ideas of (wherein the sorting of diverse sets of data includes a linkage of records and resolution of entities) as drafted, is a process or system or medium that, under its broadest reasonable interpretation, covers performance of the limitations in the mind but for the recitation of generic computer components. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. The human mind can perform step of sorting. Accordingly, the claim recites an abstract idea.
Claim 16 recites limitation of (wherein the one or more data sources includes a combination of structured and unstructured data) that indicates sources including structured and unstructured data
Claim 17 recites limitation of (wherein the one or more data sources includes one or more of smart meter outputs, grid sensor data, consumption patterns, and equipment telemetry) that just indicates definition of data sources,
Claim 18 recites limitation of (wherein the data sources include one or more of streaming logs, user preferences, content metadata, and social media interactions) that just indicates definition of data sources.
Claim 19 recites limitation of (wherein the one or more data sources includes one or more of event logs, authentication records, network packets, malware signatures) that just indicates definition of data sources.
Claim 20 recites limitation of wherein at least one of the one or more data sources includes biometric data that just indicates definition of data sources.
Accordingly, these additional elements do not recite additional elements that integrate the judicial exception into a practical application and do not amount to significantly more than the judicial exception. The claims are not patent eligible.
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 1-2, 8, 15, 17-18, 20 are rejected under 35 U.S.C. 103 as being unpatentable over Tseng et al (US 20130013595) in view of O Mahony et al (or hereinafter “Ma”) (US 20210004157), and Colley et al (US 20210090694)
As to claim 1, Tseng teaches a computer implemented method for sorting diverse sets of data (paragraph 14), comprising:
“receiving a plurality of records from one or more data sources, wherein each record includes one or more attributes associated with an entity” as receiving a plurality of objects as records from one or more third parties or providers 120 that includes one or more data sources (fig. 1, paragraphs 20, 56), each object as record includes categories, locations, and delivery time ranges as one or more attributes (paragraph 6) associated with an entity (paragraph 20);
“creating superblocks……” as storing as creating user profiles, which include information e.g., biographic, demographic, and other types of descriptive information, such as work experience, educational history, hobbies or preferences, interests, location, are represented as superblocks (paragraphs 29-30, 94);
“generating ……for all the records based upon……” as generating a social graph including nodes in the social graph for the objects as all the records based on data stored in connection store 245, user profile store 240, and action log 230 (paragraph 43);
“defining a graph G (V, E) where there is a node per record and connecting records via an edge in the graph when records are found together in at least one of the superblock and an edit distance between the records is within a given threshold value” as generating as defining a graph (node(s) as V, edge(s) as E) (paragraph 43) e.g., graph 607 (fig. 6B), the graph includes a node per object as record and linking or identifying objects via edges in the graph when objects as records are identified in profiles e.g., 601 and 603 as the superblocks and (figs. 6A-6B, paragraphs , paragraphs 93-96) an relevant score between content object location and a user’s current location (paragraphs 6, 110) is below as within a threshold value (paragraphs 95-96, 100-101).
In particularly:
Data stored in the connection store 245, the user profile store 240 and the action log 230 allows the social networking system 120 to generate a social graph that uses nodes to identify various objects and edges connecting nodes to identify relationships between different objects. An edge between two nodes in the social graph represents a particular kind of connection between the two nodes, which may result from an action that was performed by one of the nodes on the other node (paragraph 43).
The social networking system 130 identifies, for a first user, a second user having a connection with the first user in the social network. To determine the connection, the social networking system 130 accesses the first user's profile 601 illustrated in FIG. 6A. In the example shown in FIG. 6A, the first user's profile 601 indicates that the first user "Erick" is friends with "John." Accordingly, the social networking system 130 locates John's user profile 603. Similarly, the second user's profile 603 indicates that John is also friends with Erick indicating a bidirectional relationship between the users (paragraph 93).
The social networking system 130 then identifies 503 an interest common to the first user and the second user. In the example shown in FIG. 6A, the social networking system 130 compares profiles 601 and 603 to identify a common interest between the profiles. The comparison indicates that Erick and John both have an interest for coffee. However, John's profile 603 further indicates that John has an interest for Starbucks coffee followed by Peets coffee and CPK coffee. The social networking system 130 determines that Starbucks is associated with "coffee" due to a Starbucks object 605 indicating that Starbucks is a sub-type of "coffee" and has a categorization of "beverage." A similar determination is made for Peets coffee and CPK coffee (paragraph 94);
Referring now to FIG. 6B, a plurality of preference graphs (i.e., interest trees) are shown for users of the social networking system 130 in order to illustrate the calculation of the relevance scores for the first user. Each preference graph represents preferences as nodes on the graph. As shown in FIG. 6B, the preference graph for Erik includes nodes for Erik's interest for "steak" and "coffee." In contrast, John's preference graph includes nodes for John's interests in the movie "Braveheart" as well as the beverages "coffee" and "tea." (paragraph 96)
“finding and outputting the connected components of graph G(V, E) as final clusters” as obtaining as finding and returning or displaying as outputting 710 third-party content objects e.g., search results (figs. 8A-8B, paragraph 109), the search results includes locations, friends or other social network connections 840 as the connected components of the social network system of (paragraph 120) graph (nodes, edges) (paragraph 101, fig. 6B), the search results, which indicates that three of their friends are at a nearby coffee shop, are represented as final clusters because based on these results a user can make a decision what to do next (paragraph 117).
In particularly:
Once the context search query and user location has been received 705 from the user, the social networking system performs a search to obtain 710 search results related to the search query. In one embodiment, performing the search involves searching an external database using a search engine to obtain the search results 710 (paragraph 109).
