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 .
Status of Claims
This action is in reply to the communications filed on 01/05/2026.
Claims 1, 3-7, 9-10, 12, and 14-19 have been amended.
Claims 2, 8, 11, and 13 have been cancelled.
Claims 20 has been added.
Claims 1, 3-7, 9-10, 12, and 14-20 are currently pending and have been examined.
Response to Applicant’s Remarks
Applicant’s arguments and remarks filed on 01/05/2026 have been fully considered and each argument will be respectfully addressed in the following final office action.
Response to Claim Objection Remarks
Applicant’s remarks filed on page 7 of the Response concerning the objection to claim 14 have been fully considered and are found persuasive. In view of the amendments to the claim, the claim objection has been withdrawn herein.
Response to 35 U.S.C. § 112(a) and (b) Remarks
Applicant’s remarks filed on pages 7-8 of the Response concerning the 35 U.S.C. § 112 (a) and (b) rejections of the claims have been fully considered but are found not persuasive. The amendments to the claims fail to address or overcome the corresponding § 112 (a) and (b) rejections of the claims. Accordingly, the corresponding § 112(a) and (b) rejections have been maintained herein.
Response to 35 U.S.C. § 101 Remarks
Applicant’s remarks filed on pages 8-9 of the Response concerning the 35 U.S.C. § 101 rejections of the claims have been fully considered but are found not persuasive.
On pages 8-9 of the Response, the Applicant argues the amendments to independent claim 1 “defines a concrete data-processing architecture rather than a mental process […] Humans cannot perform these computational conversions or weighted aggregations with the precision and speed achieved by the configured computing device” and the “claimed operations therefore represent an improvement over computer-implemented evaluation systems […] the computer itself now perform weighting generation and normalization internally, ensuring consistent results and reduced computational overhead”.
The Examiner respectfully disagrees that independent claim 1 does not recite a mental process, and that the additional elements of the claim reflect an improvement to technology. Firstly, the Examiner notes that “claiming the improved speed or efficiency inherent with applying the abstract idea on a computer does not integrate a judicial exception into a practical application or provide an inventive concept” (see MPEP 2106.05(f)(2)), and that “Claims can recite a mental process even if they are claimed as being performed on a computer” (see MPEP 2106.04(a)(2)(III)(C). Claim 1, as currently drafted, recites steps for organizing information (i.e., a feature list comprising a plurality of individual and distinct features corresponding to characteristics/qualities of a subject relevant to a decision), collecting information (i.e., receiving data entered by a user representing an ordering or arrangement of features on a feature list, and receiving a quantitative value entered by the user for each respective feature), and analyzing information (i.e., processing the received information according to calculation rules so as to generate a global decision score for the subject) – which is the abstract idea of mental processes. See MPEP 2106.04(a)(2)(III). A human, using mental steps with the aid of pen and paper, is reasonably capable of collecting information and analyzing information according to “calculation rules” as currently recited in the claims. There is nothing in the claim to suggest the performance of a calculation that would be beyond of the scope of human capabilities because a human using mental steps is reasonably capable of following “calculation rules” to arrive at a mathematical result.
The additional elements of the claim merely include a “system” configured to perform the claimed mental processes. The “system” is recited at a high level of generality such that it is merely considered as a generic computer tool executing high level computer instructions to apply the abstract idea. Moreover, the “system” is merely recited as a generic computer tool being utilized in its ordinary capacity to apply the abstract idea. The Examiner notes “Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more” (MPEP 2106.05 (f)). Thus, the utilization of a generic computer tool (i.e. “the system”) to perform the abstract idea of collecting and processing information, when considered as a whole/ordered combination, is not considered to be a technical improvement to the computer itself and, as such, cannot be considered to integrate the abstract idea into a practical application or provide significantly more.
Response to 35 U.S.C. § 103 Remarks
Applicant’s remarks filed on pages 9-10 of the Response concerning the 35 U.S.C. § 103 rejections of the claims have been fully considered but are moot in view of the amended § 103 rejection of the amended claims.
On pages 9-10 of the Response, the Applicant argues that the prior art of record, namely Gross and Wade, do not teach or suggest the features of the amended independent claim. In view of the amendments to the claims, the Examiner has set forth an amended §103 rejection with newly cited prior art that may be found starting on page 13 herein.
