DETAILED ACTION
This non-final rejection is responsive to the claims filed 13 September 2024. Claims 1-20 are pending. Claims 1, 8, and 15 are independent claims.
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 .
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.
Regarding Claim 1
Step 1
According to the first part of the analysis, in the instant case, claims 1-7 are directed to a method, and claim 8-14 are directed to a system, and claims 15-20 are directed to a computer-readable storage medium. Thus, each of the claims falls within one of the four statutory categories (i.e., process, machine, manufacture, or composition of matter).
Step 2A, Prong One
filtering out search queries from the unfiltered search queries that do not contain a keyword to create a set of queries that all contain the keyword, wherein the keyword identifies a topic of analysis; (This step captures filtering values and it is practically implementable in the human mind or with the help of pen and paper and is understood to be a recitation of a mental process (i.e., judgment).)
removing stop words and the keyword from query contents of the raw search query; (This step capturing removing filler words and keywords, which is a mental process.)
representing the raw search query as a multidimensional feature vector after removal of the stop words and the keyword; and (This step captures a mathematical concept, i.e. assigning a vector.)
classifying the multidimensional feature vector into one of a plurality of categories (This step captures assigning a category to the vector, which is a mental process.)
Step 2A Prong 2: This judicial exception is not integrated into a practical application.
receiving unfiltered search queries related to multiple topics; (This step is directed to receiving information, which is understood to be insignificant extra-solution activity and data gathering. See MPEP 2106.05(g).)
... using a machine learning classifier; (Using a machine learning classifier is understood to be a field of use limitation. See MPEP 2106.05(h).)
Step 2B
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because when considered separately and in combination, they do not add significantly more (also known as an “inventive concept”) to the exception. The claim recites additional limitations that are directed to receiving or transmitting data over a network, these are well-understood, routine, conventional computer functions as recognized by the court decisions listed in MPEP § 2106.05(d).
Regarding Claim 2
Step 2A Prong One: The claim does not recite any mental steps.
Step 2A Prong Two:
wherein the raw search query is a query directed to an Internet search engine and the multidimensional feature vector is generated by a neural network trained on other Internet search queries. (This step is a field of use limitation, i.e. the query of an internet search engine and the usage of a neural network.)
Step 2B:
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because when considered separately and in combination, they do not add significantly more (also known as an “inventive concept”) to the exception.
Regarding Claim 3
Step 2A Prong One:
wherein the raw search query comprises a geolocation and further comprising: assigning the raw search query to a geographic region based on the geolocation; and (This step captures organizing the queries by location, which is a mental process.)
counting a total number of search queries, including the raw search query, in the geographic region that are classified in a same one of the plurality of categories. (This step captures a mathematical concept, i.e. counting the number of queries.)
Step 2A Prong Two:
The claim does not recite any additional elements.
Step 2B:
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because when considered separately and in combination, they do not add significantly more (also known as an “inventive concept”) to the exception.
Regarding Claim 4
Step 2A Prong One:
wherein the topic of analysis is job searching. (This step further narrows the mental process to specific types of topics.)
Step 2A Prong Two:
This step does not recite any additional elements.
Step 2B:
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because when considered separately and in combination, they do not add significantly more (also known as an “inventive concept”) to the exception.
Regarding Claim 5
Step 2A Prong One:
wherein the keyword is job, jobs, employment, career, or careers. (This step further narrows the mental process to specific types of keywords.)
Step 2A Prong Two:
This step does not recite any additional elements.
Step 2B:
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because when considered separately and in combination, they do not add significantly more (also known as an “inventive concept”) to the exception.
Regarding Claim 6
Step 2A Prong One:
wherein the plurality of categories includes architecture/engineering, art, business, construction, education, finance, food, healthcare, leisure/hospitality, manufacturing, retail, science, technology, and transportation. (This step further narrows the mental process to specific types of categories.)
Step 2A Prong Two:
This step does not recite any additional elements.
Step 2B:
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because when considered separately and in combination, they do not add significantly more (also known as an “inventive concept”) to the exception.
Regarding Claim 7
Step 2A Prong One:
wherein the machine learning classifier is a support vector machine trained on labeled data. (Classifying using a support vector machine is a mathematical concept.)