The ranked list of search results is displayed in a textual format 825 in addition to the graphical map 815, or instead of it. In the textual format, the ranked list of search results appear in text form, ranked according to their relevance scores. In one embodiment, the displayed ranked list of search results may be appended to include the user's social graph information, for example, likes 830 regarding a given search result, or comments 835 from friends regarding that search result. Additionally, in the case where the search results are related to locations of places or things to do, the displayed ranked list of search results may be appended to include friends or other social network connections 840 that are currently checked in at the location of that search result. For example, a search query for "restaurant" may indicate that a user has two friends who are currently eating at a nearby In-N-Out Burger (paragraph 120).
Tseng does not explicitly teach limitations
based upon one or more blocking attributes;
k-mers; a selected k value;
performing blocking on the records and placing any records with matching k-mers in the appropriate superblocks.
Ma teaches limitations
“based upon one or more blocking attributes” as forming superblocks based on blocking metadata as one or more blocking attributes (fig. 6, paragraphs 69-70);
“performing blocking on ……and placing any ……with matching ……in the appropriate superblocks” as performing blocking on MD blocks and including as placing the MD blocks with matching MD content in superblocks (fig. 6, paragraphs 70, 94, 108, 128).
In particularly:
At the step 604, blocking is performed that generates one or more MD superblocks. Each MD superblock includes MD blocks that are similar and expected to include at least some matching MD content in at least some MD blocks of the MD superblock. As described herein, one or more criteria may be used to determine similar MD blocks to be included in the same MD superblock. From the step 604, processing proceeds to the step 606 (paragraph 128).
Ma teaches further limitations
“creating superblocks based upon one or more blocking attributes” as forming superblocks based on blocking metadata as one or more blocking attributes (paragraphs 69-70).
Ma and Tseng disclose a method of receiving data and generating groups of records. Theses references are in the same field with application field. Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply Ma’s teaching to Tseng’s system in order to allow multiple host systems to access a single storage device quickly for facilitating sharing of the data on the storage device efficiently, and further to search/retrieve data from storage devices quickly.
Colley teaches limitations
the records; records (as the records: paragraph 1691);
k-mers; the k-mers (as k-mers: paragraph 5);
“a selected k value” as an identified k=30 (paragraph 5) or k=15 as a selected k value (paragraph 2190).
Colley further teaches limitations
“between the records” as between the records in each section (paragraph 1691).
Colley and Tseng disclose a method of receiving data and generating groups of records. Theses references are in the same field with application field. Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply Colley’s teaching to Tseng’s system in order to protect user data stored in a database from accessing without permission, to ensure accurate data entry entered in one or more computer systems, and further to evaluate identical portions of a data set to determine an accurate structured result for that data and/or to determine accuracy of one or more of user's attempts to structure the data.
As to claim 2, Tseng, Ma and Colley teach limitation
“wherein each record is a string of characters and a record is in multiple blocks” as each object as record is (Tseng: paragraphs 44-45) a string of characters (Colley: paragraphs 1392, 3300), a string of characters as a record is in blocks e.g., the| Cat| SAT|(Colley: paragraphs 1392, 3300) or blocks (Ma: paragraph 5).
Claim 8 has the same limitation subject matter as discussed in claim 1; thus claim 8 is rejected under the same reason as discussed in claim 1. In addition, Tseng teaches a non-transitory computer readable medium having program instructions stored thereon for sorting diverse sets of data which, when executed by a processor, causes the processor to carry out the steps of: (paragraph 149);
“defining a graph G(V, E) where there is a node per record and connecting records via an edge in the graph if they are found together in at least one of the superblocks and an edit distance between the records is within a given threshold value” as generating as defining a graph (node(s) as V, edge(s) as E) (paragraph 43) e.g., graph 607 (fig. 6B), the graph includes a node per object as record and linking or identifying objects via edges in the graph when objects as records are identified in profiles e.g., 601 and 603 as the superblocks and (figs. 6A-6B, paragraphs , paragraphs 93-96) an relevant score between content object location and a user’s current location (paragraphs 6, 110) is below as within a threshold value (paragraphs 95-96, 100-101).
In particularly:
Data stored in the connection store 245, the user profile store 240 and the action log 230 allows the social networking system 120 to generate a social graph that uses nodes to identify various objects and edges connecting nodes to identify relationships between different objects. An edge between two nodes in the social graph represents a particular kind of connection between the two nodes, which may result from an action that was performed by one of the nodes on the other node (paragraph 43).
The social networking system 130 identifies, for a first user, a second user having a connection with the first user in the social network. To determine the connection, the social networking system 130 accesses the first user's profile 601 illustrated in FIG. 6A. In the example shown in FIG. 6A, the first user's profile 601 indicates that the first user "Erick" is friends with "John." Accordingly, the social networking system 130 locates John's user profile 603. Similarly, the second user's profile 603 indicates that John is also friends with Erick indicating a bidirectional relationship between the users (paragraph 93).
The social networking system 130 then identifies 503 an interest common to the first user and the second user. In the example shown in FIG. 6A, the social networking system 130 compares profiles 601 and 603 to identify a common interest between the profiles. The comparison indicates that Erick and John both have an interest for coffee. However, John's profile 603 further indicates that John has an interest for Starbucks coffee followed by Peets coffee and CPK coffee. The social networking system 130 determines that Starbucks is associated with "coffee" due to a Starbucks object 605 indicating that Starbucks is a sub-type of "coffee" and has a categorization of "beverage." A similar determination is made for Peets coffee and CPK coffee (paragraph 94).
Claim 15 has the same limitation subject matter as discussed in claims 1, 8; thus claim 15 is rejected under the same reason as discussed in claims 1, 8. In addition, Tseng teaches apparatus for sorting diverse sets of data (paragraph 6), comprising:
“one or more processors, and memory accessible by the one or more processors, the memory storing instructions that when executed by the one or more processors, cause the apparatus to perform the method of” as a processor and storage medium as a memory accessible by the processor, the medium storing instructions when executed by the processor cause device to perform a method (paragraphs 149, 138).