Examiner Notes
With regard to the limitation of claim 14 reciting “thereby creating basis for a form of artificial intelligence that can be used by modern computer systems to carry out an automated decision based on user input” – this limitation merely describes an intended use of the claimed invention. Furthermore, the Examiner notes “Claim scope is not limited by claim language that suggests or makes optional but does not require steps to be performed, or by claim language that does not limit a claim to a particular structure. However, examples of claim language, although not exhaustive, that may raise a question as to the limiting effect of the language in a claim are: […] (B) "wherein" clauses; and (C) "whereby" clauses”. Accordingly, this limitation of claim 14, as identified above, is not given patentable weight herein.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claim 14 is rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claim 14 recites “wherein mathematics and statistics are brought into the thought processes of an evaluating human brain”.
The Applicant’s specification fails to disclose any further technical or non-technical details regarding how this limitation is accomplished or is to be performed. At most, the specification discloses “This system is essentially an opinion and mathematical based tool that can be adjusted and reconfigured to deal with any complex decision making task” (see ¶ [0189]). The specification, however, is devoid of any clarification regarding how mathematics and statistics are to be “brought into the thought processes of an evaluating human brain”.
As such, the claim contains subject matter which is not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor, at the time the application was filed, had possession of the claimed invention. For the sake of compact prosecution, the claim features described above will be treated as though they comply with the written description requirement.
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 1-19 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.
Claim 12 recites “wherein the descending ordering of features…”. There is insufficient antecedent basis in the claim for “the descending ordering of features”. Accordingly, claims 12 is rendered indefinite for reciting a limitation for which there is a lack of antecedent basis. For the purposes of examination, this limitation will be interpreted as “wherein a descending order of features”.
Claim 15 recites “wherein order two or more features may be grouped…”. It is unclear in the claim what “wherein order two or more features may be grouped” encompasses and, as such, one of ordinary skill in the art would not be apprised of the metes and bounds of the claimed invention. Accordingly, claim 15 is rendered indefinite for failing to particularly point out or distinctly claim the subject matter. For the purposes of examination, this limitation will be interpreted as “wherein two or more features may be grouped…”.
Claim 16 recites “wherein order two or more features may be grouped…”. It is unclear in the claim what “wherein order two or more features may be grouped” encompasses and, as such, one of ordinary skill in the art would not be apprised of the metes and bounds of the claimed invention. Accordingly, claim 16 is rendered indefinite for failing to particularly point out or distinctly claim the subject matter. For the purposes of examination, this limitation will be interpreted as “wherein two or more features may be grouped…”.
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 1-19 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to an abstract idea without significantly more.
First of all, claims must be directed to one or more of the following statutory categories: a process, a machine, a manufacture, or a composition of matter. Claims 1-19 are directed to a machine (“a system”). Thus, claims 1-19 satisfy Step One because they are all within one of the four statutory categories of eligible subject matter. Claims 1-19, however, are directed to an abstract idea without significantly more.
Regarding independent claim 1, the specific limitations that recite an abstract idea are:
A feature list comprising a plurality of individual and distinct features, of any number corresponding to characteristics or qualities of the subject relevant to the decision;
[…] receive data entered by a user representing an ordering or arrangement of the features on the feature list, the ordering expressing the relative importance of the features, which the […] converts into corresponding positional values used in the calculation of the overall score, the ordering representing the relative importance of the features for the decision such that separate or explicit weighting by the user is not required;
[…] Receive, for each respective feature, a quantitative mark, score, or other numerical value entered by the user, representing the user’s assessment of how well that feature meets their preferences for the subject;
[…] process the ordered features, feature groups (if any) and their respective marks, scores, or other quantitative values according to stored calculation rules so as to generate a global decision score, for the subject representing an overall assessment of the subject based on the combination of the order of features on the feature list and the marks, scores or other quantitative values of each respective feature.
Therefore, claims 1 and 2-19, by virtue of dependence, recite certain methods of organizing human activity. In particular, the limitations of claim 1 identified above, as a whole, recite concepts of planning and facilitating business relations, which is the abstract idea of commercial interactions. See MPEP 2106.04(a)(2)(II). This is further evidenced in the Applicant’s specification at ¶ [0002], ¶ [0006], and ¶ [0068]. Furthermore, these limitations are directed towards collecting information, organizing information, and evaluating information in a manner that is analogous to human mental work. See MPEP 2106.04(a)(2)(III).
The judicial exception recited above is not integrated into a practical application. The additional elements of the claim include a “system” configured to perform the claim limitations. The abstract idea is not integrated into a practical application because the additional elements merely serve as generic computer tools and instructions on which the abstract idea is implemented. See MPEP 2106.05(f).
Finally, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, as discussed above, the additional elements, in combination, are recited at a high level of generality such that they amount to no more than mere instructions to apply the abstract idea using generic computer components. Because merely “applying” the exception using generic computer components/instructions cannot provide an inventive concept, the additional elements, when viewed as a whole/ordered combination, do not recite significantly more than the judicial exception. See MPEP 2106.05(I)(A).