Step 2A Prong Two:
machine learning (Using machine learning is a field of use limitation)
Step 2B:
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because when considered separately and in combination, they do not add significantly more (also known as an “inventive concept”) to the exception.
Similar analysis applies to claims 8-20. Furthermore, claims 8-20 recite processing units, memory, and a computer-readable medium. The foregoing is understood to be generic computer equipment under MPEP 2106.05(f). The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because when considered separately and in combination, they do not add significantly more (also known as an “inventive concept”) to the exception.
Double Patenting
A rejection based on double patenting of the “same invention” type finds its support in the language of 35 U.S.C. 101 which states that “whoever invents or discovers any new and useful process... may obtain a patent therefor...” (Emphasis added). Thus, the term “same invention,” in this context, means an invention drawn to identical subject matter. See Miller v. Eagle Mfg. Co., 151 U.S. 186 (1894); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Ockert, 245 F.2d 467, 114 USPQ 330 (CCPA 1957).
A statutory type (35 U.S.C. 101) double patenting rejection can be overcome by canceling or amending the claims that are directed to the same invention so they are no longer coextensive in scope. The filing of a terminal disclaimer cannot overcome a double patenting rejection based upon 35 U.S.C. 101.
Claims 1-20 provisionally rejected under 35 U.S.C. 101 as claiming the same invention as that of claims 14-20 of copending Application No. 17859906. This is a provisional statutory double patenting rejection since the claims directed to the same invention have not in fact been patented.
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, 9, 15, and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Sercinoglu (US 2011/0040733 A1) hereinafter known as Sercinoglu in view of Thakur (US 9,767,182 B1) hereinafter known as Thakur in view of Go (Twitter Sentiment Classification using Distant Supervision, attached as pdf) hereinafter known as Go.
Regarding independent claim 1, Sercinoglu teaches:
receiving unfiltered search queries related to multiple topics; (Sercinoglu: ¶[0030]; Sercinoglu teaches a query log of a plurality of search queries.)
filtering out search queries from the unfiltered search queries that do not contain a keyword to create a set of queries that all contain the keyword, wherein the keyword identifies a topic of analysis; (Sercinoglu: ¶[0038]-¶[0039] and ¶[0067]; Sercinoglu teaches being able to search the session records using query terms.)
...
...
...
Sercinoglu does not explicitly teach but Thakur teaches:
removing stop words and the ... from query contents of the raw search query; (Thakur: col. 15, lines 64-67 to col. 16, lines 1-24; Thakur teaches deleting terms and stopwords from the search queries.)
representing the raw search query as a multidimensional feature vector after removal of the stop words and the keyword; and (Thakur: col. 17, lines 4-24; Thakur teaches converting the search queries into a plurality of training sets that comprise vectors.)
classifying the multidimensional feature vector into one of a plurality of categories using a machine learning classifier. (Thakur: col. 17, lines 4-24; Thakur teaches converting the search queries into a plurality of training sets that comprise vectors and using this search query classification to process new queries into categories using machine learning.)
Sercinoglu and Thakur are in the same field of endeavor as the present invention, as the references are directed to classifying and categorizing multiple search queries. It would have been obvious, before the effective filing date of the claimed invention, to a person of ordinary skill in the art, to combine a method for receiving search queries and filtering the queries based on keywords as taught in Sercinoglu with removing the stop words from the query contents; representing the queries as multidimensional vectors; and classifying the vectors into categories using a machine learning classifier as taught in Thakur. Thakur provides this additional functionality. As such, it would have been obvious to one of ordinary skill in the art to modify the teachings of Sercinoglu to include teachings of Thakur because the foregoing would allow removing irrelevant terms, as suggested by Thakur: col. 16, lines 1-35.
Sercinoglu in view of Thakur does not explicitly teach but Go teaches:
... keyword ... (Go: 2.2 and 4.1; Go teaches stripping out the emoticons from the search queries.)