As to claim 18, Tseng, Ma and Colley teach limitation
“wherein the data sources include one or more of streaming logs, user preferences, content metadata, and social media interactions” as the one or more data sources (Tseng: fig. 1, paragraphs 20, 56) or one or more resources include (Ma: paragraph 2) user preferences (Colley: paragraphs 1501, 3191)
As to claim 20, Tseng, Ma and Colley teach limitation
“wherein at least one of the one or more data sources includes biometric data” as the one or more data sources (Tseng: fig. 1, paragraphs 20, 56) or one or more resources include (Ma: paragraph 2) biometric identifiers as data (Colley: paragraph 3156).
Claims 3, 5 are rejected under 35 U.S.C. 103 as being unpatentable over Tseng in view of Ma and Colley and further in view of Thomas et al (US 20110087668)
As to claim 3, Tseng, Ma and Colley teach limitation
“wherein the superblocks are defined based upon……” as superblocks are formed based on metadata (Ma: paragraphs 69-70).
Tseng, Ma and Colley do not explicitly teach limitations
predefined criteria, the value of some parameter, or some other characteristic of the problem being solved.
Thomas teaches limitation
“predefined criteria, the value of some parameter, or some other characteristic of the problem being solved” as clusters are created based on a determination at block 506 that would be negative as predefined criteria (fig. 5, paragraph 69).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention Thomas’s teaching to Tseng’s system in order to improve resource utilization rate of a database and overall performance of database quickly and further to improve an execution efficiency of database system.
As to claim 5, Tseng, Ma and Colley teach limitation
“…….the deletion of the first character in a record……” as a deletion of a character in (Colley: paragraph 1538) an object as a record (Tseng: paragraph 18) or a file as a record (Ma: paragraph 96).
Tseng, Ma and Colley do not explicitly teach limitation
“wherein blocking on the records are adjusted to account for ……when determining whether to add records to a superblock”.
Thomas teaches limitations
“wherein blocking on the records are adjusted to account for……when determining whether to add records to a superblock” as grouping documents as blocking on the records are adjusted at step 506 if no matching x(d)[i] with X(r)[i] to account for saving hash(es), a new cluster is defined when determining whether to add documents to a selected cluster at steps 514, 1516, 518 (fig. 5, paragraphs 69-72).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention Thomas’s teaching to Tseng’s system in order to improve resource utilization rate of a database and overall performance of database quickly and further to improve an execution efficiency of database system.
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Tseng in view of Ma and Colley and further in view of Xiong et al (US 20230394027)
As to claim 4, Tseng, Ma and Colley teach limitation
“wherein blocking on the records is comprised of ……and k is the selected value for k-mers” as blocking on the MD blocks includes records and (Ma: fig. 6, paragraphs 94, 108, 128; Colley: paragraph 1691) k is 31 as the selected value for k-mers (Colley: paragraph 2774).
Tseng, Ma and Colley do not explicitly teach limitation
a total of s blocks, where s is the size of the alphabet.
Xiong teaches limitation
a total of s blocks, where s is the size of the alphabet” as total data blocks are pages (paragraph 116) with a size of 2.sup.nk, while actual data is also stored in the pages with a size of 2.sup.nk (paragraph 61).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention Xiong’s teaching to Tseng’s system in order to improve resource utilization rate of a database and overall performance of database quickly and further to improve an execution efficiency of database system.
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Tseng in view of Ma and Colley and further in view of YAMAMOTO et al (or hereinafter “Ya”) (US 20250046062).
As to claim 6, Tseng, Ma and Colley teach limitation
“……between records in blocking attributes….” as association between objects as records in (Tseng: paragraph 38) blocking metadata as attributes (Ma: paragraphs 94, 108, fig. 6).
Tseng, Ma and Colley explicitly teach limitation
wherein the edit distance can be adjusted so the edit distance ……is no more than a selected value.
Ya teaches limitation
“wherein the edit distance can be adjusted so the edit distance between records ……is no more than a selected value” as a similarity score as the edit distance, which is adjusted so that the similarity score between feature vectors of images as records is less than a threshold as a selected value (paragraphs 51-52).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention Ya’s teaching to Tseng’s system in order to improve an identification accuracy by filtering records to be input and setting only a record appropriate to be identified as an identification target.
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Tseng in view of Ma and Colley and further in view of Joyce et al (US 20220366043)
As to claim 7, Tseng, Ma and Colley teach limitation
“wherein the threshold value is calculated ……for a sample of the records” as threshold value is computed for (Tseng: paragraph 106) sample of files as sample of the records (Colley: paragraphs 1744, 2445).
Tseng, Ma and Colley do not explicitly teach limitation
using an empirical ground truth error rate.
Yoyce teaches limitation
“using an empirical ground truth error rate” as using an evaluated ground truth error rate as empirical ground truth error rate to provide ground truth confidence (paragraph 17, 26, 42).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention Joyce’s teaching to Tseng’s system in order to classify a sequence of records into events based upon feature values correctly with low rate of error.
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Tseng in view of Ma and Colley and further in view of Siebel et al (or hereinafter “Si”) (US 20210263945).
As to claim 9, Tseng, Ma and Colley teach limitation
“wherein the one or more data sources includes……” as the one or more data sources (Tseng: fig. 1, paragraphs 20, 56) or one or more resources as one or more data sources include (Ma: paragraph 2) geographic location (Colley: paragraph 991).
Tseng, Ma and Colley do not explicitly teach limitations
call data records (CDRs), network traffic, customer support interactions, geolocation data.
Si teaches limitation
“call data records (CDRs), network traffic, customer support interactions, geolocation data” as call and usage records as call data records (CDRs), network traffic (paragraph 486), customer support interactions (paragraph 452), geolocation station (paragraph 534).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention Si’s teaching to Tseng’s system in order to enable integration and processing of large and highly dynamic data sets from networks and information systems, and further to increase uptime as a result of predictive maintenance, lower maintenance costs, improved energy efficiency, and stronger user engagement.