Claim 3 further recites steps for collecting and organizing data, and thus further describes the abstract idea. The claim does not recite any further additional elements beyond the additional elements previously addressed with regard to claim 1 from which the claim depends.
Claim 4 further recites steps for collecting data from a user, and thus further describes the abstract idea. The claim does not recite any further additional elements beyond the additional elements previously addressed with regard to claim 1 from which the claim depends.
Claim 5 further recites steps for collecting data, and thus further describes the abstract idea. The claim does not recite any further additional elements beyond the additional elements previously addressed with regard to claim 1 from which the claim depends.
Claim 6 further recites steps for collecting and organizing data, and thus further describes the abstract idea. The claim does not recite any further additional elements beyond the additional elements previously addressed with regard to claim 1 from which the claim depends.
Claim 7 further recites steps for collecting and organizing data, and thus further describes the abstract idea. The claim does not recite any further additional elements beyond the additional elements previously addressed with regard to claim 1 from which the claim depends.
Claim 9 further recites steps for collecting data, analyzing data, and displaying a particular result of the analysis. Thus, the claim further describes the abstract idea. The claim does not recite any further additional elements beyond the additional elements previously addressed with regard to claim 1 from which the claim depends.
Claim 10 further recites steps for collecting and organizing data, and thus further describes the abstract idea. The claim does not recite any further additional elements beyond the additional elements previously addressed with regard to claim 1 from which the claim depends.
Claim 12 further recites steps for collecting and organizing data, and thus further describes the abstract idea. The claim does not recite any further additional elements beyond the additional elements previously addressed with regard to claim 1 from which the claim depends.
Claim 14 further recites steps for collecting information in an evaluating human brain, and thus further describes the abstract idea. The claim further introduces the additional elements of a “creating the basis for a form of artificial intelligence that can be used by modern computer systems to carry out an automated decision based on user input”.
The abstract idea is not integrated into a practical application because the additional elements merely serve as generic computer components and instructions on which the abstract idea is implemented. See MPEP 2106.05(f).
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements, either alone or in combination, are recited at a high level of generality such that they amount to no more than mere instructions to apply the abstract idea using generic computer components. Because merely “applying” the exception using generic computer components/instructions cannot provide an inventive concept, the additional elements, when viewed as a whole/ordered combination, do not recite significantly more than the judicial exception. See MPEP 2106.05(I)(A).
Claim 15 further recites steps for collecting and organizing data, and thus further describes the abstract idea. The claim does not recite any further additional elements beyond the additional elements previously addressed with regard to claim 1 from which the claim depends.
Claim 16 further recites steps for collecting and organizing data, and thus further describes the abstract idea. The claim does not recite any further additional elements beyond the additional elements previously addressed with regard to claims 1 and 15 from which the claim depends.
Claim 17 further recites steps for collecting and organizing data, and thus further describes the abstract idea. The claim does not recite any further additional elements beyond the additional elements previously addressed with regard to claim 1 from which the claim depends.
Claim 18 further recites steps for collecting and organizing data, and thus further describes the abstract idea. The claim does not recite any further additional elements beyond the additional elements previously addressed with regard to claims 1 and 17 from which the claim depends.
Claim 19 further recites steps for collecting and analyzing data, and thus further describes the abstract idea. The claim does not recite any further additional elements beyond the additional elements previously addressed with regard to claim 1 from which the claim depends.
Claim 20 further recites steps for allowing two or more features to be grouped together to form a single group in which all of the features within the group have equal importance and including the feature groups within the stored calculation rules used for processing the ordered features and generating the global decision score. Thus, claim 20 further describes the abstract idea. The claim does not recite any further additional elements beyond the additional elements previously addressed with regard to claim 1 from which the claim depends.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 3-7, 9, 12, 14-16 and 20 are rejected under 35 U.S.C. § 103 as being unpatentable over Gross U.S. Publication No. 2016/0048934, hereafter known as Gross, in view of Hayford U.S. Publication No. 2021/0345347, hereafter known as Hayford.
Claim 1: Gross teaches the following:
A features list comprising a plurality of individual and distinct features, of any number corresponding to characteristics or qualities of the subject relevant to the decision; (¶ [0137]: users can search for real estate/building stock that meets particular criteria of interest, including visual aesthetics, architectural features, etc. This is done by providing search parameters to Lead Generator engine which then identifies matching properties and outputs a report to a client device); (¶ [0139]: a report of results is presented to a user in accordance with the filtering parameters specified by the user); (¶ [0141]-¶ [0142]: the selection of search parameters may be achieved through an interactive interface on a device, as depicted in Fig. 3B. The selection screen includes a number of query selection boxes, buttons, pull-down elements, etc.).