Go is in the same field of endeavor as the present invention, since it is directed to classifying and categorizing multiple search queries. It would have been obvious, before the effective filing date of the claimed invention, to a person of ordinary skill in the art, to combine a method for receiving search queries; filtering the queries based on keywords; and removing stop words as taught in Sercinoglu in view of Thakur with further removing the keywords from the query as taught in Go. As such, it would have been obvious to one of ordinary skill in the art to modify the teachings of Sercinoglu and Thakur to include teachings of Go because the foregoing would allow classifying based on other features of the query, as suggested by Go: 2.2.
Regarding claim 2, Sercinoglu in view of Thakur in view of Go further teaches the method of claim 1.
Thakur further teaches:
wherein the raw search query is a query directed to an Internet search engine and the multidimensional feature vector is generated by a neural network trained on other Internet search queries. (Thakur: col. 8, lines 60-67 to col. 9, lines 1-16; Thakur teaches using the Word2Vec model which may be implemented by neural networks. Col. 19, lines 57-60 and col. 2, lines 18-24 teach the query directed to search engines.)
Regarding claims 8, 9, 15, and 16, these claims recite a system and a computer-readable storage medium that performs the method of claims 1 and 2; therefore, the same rationale for rejection applies. Sercinoglu further teaches (Fig. 11B) a processing unit and memory.
Claims 3, 10, and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Sercinoglu in view of Thakur in view of Go in view of Mehta (US 8,145,623 B1) hereinafter known as Mehta.
Regarding claim 3, Sercinoglu in view of Thakur in view of Go further teaches the method of claim 1.
Sercinoglu in view of Thakur in view of Go does not explicitly teach but Mehta teaches:
wherein the raw search query comprises a geolocation and further comprising: assigning the raw search query to a geographic region based on the geolocation; and counting a total number of search queries, including the raw search query, in the geographic region that are classified in a same one of the plurality of categories. (Mehta: Fig. 8 and col. 19, lines 65-67 to col. 20, lines 1-18; Mehta teaches a memory with the processor. Col. 5, lines 65-67 to col. 6, liens 1-10 further teach a query log 116 which stores data related to search queries submitted to the search system wherein the data is specific to geographical regions, as further detailed in col. 3, lines 38-50. Col. 10, lines 67-68 to col. 11, lines 1-7 further teach presenting a number of representative queries to the user under each category. Further, col. 11, lines 8-12 teach that filters are used to create query listings specific to a geographical area or a wider geographical area.)
Mehta is in the same field of endeavor as the present invention, since it is directed to classifying and categorizing multiple search queries. It would have been obvious, before the effective filing date of the claimed invention, to a person of ordinary skill in the art, to combine a method for receiving search queries; filtering the queries based on keywords; and removing stop words and keywords; and converting the search queries to vector to classify into categories as taught in Sercinoglu in view of Thakur in view of Go with the query comprising a geolocation as taught in Mehta. As such, it would have been obvious to one of ordinary skill in the art to modify the teachings of Sercinoglu, Thakur, and Go to include teachings of Mehta because the foregoing would allow narrowing down the queries to a geographical region, as suggested by Mehta: col. 5, lines 65-67 to col. 6, lines 1-10 and col. 3, lines 38-50.
Regarding claims 10 and 17, these claims recite a system and a computer-readable storage medium that performs the method of claim 3; therefore, the same rationale for rejection applies.
Claims 4, 5, 11, 12, and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Sercinoglu in view of Thakur in view of Go in view of Cheng (US 10,409,866 B1) hereinafter known as Cheng.
Regarding claim 4, Sercinoglu in view of Thakur in view of Go further teaches the method of claim 1.
Sercinoglu in view of Thakur in view of Go does not explicitly teach but Cheng teaches:
wherein the topic of analysis is job searching. (Cheng: Figs. 2-3 and col. 5, lines 35-51; Cheng teaches job queries entered by users which are then converted to a normalized occupation.)
Cheng is analogous prior at to the present invention since Cheng is reasonably pertinent to the problem faced by the inventor, i.e. visualizing categorized data inputted by many users. It would have been obvious, before the effective filing date of the claimed invention, to a person of ordinary skill in the art, to combine a method for receiving search queries; filtering the queries based on keywords; and removing stop words and keywords; and converting the search queries to vector to classify into categories as taught in Sercinoglu in view of Thakur in view of Go with the search queries comprising job search and the categories comprising job categories as taught in Cheng. As such, it would have been obvious to one of ordinary skill in the art to modify the teachings of Sercinoglu, Thakur, and Go to include teachings of Cheng because such a combination would allow the mapping of multiple different job search queries to occupations, as suggested by Cheng: col. 2, lines 10-23.