Claims 10-12, 19 are rejected under 35 U.S.C. 103 as being unpatentable over Tseng in view of Ma and Colley and further in view of Cella et al (US 20250299255)
As to claim 10, Tseng, Ma and Colley teach limitation
“wherein the one or more data sources include……” as the one or more data sources (Tseng: fig. 1, paragraphs 20, 56) or one or more resources as one or more data sources include (Ma: paragraph 2) geographic location (Colley: paragraph 991).
Tseng, Ma and Colley do not explicitly teach limitation
purchase history, clickstreams, inventory logs, customer profiles, supply chain data.
Cella teaches limitation
“purchase history, clickstreams, inventory logs, customer profiles, supply chain data” as purchase history (paragraph 256), clickstreams (paragraph 1810), inventory accounts as logs (paragraph 334), customer profiles (paragraph 317), inventory records (paragraph 334), supply chain data (paragraph 451).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention Cella’s teaching to Tseng’s system in order to provide users with a quick and easy way to navigate digital marketplace and find records they are interested in.
As to claim 11, Tseng, Ma and Colley teach limitation
“wherein the one or more data sources include……” as the one or more data sources (Tseng: fig. 1, paragraphs 20, 56) or one or more resources as one or more data sources include (Ma: paragraph 2) geographic location (Colley: paragraph 991).
Tseng, Ma and Colley do not explicitly teach limitation
one or more of data from the Census Bureau, Social Security Administration, hospitals, healthcare providers, traffic data, transactional data, and forensic data.
Cella teaches limitation
“one or more of data from the Census Bureau, Social Security Administration, hospitals, healthcare providers, traffic data, transactional data, and forensic data” as transaction data (paragraph 2274).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention Cella’s teaching to Tseng’s system in order to provide users with a quick and easy way to navigate digital marketplace and find records they are interested in.
As to claim 12, Tseng, Ma and Colley teach limitation
“wherein the one or more data sources include ……” as the one or more data sources (Tseng: fig. 1, paragraphs 20, 56) or one or more resources as one or more data sources include (Ma: paragraph 2) geographic location (Colley: paragraph 991).
Tseng, Ma and Colley do not explicitly teach limitation
financial records, banking records, transaction logs, market feeds, risk models, fraud detection data, customer behavior.
Cella teaches limitations
“financial records, banking records, transaction logs, market feeds, risk models, fraud detection data, customer behavior” as financial records (paragraph 250), banking records (paragraph 668), transaction records as transaction logs (paragraph 1085), market factors as market feeds (paragraph 2248), risk models (paragraphs 2194, 2242), fraud detection data (paragraph 2248), customer behavior (paragraph 2194).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention Cella’s teaching to Tseng’s system in order to provide users with a quick and easy way to navigate digital marketplace and find records they are interested in.
As to claim 19, Tseng, Ma and Colley teach limitation
“wherein the one or more data sources includes……” as the one or more data sources (Tseng: fig. 1, paragraphs 20, 56) or one or more resources include (Ma: paragraph 2) geographic location e.g., geocodes as geolocation data (Colley: paragraph 991).
Tseng, Ma and Colley do not explicitly teach limitation
one or more of event logs, authentication records, network packets, malware signatures.
Cella teaches limitation “one or more of event logs, authentication records, network packets, malware signatures” as event logs (paragraph 652).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention Cella’s teaching to Tseng’s system in order to provide users with a quick and easy way to navigate digital marketplace and find records they are interested in.
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Tseng in view of Ma and Colley and further in view of Kain (US 20230252017).
As to claim 13, Tseng, Ma and Colley teach limitation
“ wherein at least one of the one or more data sources includes……” as the one or more data sources (Tseng: fig. 1, paragraphs 20, 56) or one or more resources as one or more data sources include (Ma: paragraph 2) geographic location (Colley: paragraph 991).
Tseng, Ma and Colley do not explicitly teach limitation
genomic sequences, electronic health records, imaging data, clinical trials, wearable device data.
Kain teaches limitations
“genomic sequences, electronic health records, imaging data, clinical trials, wearable device data” as genomic sequences (paragraph 89), electronic health records (paragraph 65), imaging data (paragraph 199), clinical trials (paragraph 174), wearable device data (paragraph 10).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention Kain’s teaching to Tseng’s system in order to enable users to search different types of database based on phenotypic or genomic signatures, or other data types and further to sustain or improve health and fitness of users.
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over Tseng in view of Ma and Colley and further in view of OSESINA et al (or hereafter “Os”) (US 20180137150)
As to claim 14, Tseng, Ma and Colley teach limitation
“wherein the sorting of diverse sets of data includes a linkage of records and……” as the ranking of different search results of data as diverse sets of data includes likes and comments as linkage of objects (Tseng: fig. 8C, paragraphs 120-123; Colley: paragraphs 698, 838)
Tseng, Ma and Colley do not explicitly teach limitations
resolution of entities.
Os teaches limitations
“resolution of entities” as resolution of entities (paragraph 89).
Os further teaches limitation
“a linkage of records” as linkage of data instances (paragraph 89).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention Os’s teaching to Tseng’s system in order to increase efficiencies, reduce unnecessary waste, reduce costs, improve the functioning of entity resolution systems and eliminate or reduce duplicate records.
Claim 16 is rejected under 35 U.S.C. 103 as being unpatentable over Tseng in view of Ma and Colley and further in view of Acharya (or hereinafter “Ac”) (US 20070271287).
As to claim 16, Tseng, Ma and Colley teach limitation
“wherein the one or more data sources includes……” as the one or more data sources (Tseng: fig. 1, paragraphs 20, 56) or one or more resources as the one or more data sources include (Ma: paragraph 2) geographic location (Colley: paragraph 991).
