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.
Claim 1 is rejected under 35 U.S.C. 101 because the claimed invention is directed to a mental process without significantly more.
The claims recites:
“1. A computer implemented method for processing information related to an extract- transform-load (ETL) data migration, the method comprising:
loading a business object definition, wherein said business object definition comprises a set of table definitions, wherein each table definition comprises a plurality of column definitions and wherein each column definition comprises a first natural language descriptor;
loading a plurality of database table definitions wherein said database table definition comprises a plurality of database column definitions and wherein each database column definition comprises a second natural language descriptor;
using a first TF vectorizer to convert a first text in said first descriptor into a first numerical vector based one or more TF-IDF scores of a plurality of words in said first descriptor;
using a second TF vectorizer to convert a second text in said second descriptor into a second numerical vector based one or more TF-IDF scores of a plurality of words in said second descriptor;
creating a quantum superposition of said first vector and said second vector; and
encoding a distance between said first vector and said second vector into an amplitude of each vector in said superposition.”
This is a mental process because the claimed “using a first TF vectorizer to convert a first text in said first descriptor into a first numerical vector based one or more TF-IDF scores of a plurality of words in said first descriptor” and “using a second TF vectorizer to convert a second text in said second descriptor into a second numerical vector based one or more TF-IDF scores of a plurality of words in said second descriptor” are both mental process steps because a human being equipped with pen and paper or a computer is capable of performing the data analyses necessary to convert data into numerical vectors. The “creating a quantum superposition of said first vector and said second vector” and “encoding a distance between said first vector and said second vector into an amplitude of each vector in said superposition” similarly appear to be the result of inputting data into a data analysis function and producing a result. All of these steps may be performed by a human being equipped with pen and paper or a generic computer to perform the claimed functions using the claimed input to produce the claimed output.
The claim contains an additional element beyond the mental process in the form of the “loading a business object definition, wherein said business object definition comprises a set of table definitions, wherein each table definition comprises a plurality of column definitions and wherein each column definition comprises a first natural language descriptor” step.
This judicial exception is not integrated into a practical application because the claimed additional elements do not appear to improve the processing of a computer, require the use of a specific machine, effect a transformation or reduction of a particular article to a different state or thing, or provide a technological solution to a technological problem.
The “loading a business object definition…” step appears to be a data gathering step, and is thus mere pre-solution insignificant activity (see MPEP 2106.05(g).
It is noted that the additional element does not appear to improve the processing of a computer, require the use of a specific machine, effect a transformation or reduction of a particular article to a different state or thing, or provide a technological solution to a technological problem. As such, the additional element does not appear to integrate the judicial exception into a practical application.
None of the additional elements are sufficient to amount to significantly more than the judicial exception, in part or in whole.
The “loading a business object definition…” step is merely extra-solution activity data gathering and is well understood, routine, and conventional (see MPEP 2106.05(g)).
None of the additional elements, in part or in whole, appear to improve the processing of a computer, require the use of a particular machine, effect a transformation or reduction of a particular article to a different state or thing, or add a specific limitation other than what is well understood, routine, or conventional. As such, none of the additional elements appears to be, in part or in whole, significantly more than the judicial exception.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim 1 is rejected under 35 U.S.C. 103 as being unpatentable over Hoang et al. (US Pre-Grant Publication 2025/0291772) in view of Sajid et al. (US Pre-Grant Publication 2025/0004922) and further in view of Clapis et al. (US Pre-Grant Publication 2023/0325704).