Regarding claim 5, Sercinoglu in view of Thakur in view of Go in view of Cheng further teaches the method of claim 4.
Cheng further teaches:
wherein the keyword is job, jobs, employment, career, or careers. (Cheng: Figs. 2-3 and col. 5, lines 35-51; Cheng teaches job queries entered by users which are then converted to a normalized occupation.)
Regarding claims 11, 12, and 18, these claims recite a system and a computer-readable storage medium that performs the method of claims 4 and 5; therefore, the same rationale for rejection applies.
Claims 6, 13, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Sercinoglu in view of Thakur in view of Go in view of Lawton (US 2002/0080187 A1) hereinafter known as Lawton.
Regarding claim 6, Sercinoglu in view of Thakur in view of Go further teaches the method of claim 1.
Sercinoglu in view of Thakur in view of Go does not explicitly teach but Lawton teaches:
wherein the plurality of categories includes architecture/engineering, art, business, construction, education, finance, food, healthcare, leisure/hospitality, manufacturing, retail, science, technology, and transportation. (Lawton: Fig. 4b; Lawton further teaches Engineering & Architecture, Media & Arts, Management, Construction, Education ,Food, Health, Food & Lodging, Manufacturing, Sales, Science, Computer/IT, and Transportation, respectively.)
Lawton is analogous prior at to the present invention since Lawton is reasonably pertinent to the problem faced by the inventor, i.e. processing search queries and determining appropriate categories for the queries. It would have been obvious, before the effective filing date of the claimed invention, to a person of ordinary skill in the art, to combine a method for receiving search queries; filtering the queries based on keywords; and removing stop words and keywords; and converting the search queries to vector to classify into categories as taught in Sercinoglu in view of Thakur in view of Go with the categories including architecture/engineering, art, business, construction, education, finance, food, healthcare, leisure/hospitality, manufacturing, retail, science, technology, and transportation as taught in Lawton. As such, it would have been obvious to one of ordinary skill in the art to modify the teachings of Sercinoglu, Thakur, and Go to include teachings of Lawton because such a combination would allow categorization into a wider variety of categories.
Regarding claims 13 and 19, these claims recite a system and a computer-readable storage medium that performs the method of claim 6; therefore, the same rationale for rejection applies.
Claims 7, 14, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Sercinoglu in view of Thakur in view of Go in view of Thiesson (US 2007/0255552 A1) hereinafter known as Thiesson.
Regarding claim 7, Sercinoglu in view of Thakur in view of Go further teaches the method of claim 1.
Sercinoglu in view of Thakur in view of Go does not explicitly teach but Thiesson teaches:
wherein the machine learning classifier is a support vector machine trained on labeled data. (Thiesson: ¶[0035]-¶[0037]; Thiesson teaches using the support vector machine as a classifier.)
Thiesson is analogous prior at to the present invention since Thiesson is reasonably pertinent to the problem faced by the inventor, i.e. using machine learning classifiers to classify data. It would have been obvious, before the effective filing date of the claimed invention, to a person of ordinary skill in the art, to combine a method for receiving search queries; filtering the queries based on keywords; and removing stop words and keywords; and converting the search queries to vector to classify into categories as taught in Sercinoglu in view of Thakur in view of Go with using the support vector machine as a classifier as taught in Thiesson. As such, it would have been obvious to one of ordinary skill in the art to modify the teachings of Sercinoglu, Thakur, and Go to include teachings of Thiesson because such a combination would allow the use of different and efficient classifiers to classify data.
Regarding claims 14 and 20, these claims recite a system and a computer-readable storage medium that performs the method of claim 7; therefore, the same rationale for rejection applies.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ALEX OLSHANNIKOV whose telephone number is (571)270-0667. The examiner can normally be reached M-F 9:30-6.
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/ALEKSEY OLSHANNIKOV/Primary Examiner, Art Unit 2118
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