Tseng, Ma and Colley do not explicitly teach limitations
a combination of structured and unstructured data
Ac teaches limitation “a combination of structured and unstructured data” as a combination of unstructured and semi-structured information (paragraph 22).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention Ac’s teaching to Tseng’s system in order to categorize different types of data into corresponding categories efficiently, and further to further provide a system and method capable of clustering and classifying a category dataset into correct group.
Claim 17 is rejected under 35 U.S.C. 103 as being unpatentable over Tseng in view of Ma and Colley and further in view of Swamy et al (US 20210191957).
As to claim 17, Tseng, Ma and Colley teach limitation
“ wherein the one or more data sources includes……” as the one or more data sources (Tseng: fig. 1, paragraphs 20, 56) or one or more resources as the one or more data sources include (Ma: paragraph 2) geographic location (Colley: paragraph 991).
Tseng, Ma and Colley do not explicitly teach limitations
one or more of smart meter outputs, grid sensor data, consumption patterns, and equipment telemetry.
Swamy teaches limitation “one or more of smart meter outputs, grid sensor data, consumption patterns, and equipment telemetry” as consumption patterns (paragraph 25).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention Swamy’s teaching to Tseng’s system in order to provide a user with access to data based on the role of the user with respect to an operation or a unit within an organization and further to efficiently analyze data and provide a centralized data hub for enterprise data analysis.
Claims 1-2, 8, 15-16, 18, 20 are rejected under 35 U.S.C. 103 as being unpatentable over Tseng et al (US 20130013595) in view of Acharya (or hereinafter “Ac”) (US 20070271287), Kaufman et al (or hereinafter “Kau”) (US 20200104464)
As to claim 1, Tseng teaches a computer implemented method for sorting diverse sets of data (paragraph 14), comprising:
“receiving a plurality of records from one or more data sources, wherein each record includes one or more attributes associated with an entity” as receiving a plurality of objects as records from one or more third parties or providers 120 that includes one or more data sources (fig. 1, paragraphs 20, 56), each object as record includes categories, locations, and delivery time ranges as one or more attributes (paragraph 6) associated with an entity (paragraph 20);
“creating superblocks……” as storing as creating user profiles, which include information provided by user e.g., biographic, demographic, and other types of descriptive information, such as work experience, educational history, hobbies or preferences, interests, location, are represented as superblocks (paragraphs 29, 94);
“generating ……for all the records based upon……” as generating social graph including nodes in the social graph for the objects as all the records based on data stored in connection store 245, user profile store 240, and action log 230 (paragraph 43);
“defining a graph G (V, E) where there is a node per record and connecting records via an edge in the graph when records are found together in at least one of the superblock and an edit distance between the records is within a given threshold value” as generating as defining a graph (node(s) as V, edge(s) as E) (paragraph 43) e.g., graph 607 (fig. 6B), the graph includes a node per object as record and linking or identifying objects via edges in the graph when objects as records are identified in profiles e.g., 601 and 603 as the superblocks and (figs. 6A-6B, paragraphs 93-94) an relevant score between content object location and a user’s current location (paragraphs 6, 110) is below as within a threshold value (paragraphs 95-96, 100-101).
In particularly:
Data stored in the connection store 245, the user profile store 240 and the action log 230 allows the social networking system 120 to generate a social graph that uses nodes to identify various objects and edges connecting nodes to identify relationships between different objects. An edge between two nodes in the social graph represents a particular kind of connection between the two nodes, which may result from an action that was performed by one of the nodes on the other node (paragraph 43).
The social networking system 130 identifies, for a first user, a second user having a connection with the first user in the social network. To determine the connection, the social networking system 130 accesses the first user's profile 601 illustrated in FIG. 6A. In the example shown in FIG. 6A, the first user's profile 601 indicates that the first user "Erick" is friends with "John." Accordingly, the social networking system 130 locates John's user profile 603. Similarly, the second user's profile 603 indicates that John is also friends with Erick indicating a bidirectional relationship between the users (paragraph 93).
The social networking system 130 then identifies 503 an interest common to the first user and the second user. In the example shown in FIG. 6A, the social networking system 130 compares profiles 601 and 603 to identify a common interest between the profiles. The comparison indicates that Erick and John both have an interest for coffee. However, John's profile 603 further indicates that John has an interest for Starbucks coffee followed by Peets coffee and CPK coffee. The social networking system 130 determines that Starbucks is associated with "coffee" due to a Starbucks object 605 indicating that Starbucks is a sub-type of "coffee" and has a categorization of "beverage." A similar determination is made for Peets coffee and CPK coffee (paragraph 94);
“finding and outputting the connected components of graph G(V, E) as final clusters” as obtaining as finding and returning or displaying as outputting 710 third-party content objects e.g., search results (figs. 8A-8B, paragraph 109), the search results includes locations, friends or other social network connections 840 as the connected components of the social network system of (paragraph 120) graph (nodes, edges) (paragraph 101, fig. 6B), the search results, which indicates that three of their friends are at a nearby coffee shop, are represented as final clusters because based on these results a user can make a decision what to do next (paragraph 117).
In particularly:
Once the context search query and user location has been received 705 from the user, the social networking system performs a search to obtain 710 search results related to the search query. In one embodiment, performing the search involves searching an external database using a search engine to obtain the search results 710 (paragraph 109).
The ranked list of search results is displayed in a textual format 825 in addition to the graphical map 815, or instead of it. In the textual format, the ranked list of search results appear in text form, ranked according to their relevance scores. In one embodiment, the displayed ranked list of search results may be appended to include the user's social graph information, for example, likes 830 regarding a given search result, or comments 835 from friends regarding that search result. Additionally, in the case where the search results are related to locations of places or things to do, the displayed ranked list of search results may be appended to include friends or other social network connections 840 that are currently checked in at the location of that search result. For example, a search query for "restaurant" may indicate that a user has two friends who are currently eating at a nearby In-N-Out Burger (paragraph 120).
