DETAILED ACTION
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 rejected under 35 U.S.C. § 101 are directed to an abstract idea without significantly more.
The claims do not provide significantly more than the judicial exception under the subject matter eligibility two-part statutory analysis, as provided below.
Regarding Step 1,
Step 1 addresses whether the claims are directed to one of the four statutory categories of invention, i.e., process, machine, manufacture, or composition of matter according to MPEP §2106.03. Claim 15 recites system (apparatus/machine), claim 8 recites a non-transitory computer readable medium (article of manufacture), and claim 1 recites a method (process) which all fall within one of the four statutory categories. The dependent claims are also included based on their dependencies to their respective independent claims.
Regarding Step 2A [prong 1],
The claimed invention recites an abstract idea according to MPEP §2106.04. Independent claim 1, also representative of independent claims 8 & 15 for the same abstract features, is underlined below which recite the following claim limitations, as an abstract idea.
Generating a technical requirements document from a business requirements document comprising: extracting section headers and section content from the business requirements document; extracting entities from the section content using an entities detection model; mapping the entities to technical terms using a master data dictionary; identifying key topics using topic modeling based on the section content; generating a summary of the section content by using the technical terms and section content as inputs to a model; and arranging the summary based on the key topics to generate the technical requirements document.
The underlined claim limitations, under its broadest reasonable interpretation, fall under “Certain Methods of Organizing Human Activities” grouping of abstract ideas, and includes at least managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions). See MPEP §2106.04(a)(2)(II).
But for the recitation of generic implementation of computer system components, the claimed invention merely recites a process for managing personal behavior/relationships or interactions between people because the claimed steps recite extracting information pertaining to business requirements, associating or mapping the entities to technical terms using a master data dictionary, identifying key topics using topic and providing a summary using the technical terms and section content to generate the technical requirements document. Accordingly, since the claimed invention describes a process that falls under “Certain Methods of Organizing Human Activities” grouping, the claimed invention recites an abstract idea.
Alternatively, the underlined claim limitations recite “Mental Processes” grouping of abstract ideas, which can practically be performed in the human mind and/or with the use of a physical aid such as pen and paper. The use of a physical aid (e.g., pencil and paper) to help perform a mental step (e.g., a mathematical calculation) does not negate the mental nature of the limitation. The limitations recite a mental-process type abstract idea as they can be accomplished by including an observation, evaluation, judgment, and/or opinion based on extracting information pertaining to business requirements, associating or mapping the entities to technical terms using a master data dictionary, identifying key topics using topic and providing a summary using the technical terms and section content to generate the technical requirements document.
Regarding Step 2A [prong 2],
The judicial exception is not integrated into a practical application according to MPEP §2106.04(d). Claims 1 and 9 include the following additional elements:
A system comprising: one or more processors and one or more non-transitory computer-readable media storing program instructions that, when executed by one or more processors, cause the one or more processors to perform operations, comprising: data dictionary (database) and a machine learning model.
In particular, the additional elements cited above beyond the abstract idea are recited at a high-level of generality and simply equivalent to a generic recitation and basic functionality that amount to no more than mere instructions to apply the judicial exception using generic computer technology components.
The claimed invention merely provides an abstract-idea-based-solution implemented with generic computer processes and components recited at a high-level of generality (receiving, storing, determining, and comparing data) using computer instructions to implement the abstract idea on a computer, and merely “apply it” without any meaningful technological limits or any improvement to technology, technical field or improvement to the functioning of the computer itself.
Therefore, the additional elements fail to integrate the recited abstract idea into any practical application since they do not impose any non-generic meaningful limits on practicing the abstract idea. Thus, the claimed invention is directed to an abstract idea.
Regarding Step 2B,
The claimed invention does not include additional elements that are sufficient to amount to significantly more than the judicial exception. See MPEP §2106.05.
As discussed above, the claimed additional elements recited above amounts to no more than mere instructions to implement the abstract idea by adding the words “apply it” using generic computer components and functionality. See MPEP §2106.05(h). Mere instructions to apply the judicial exception using generic computer components are insufficient to provide an inventive concept. Furthermore, the claimed additional elements merely limit the abstract idea to be executed in a computer environment, thus do nothing more than generally linking the use of a judicial exception to a particular technological environment or field of use. See MPEP §2106.05(h).