As to claim 1, Hoang teaches a computer implemented method for processing information related to an extract- transform-load (ETL) data migration, the method comprising:
loading a business object definition, wherein said business object definition comprises a set of table definitions, wherein each table definition comprises a plurality of column definitions and wherein each column definition comprises a first natural language descriptor (see Hoang paragraphs [0031], [0034], [0045], and [0054]-[0055]. A database schema is loaded into the system, see paragraphs [0054]-[0055]. As noted in paragraph [0045], database schemas may comprise multiple table definitions with multiple columns. Paragraph [0071] describes how database column definitions include lines and text and may include comments. The comments may be in natural language);
loading a plurality of database table definitions wherein said database table definition comprises a plurality of database column definitions and wherein each database column definition comprises a second natural language descriptor (see Hoang paragraphs [0045], [0054]-[0055], and [0071]. Column definitions may exist, wherein the column definitions include lines of text and a comment);
using a first TF vectorizer to convert a first text in said first descriptor into a first numerical vector based one or more … of a plurality of words in said first descriptor (see paragraphs [0071]-[0073]. Vector encodings may be calculated based on column definitions);
using a second TF vectorizer to convert a second text in said second descriptor into a second numerical vector based one of a plurality of words in said second descriptor (see paragraphs [0071]-[0073]. Vector encodings may be calculated based on column definitions);
…
Hoang does not explicitly teach:
using a first TF vectorizer to convert a first text in said first descriptor into a first numerical vector based one or more TF-IDF scores of a plurality of words in said first descriptor;
using a second TF vectorizer to convert a second text in said second descriptor into a second numerical vector based one or more TF-IDF scores of a plurality of words in said second descriptor;
creating a quantum superposition of said first vector and said second vector; and
encoding a distance between said first vector and said second vector into an amplitude of each vector in said superposition
Sajid teaches:
using a first TF vectorizer to convert a first text in said first descriptor into a first numerical vector based one or more TF-IDF scores of a plurality of words in said first descriptor (see Sajid paragraphs [0030]-[0032]. As noted in paragraph [0030]-[0031], a mapping may be formed into a matrix wherein values are calculated using TF-IDF from words in a description of data. Paragraph [0032] shows that these values may be used as TF-IDF weighted vectors to determine similarity);
using a second TF vectorizer to convert a second text in said second descriptor into a second numerical vector based one or more TF-IDF scores of a plurality of words in said second descriptor (see Sajid paragraphs [0030]-[0032]. As noted in paragraph [0030]-[0031], a mapping may be formed into a matrix wherein values are calculated using TF-IDF from words in a description of data. Paragraph [0032] shows that these values may be used as TF-IDF weighted vectors to determine similarity);
As noted above, Hoang teaches the creation of vectors. Hoang does not teach the use of TF-IDF to calculate the vectors. Sajid teaches the use of TF-IDF vectors to calculate similarity between elements of data. It would have been obvious to one of ordinary skill in the art before the earliest filing date of the invention to have modified Hoang by the teachings of Sajid because both references are directed towards linguistic analysis between vectors to identify similarity. Sajid simply provides to Hoang additional ways to calculate linguistic similarity, which will give an administrator of Hoang additional options to use when determining the best way to identify similarity amongst data elements.
Clapis teaches:
creating a quantum superposition of said first vector and said second vector (see paragraph [0079]. A superposition of multiple component vectors may be calculated); and
encoding a distance between said first vector and said second vector into an amplitude of each vector in said superposition (see paragraph [0079]. Clapis teaches that “The quantum state described by the state vector may be a superposition (sum) of multiple component vectors describing the possible measurement outcomes of the quantum computing system with their associated amplitude and phase.” Clapis later describes how an amplitude may be included. Clapis also notes that the state vectors may include multiple types of mathematical information, including scaling factors. While Clapis does not explicitly say distance is such a factor, it is noted that Hoang, previously cited above, teach to calculate and store a distance between two vectors in a vector store (see Hoang paragraph [0073]. Combined, the references teach the claimed subject matter)).
As noted above, Hoang teaches the creation of vectors. Hoang does not teach analyzing the vectors in a quantum system. Clapis teaches to analyze vectors in a quantum framework. It would have been obvious to one of ordinary skill in the art before the earliest filing date of the invention to have modified Hoang by the teachings of Clapis because both references are directed towards analysis of vectors. Clapis simply provides to Hoang ways of analyzing data that may be much faster than classical computers (see Clapis paragraph [0002]). This will improve the speed and efficiency of Hoang.
Conclusion
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/CHARLES D ADAMS/ Primary Examiner, Art Unit 2152