Tseng does not explicitly teach limitations
based upon one or more blocking attributes;
k-mers; a selected k value;
performing blocking on the records and placing any records with matching k-mers in the appropriate superblocks.
Ac teaches limitations
“based upon one or more blocking attributes” as generating groups or folders that contain data points are represented as superblocks based on category data including one or more attributes in a vector space (paragraphs 6, 22-25), the one or more attributes in a vector space is represented as one or more blocking attributes);
“performing blocking on the records and placing any records with ……in the appropriate superblocks” as performing clustering or grouping the records and including as placing records with category data into folders, groups or clusters as the superblocks according a predetermined entropic similarity condition in folders or clusters (paragraphs 6, 23-25).
Ac teaches further limitations
creating superblocks based upon one or more blocking attributes; the superblocks (as generating groups or folders that contain data points are represented as superblocks based on category data including one or more attributes in a vector space (paragraphs 6, 22-25), the one or more attributes in a vector space is represented as one or more blocking attributes);
“an edit distance between the records” as distance metric as edit distance between two arbitrary clusters (paragraph 92) that include the records (paragraphs 6, 23, 25).
Ac and Tseng disclose a method of receiving data and generating groups of records. Theses references are in the same field with application field. Thus, i would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention Ac’s teaching to Tseng’s system in order to categorize different types of data into corresponding categories efficiently, and further to further provide a system and method capable of clustering and classifying a category dataset into correct group.
Kau teaches limitations
k-mers; the k-mers (as k-mers: paragraph 68);
“a selected k value” as a modified k value is 31 as a selected k value (paragraph 68);
“matching k-mers” as matching k-mers (paragraphs 98, 104).
Kau and Tseng disclose a method of receiving data and generating groups of records. Theses references are in the same field with application field. Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply Kau’s teaching to Tseng’s system in order to allow a user conduct grouping and searching k-mer database located at sites quickly and further to provide queries that do not exceed limits of information contained in self-consistent k-mer database for searching efficiently.
As to claim 2, Tseng, Ac, and Kau teach limitation
“wherein each record is a string of characters and a record is in multiple blocks” as each object as record is (Tseng: paragraphs 44-45) string of words (Ac: paragraph 41, fig. 4) and a day as a record is in periods as multiple blocks (Tseng: paragraph 62).
Claim 8 has the same limitation subject matter as discussed in claim 1; thus claim 8 is rejected under the same reason as discussed in claim 1. In addition, Tseng teaches a non-transitory computer readable medium having program instructions stored thereon for sorting diverse sets of data which, when executed by a processor, causes the processor to carry out the steps of: (paragraph 149);
“defining a graph G(V, E) where there is a node per record and connecting records via an edge in the graph if they are found together in at least one of the superblocks and an edit distance between the records is within a given threshold value” as generating as defining a graph (node(s) as V, edge(s) as E) (paragraph 43) e.g., graph 607 (fig. 6B), the graph includes a node per object as record and linking or identifying objects via edges in the graph when objects as records are identified in profiles e.g., 601 and 603 as the superblocks and (figs. 6A-6B, paragraphs 93-94) an relevant score between content object location and a user’s current location (paragraphs 6, 110) is below as within a threshold value (paragraphs 95-96, 100-101).
In particularly:
Data stored in the connection store 245, the user profile store 240 and the action log 230 allows the social networking system 120 to generate a social graph that uses nodes to identify various objects and edges connecting nodes to identify relationships between different objects. An edge between two nodes in the social graph represents a particular kind of connection between the two nodes, which may result from an action that was performed by one of the nodes on the other node (paragraph 43).
The social networking system 130 identifies, for a first user, a second user having a connection with the first user in the social network. To determine the connection, the social networking system 130 accesses the first user's profile 601 illustrated in FIG. 6A. In the example shown in FIG. 6A, the first user's profile 601 indicates that the first user "Erick" is friends with "John." Accordingly, the social networking system 130 locates John's user profile 603. Similarly, the second user's profile 603 indicates that John is also friends with Erick indicating a bidirectional relationship between the users (paragraph 93).
The social networking system 130 then identifies 503 an interest common to the first user and the second user. In the example shown in FIG. 6A, the social networking system 130 compares profiles 601 and 603 to identify a common interest between the profiles. The comparison indicates that Erick and John both have an interest for coffee. However, John's profile 603 further indicates that John has an interest for Starbucks coffee followed by Peets coffee and CPK coffee. The social networking system 130 determines that Starbucks is associated with "coffee" due to a Starbucks object 605 indicating that Starbucks is a sub-type of "coffee" and has a categorization of "beverage." A similar determination is made for Peets coffee and CPK coffee (paragraph 94).
Claim 15 has the same limitation subject matter as discussed in claim 1; thus claim 15 is rejected under the same reason as discussed in claim 1. In addition, Tseng teaches apparatus for sorting diverse sets of data, comprising:
“one or more processors, and memory accessible by the one or more processors, the memory storing instructions that when executed by the one or more processors, cause the apparatus to perform the method of” as a processor and storage medium as a memory accessible by the processor, the medium storing instructions when executed by the processor cause device to perform a method (paragraphs 149, 138).
As to claim 16, Tseng, Ac, and Kau teach limitation
“wherein the one or more data sources includes a combination of structured and unstructured data” as the one or more data sources include (Tseng: fig. 1, paragraphs 20, 56) a combination of unstructured and semi-structured information (Ac: paragraph 22).
As to claim 18, Tseng, Ac and Kau teach limitation
“wherein the data sources include one or more of streaming logs, user preferences, content metadata, and social media interactions” as the one or more data sources include (Tseng: fig. 1, paragraphs 20, 56) the metadata of the sample genomes as content metadata (Kau: paragraph 109).