Considered as an ordered combination, the additional elements are claimed at a high-level of generality and add nothing that is not already present when the steps are considered separately. The sequence of the claimed limitations is equally generic and otherwise held to be abstract since the combination of these additional elements is no more than mere instructions to apply the judicial exception using generic computer components operating in their ordinary and generic capacities of what is typically expected of computers storing and updating data, and receiving and transmitting data between generic computer devices. The claimed invention is not patent eligible because the additional elements are merely invoked as tools to execute the abstract idea and thus are insufficient to amount to an inventive concept significantly more than the judicial exception.
As for dependent claims, they merely further narrow and reiterate the same abstract ideas for storing and updating data, and receiving and transmitting data using generic data storage and transmittal techniques with the same additional elements as recited above which provide nothing more than applying the abstract idea using generic computer technology components. Furthermore dependent claims comprise the following additional elements:
a graphical user interface;
outputting the document as an editable computer file.
These additional elements do not provide any improvement to technology, technical field or improvement to the functioning of the computer itself, and at best simply applying the abstract idea executed in a general-purpose computer environment. Therefore the dependent claims are also directed to ineligible subject matter since they do not provide significantly more than the abstract idea itself.
Thus, after considering all claim elements in Claims 1-20 both individually and as an ordered combination, it has been determined that the claimed invention as a whole, is not enough to transform the abstract idea into a patent-eligible invention since nothing in the claim limitations provide significantly more than the abstract idea under 35 U.S.C. § 101.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of pre-AIA 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(b) the invention was patented or described in a printed publication in this or a foreign country or in public use or on sale in this country, more than one year prior to the date of application for patent in the United States.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Toivanen (US 20190213407).
Regarding Claims 1, 8 and 15,
Toivanen discloses:
A system, computer-implemented method for generating a technical requirements document from a business requirements document (Abstract, Background, and Figs 1-9), one or more processors and one or more non-transitory computer-readable media storing program instructions that, when executed by one or more processors, cause the one or more processors to perform operations ([0184] processors, computer program performing tasks carried out programmatically), comprising:
extracting section headers and section content from the business requirements document; extracting entities from the section content using an entities detection model ([0020] semantic search analyzing abstracts, summaries of patents, or enhanced with technology classifications and titles, [0070] the system extracts the documents and creates feature values from the extracted documents, [0120-0123] text mining extracts a selection of documents which is then sent to modelling 122 with the use of classification engine 150, such as LDA, generates topics in the modelling. [0135] title filtering field of all the documents, [0102] extracting the description section of each patent document, with lexical analysis, and this extracted and filtered data is used as a input to preprocessing and tokenization);
mapping the entities to technical terms using a master data dictionary; identifying key topics using topic modeling based on the section content ([0104] the tokenized data from the extracted documents is input to the selected classifier, [0094] analyzing of the extracted data using NLP and machine learning techniques for a modeled knowledge base or map to identify areas of interest for technology, [0096] means 102 for automatically identifying documents in data warehouses and defining identification models to a reference document database 122, [0103] Each unique word in the whole input is assigned to a unique id creating a dictionary of unique words represented by integer tokens. Using the dictionary created patent documents are converted to a vector of ids, [0124] data created by the modelling is integrated to the knowledge database 120 via a unique identified, all data and information created by the modelling can be associated and connected to bibliographic information, [0125] modelling creates machine readable data and information that are used to create visualizations, landscapes, and maps of the document collection, [0127] machine learning generated topics provided by visualizations of each topics, the visualizations are created by generating a word cloud from the full-text description of patents assigned to a given topic, or from other elements in the patent document such as technology classifications, titles, abstracts identified);
generating a summary of the section content by using the technical terms and section content as inputs to a machine learning model; and arranging the summary based on the key topics to generate the technical requirements document ([0111] Creating automated compiled documents can be achieved by machine based summary of documents relevant to the key terms, and training a neural network model to create a synthetic document, [0105] the classified data of the full data can be evaluated by parameters based on the classifier model and can include automated summaries and/or word clouds [0127-0131] the machine learning generated topics are by accessing visualizations of each topics. The visualizations are created by generating a word cloud visual document of technical terms and keywords from the full-text description of patents assigned to a given topic, or from other elements in the patent document such as technology classifications, titles, abstracts, providing what technology and business areas each topic represents).
Regarding Claims 2 & 9 and 16, further comprising providing a graphical user interface configured to prompt a user to input the business requirements document ([0094] the created model can be used, modified, updated, analyzed and visualized through a graphical user interface, [0143-0150] Through the GUI the user can access the network visualization or other landscape visualization, and explore how different topics are related. Furthermore, the user can explore the document collection in the landscape as it includes representations of the modelling created data and information, as well as on each collection document included in the model and the user can input Boolean search terms in the patent description to enable relevant documents)
Regarding Claims 3 & 10 and 17, further comprising identifying a document type of the business requirements document using a classifier model, wherein the classifier model uses layout metadata of the business requirements document as an input ([0149] modelling generated classification data, [0007] Machine-learning based classification analyzing vast amounts of data rapidly and to generate knowledge model, [0030] records are chosen for modelling based on their combined classification in a matrix established by automated classification, [0034-0035] automatically identifying input documents in data warehouses comprising similar structured data forms as said structured collection data form, means for preprocessing and tokenizing said input documents, and the automated analysis system comprises a classification engine using the tokenized and preprocessed documents as input classifying each item of the input documents).
Regarding Claims 4 & 11 and 18, wherein extracting the section headers and the section content from the business requirements document comprises automatically distinguishing between the section headers and the section content based on font and layout information of the business requirements document ([0127] machine learning generated topics provided by visualizations of each topics, the visualizations are created by generating a word cloud from the full-text description of patents assigned to a given topic, or from other elements in the patent document such as technology classifications, titles, abstracts identified sections).
Regarding Claims 5 & 12, wherein the entities detection model is a custom entities detection model adapted from a pre-trained entities detection model, the method comprising adapting the pre-trained entities detection model by providing a machine learning training processes using a dataset including custom entities associated with sample section content ([0127-0131] the machine learning generated topics are by accessing visualizations of each topics. The visualizations are created by generating a word cloud visual document of technical terms and keywords from the full-text description of patents assigned to a given topic, or from other elements in the patent document such as technology classifications, titles, abstracts, providing what technology and business areas each topic represents).
Regarding Claims 6 & 13 and 19, wherein the master data dictionary comprises the technical terms, the technical terms relate to software engineering, and mapping the entities to the technical terms comprises applying a data clustering approach ([0103] Each unique word in the whole input is assigned to a unique id creating a dictionary of unique words represented by integer tokens. Using the dictionary created patent documents are converted to a vector of ids, [0124] data created by the modelling is integrated to the knowledge database 120 via a unique identified, all data and information created by the modelling can be associated and connected to bibliographic information, [0139] modelling exports automatically nodes and edges data compatible with the visualization using data clustering, [0115] the bipartite graph can be also relational between item or classes and the visualization can also be clustered using a modularity algorithm).
Regarding Claims 7 & 14 and 20, further comprising outputting the technical requirements document to a user as an editable computer file ([0125] modelling outputs and stores such data and information by at least one of the following methods: automatically semi-automatically or by user prompt directly to a database, [0145] GUI to display information on the said collection document. The user can save selected records to a specific MyList or MyCollection).
Conclusion
The relevant prior art made of record not relied upon but considered pertinent to applicant's disclosure can be found in the current and/or previous PTO-892 Notice of References Cited. Any inquiry concerning this communication or earlier communications from the Examiner should be directed to LAURA YESILDAG whose direct telephone number is (571) 270-5066 and work schedule is generally Monday-Friday, from 9:00 AM - 5:00 PM ET.
US20200019643 Dynamic modification of information presentation and linkage based on usage patterns and sentiments
US20160034757 Generating an Academic Topic Graph from Digital Documents
Jain, Sarika. "Exploiting knowledge graphs for facilitating product/service discovery." arXiv preprint arXiv:2010.05213 (2020).
T. Shaik et al., "A Review of the Trends and Challenges in Adopting Natural Language Processing Methods for Education Feedback Analysis," in IEEE Access, vol. 10, pp. 56720-56739, 2022.
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/LAURA YESILDAG/Primary Examiner, Art Unit 3629