As to claim 20, Tseng, Ac and Kau teach limitation
“wherein at least one of the one or more data sources includes biometric data” the one or more data sources include (Tseng: fig. 1, paragraphs 20, 56) biometric readers (Kau: paragraph 160)
Claims 3, 5 are rejected under 35 U.S.C. 103 as being unpatentable over Tseng in view of Ac and Kau and further in view of Thomas et al (US 20110087668)
As to claim 3, Tseng, Ac, and Kau teach limitation
“wherein the superblocks are defined based upon……” as clusters or groups or folders that contain data points are represented as superblocks are created based on category data including one or more attributes in a vector space (Ac: paragraphs 6, 22-25).
Tseng, Ac, and Kau do not explicitly teach limitations
predefined criteria, the value of some parameter, or some other characteristic of the problem being solved.
Thomas teaches limitation
“predefined criteria, the value of some parameter, or some other characteristic of the problem being solved” as clusters are created based on a determination at block 506 that would be negative as predefined criteria (fig. 5, paragraph 69).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention Thomas’s teaching to Tseng’s system in order to improve resource utilization rate of a database and overall performance of database quickly and further to improve an execution efficiency of database system.
As to claim 5, Tseng, Ac, and Kau teach limitation
“……the deletion of the first character in a record……” as removing term(s) as the first character from each record (Ac: paragraph 44).
Tseng, Ac, and Kau do not explicitly teach limitation
“wherein blocking on the records are adjusted to account for ……when determining whether to add records to a superblock”.
Thomas teaches limitations
“wherein blocking on the records are adjusted to account for……when determining whether to add records to a superblock” as grouping documents as blocking on the records are adjusted at step 506 if no matching x(d)[i] with X(r)[i] to account for saving hash(es) a new cluster is defined when determining whether to add documents to a selected cluster at steps 514, 1516, 518 (fig. 5, paragraphs 69-72).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention Thomas’s teaching to Tseng’s system in order to improve resource utilization rate of a database and overall performance of database quickly and further to improve an execution efficiency of database system.
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Tseng in view of Ac, and Kau and further in view of Xiong et al (US 20230394027)
As to claim 4, Tseng, Ac, and Kau teach limitation
“wherein blocking on the records is comprised of ……and k is the selected value for k-mers” as blocking on records includes records and (Ac: paragraphs 6, 22-24) k is 31 as the selected value for k-mers (Kau: paragraph 68).
Tseng, Ma and Colley do not explicitly teach limitation
a total of s blocks, where s is the size of the alphabet.
Xiong teaches limitation
“a total of s blocks, where s is the size of the alphabet” as a total data blocks are pages (paragraph 116) with a size of 2.sup.nk as the alphabet, while actual data is also stored in the pages with a size of 2.sup.nk (paragraph 61).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention Xiong’s teaching to Tseng’s system in order to improve resource utilization rate of a database and overall performance of database quickly and further to improve an execution efficiency of database system.
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Tseng in view of Ac, and Kau and further in view of YAMAMOTO et al (or hereinafter “Ya”) (US 20250046062).
As to claim 6, Tseng, Ac, and Kau teaches limitation
“……between records in blocking attributes….” as association between objects as records in (Tseng: paragraph 38) blocking attributes (Ac: paragraphs 6, 23-25).
Tseng, Ac, and Kau do not explicitly teach limitation
wherein the edit distance can be adjusted so the edit distance ……is no more than a selected value.
Ya teaches limitation
“wherein the edit distance can be adjusted so the edit distance between records ……is no more than a selected value” as a similarity score as the edit distance, which is adjusted so that the similarity score between feature vectors of images as records is less than a threshold as a selected value (paragraphs 51-52).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention Ya’s teaching to Tseng’s system in order to improve an identification accuracy by filtering records to be input and setting only a record appropriate to be identified as an identification target.
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Tseng in view of Ac, and Kau and further in view of Joyce et al (US 20220366043)
As to claim 7, Tseng, Ac, and Kau teach limitation
“wherein the threshold value is calculated …… for a sample of the records” as threshold value is computed for (Tseng: paragraph 106) as sample of files (Colley: paragraphs 1744, 2445).
Tseng, Ac, and Kau do not explicitly teach limitation
using an empirical ground truth error rate
Yoyce teaches limitation
“using an empirical ground truth error rate” as using an evaluated ground truth error rate as empirical ground truth error rate to provide ground truth confidence (paragraph 17, 26, 42).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention Joyce’s teaching to Tseng’s system in order to classify a sequence of records into events based upon feature values correctly with low rate of error.
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Tseng in view of Ac, and Kau and further in view of Siebel et al (or hereinafter “Si”) (US 20210263945).
As to claim 9, Tseng, Ac, and Kau teach limitation
“wherein the one or more data sources includes……” as the one or more data sources include (Tseng: fig. 1, paragraphs 20, 56) data (Ac: paragraph 22).
Tseng, Ac, and Kau do not explicitly teach limitations
call data records (CDRs), network traffic, customer support interactions, geolocation data.
Si teaches limitation
“call data records (CDRs), network traffic, customer support interactions, geolocation data” as call and usage records as call data records (CDRs), network traffic (paragraph 486), customer support interactions (paragraph 452), geolocation station (paragraph 534).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention Si’s teaching to Tseng’s system in order to enable integration and processing of large and highly dynamic data sets from enormous sensor networks and information systems, and further to increase uptime as a result of predictive maintenance, lower maintenance costs, improved energy efficiency, and stronger user engagement.
Claims 10-12, 19 are rejected under 35 U.S.C. 103 as being unpatentable over Tseng in view of Ac, and Kau and further in view of Cella et al (US 20250299255)
As to claim 10, Tseng, Ac and Kau teach limitation
“wherein the one or more data sources include……” as the one or more data sources (Tseng: fig. 1, paragraphs 20, 56) or one or more databases comprise k-mers (Kau: paragraph 46).
Tseng, Ac, and Kau do not explicitly teach limitations
purchase history, clickstreams, inventory logs, customer profiles, supply chain data.
Cella teaches limitation
“purchase history, clickstreams, inventory logs, customer profiles, supply chain data” as purchase history (paragraph 256), clickstreams (paragraph 1810), inventory accounts as logs (paragraph 334), customer profiles (paragraph 317), inventory records (paragraph 334), supply chain data (paragraph 451).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention Cella’s teaching to Tseng’s system in order to provide users with a quick and easy way to navigate digital marketplace and find records they are interested in.
As to claim 11, Tseng, As and Kau teach limitation
“wherein the one or more data sources include……” as the one or more data sources (Tseng: fig. 1, paragraphs 20, 56) or one or more databases comprise k-mers (Kau: paragraph 46).
Tseng, Ac and Kau do not explicitly teach limitation
one or more of data from the Census Bureau, Social Security Administration, hospitals, healthcare providers, traffic data, transactional data, and forensic data
Cella teaches limitation
“one or more of data from the Census Bureau, Social Security Administration, hospitals, healthcare providers, traffic data, transactional data, and forensic data” as transaction data (paragraph 2274).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention Cella’s teaching to Tseng’s system in order to to provide users with a quick and easy way to navigate digital marketplace and find records they are interested in.
As to claim 12, Tseng, Ac and Kau teach limitation
“wherein the one or more data sources include ……” as the one or more data sources (Tseng: fig. 1, paragraphs 20, 56) or one or more databases comprise k-mers (Kau: paragraph 46).
Tseng, Ac and Kau do not explicitly teach limitation
financial records, banking records, transaction logs, market feeds, risk models, fraud detection data, customer behavior.
Cella teaches limitations
“financial records, banking records, transaction logs, market feeds, risk models, fraud detection data, customer behavior” as financial records (paragraph 250), banking records (paragraph 668), transaction records as transaction logs (paragraph 1085), market factors as market feeds (paragraph 2248), risk models (paragraphs 2194, 2242), fraud detection data (paragraph 2248), customer behavior (paragraph 2194).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention Cella’s teaching to Tseng’s system in order to provide users with a quick and easy way to navigate digital marketplace and find records they are interested in.
As to claim 19, Tseng, Ac and Kau teach limitation
“wherein the one or more data sources includes ……” as the one or more data sources (Tseng: fig. 1, paragraphs 20, 56) or one or more databases comprise k-mers (Kau: paragraph 46).
Tseng, Ac and Kau do not explicitly teach limitation
one or more of event logs, authentication records, network packets, malware signatures.
Cella teaches limitation “one or more of event logs, authentication records, network packets, malware signatures” as event logs (paragraph 652).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention Cella’s teaching to Tseng’s system in order to provide users with a quick and easy way to navigate digital marketplace and find records they are interested in.
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Tseng in view of Ac, and Kau and further in view of Kain (US 20230252017).
As to claim 13, Tseng, Ac and Kau teach limitation
“wherein at least one of the one or more data sources includes……” as the one or more data sources (Tseng: fig. 1, paragraphs 20, 56) or one or more databases comprise k-mers (Kau: paragraph 46).
Tseng, Ac and Kau do not explicitly teach limitation
genomic sequences, electronic health records, imaging data, clinical trials, wearable device data.
Kain teaches limitations
“genomic sequences, electronic health records, imaging data, clinical trials, wearable device data” as genomic sequences (paragraph 89), electronic health records (paragraph 65), imaging data (paragraph 199), clinical trials (paragraph 174), wearable device data (paragraph 10).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention Kain’s teaching to Tseng’s system in order to enable users to search different types of database based on phenotypic or genomic signatures, or other data types and further to sustain or improve health and fitness of users.
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over Tseng in view of Ac and Kau and further in view of OSESINA et al (or hereafter “Os”) (US 20180137150)
As to claim 14, Tseng, Ac and Kau teach limitation
“wherein the sorting of diverse sets of data includes a linkage of records and ….” as the ranking of different search results of data as diverse sets of data includes likes and comments as linkage of objects (Tseng: fig. 8C, paragraphs 120-123; Colley: paragraphs 698, 838)
Tseng, Ac and Kau do not explicitly teach limitations
resolution of entities.
Os teaches limitations
“resolution of entities” as resolution of entities (paragraph 89).
Os further teaches limitations
“a linkage of records” as linkage of data instances (paragraph 89).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention Os’s teaching to Tseng’s system in order to increase efficiencies, reduce unnecessary waste, reduce costs, improve the functioning of entity resolution systems and eliminate or reduce duplicate records.
Claim 17 is rejected under 35 U.S.C. 103 as being unpatentable over Tseng in view of Ac and Kau and further in view of Swamy et al (US 20210191957).
As to claim 17, Tseng, Ac and Kau teach limitation
“wherein the one or more data sources includes……” as the one or more data sources include (Tseng: fig. 1, paragraphs 20, 56) or one or more databases comprise k-mers (Kau: paragraph 46).
Tseng, Ac and Kau do not explicitly teach limitations
one or more of smart meter outputs, grid sensor data, consumption patterns, and equipment telemetry.
Swamy teaches limitation “one or more of smart meter outputs, grid sensor data, consumption patterns, and equipment telemetry” as consumption patterns (paragraph 25).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention Swamy’s teaching to Tseng’s system in order to provide a user with access to data based on the role of the user with respect to an operation or a unit within an organization and further to efficiently analyze data and provide a centralized data hub for enterprise data analysis.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CAM-Y T TRUONG whose telephone number is (571)272-4042. The examiner can normally be reached (571) 272 4042.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, SHERIEF BADAWI can be reached at (571) 272-9782. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/CAM Y T TRUONG/ Primary Examiner, Art Unit 2169
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