The system being configured to receive, for each respective feature, a quantitative mark, score or other numerical value entered by the user representing the user’s assessment of how well that feature meets their preferences for the subject; (¶ [0340]: users can customize and weight features directly within the interface using a slider, a set of radio buttons, or similar types of input mechanisms. The data capture sliders directly influence the composition and weight of features used for the curb score calculation); (¶ [0350]-¶ [0353]: a Homescore and Curbscore consists of an automated calculation involving a selected set of desired parameters/features and a set of corresponding weighting factors specified for each feature as customized); (Fig. 29E: this Figure depicts the adjustable sliders for each individual feature, thus indicating a quantitative mark/score for the individual features).
Gross does not explicitly teach the system being configured to receive data entered by a user representing an ordering or arrangement of the features on the feature list, the ordering expressing the relative importance of the features, which the system converts into corresponding positional values used in the calculation of the overall score, the ordering representing the relative importance of the features for the decision such that separate or explicit weighting by the user is not required. Furthermore, Gross does not explicitly teach the system being configured to process the ordered features, feature groups (if any) and their respective marks, scores, or other quantitative values according to stored calculation rules so as to generate a global decision score, for the subject representing an overall assessment of the subject based on the combination of the order of features on the feature list and the marks, scores, or other quantitative values of each respective feature.
However, Hayford teaches the following:
The system being configured to receive data entered by a user representing an ordering or arrangement of the features on the feature list, the ordering expressing the relative importance of the features, which the system converts into corresponding positional values used in the calculation of the overall score, the ordering representing the relative importance of the features for the decision such that separate or explicit weighting by the user is not required; (¶ [0015]: a method for generating a prioritized list of relevant items associated with a good/service include onboarding a plurality of preference criteria indicating at least one degree of importance that the user assigns to a corresponding attribute of the good or service, determining a score for each corresponding attribute for each of the relevant items using electronic records; and generating the prioritized list of the relevant items using at least one ranking algorithm, wherein the ranking algorithm uses average scores for corresponding attributes having a same degree of importance assigned thereto, the average scores being weighted by a factor that is different for different degrees of importance and summed to generate a composite score; wherein the composite score of each relevant item is used to determine where each relevant item is ranked in the prioritized list); (¶ [0036]: the system enables flexible preferences of the user, e.g., a user may categorize preferences as “musts”, “wants”, “haves”, “do not wants”, etc.).
The system being configured to process the ordered features, feature groups (if any) and their respective marks, scores, or other quantitative values according to stored calculation rules so as to generate a global decision score, for the subject representing an overall assessment of the subject based on the combination of the order of features on the feature list and the marks, scores, or other quantitative values of each respective feature. (¶ [0015]: see above); (¶ [0036]: see above); (¶ [0014]: the system identifies personal preferences by using specific attributes indicated by the user, which are weighted by additional data selected by the user, to generate lists of prioritized products/services); (¶ [0048]: a user may select weighting values to appropriately weight different importance levels for preferences and generate a ranked list which accurately reflects a user’s desired product or service, e.g., a real estate property. Weighting factors may include, for example, 1, .1, and .01 for high importance, moderate importance, and low importance); (¶ [0045]: the system generates a set of scores for each of the user’s top preferences for one property using the prioritized preferences); (¶ [0047]: Once the system has scored all the relevant properties for each user preference, it can generate a composite score for each property using the generated preference scores. Equation (1) shows that the composite score is calculated from multiplying the preferences scores with the user selected weighting values).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system of Gross with the teachings of Hayford by incorporating the features for receiving data entered by a user representing an ordering or arrangement of the features on the feature list, the ordering expressing the relative importance of the features which the system converts into corresponding positional values used in the calculation of the overall score, and processing the ordered features and their respective marks, scores, or other quantitative values according to stored calculation rules so as to generate a global decision score, for the subject representing an overall assessment of the subject based on the combination of the order of features on the feature list and the marks, scores, or other quantitative values of each respective feature, as taught by Hayford. One of ordinary skill in the art would have been motivated to make this modification with the purpose to “generate a ranked list which accurately reflects a user's desired product or service, e.g., a real estate property” (¶ [0048]), as suggested by Hayford. Furthermore, one of ordinary skill in the art would have been motivated to make this modification when one considers that “by providing users with filtered, ranked information about local real estate, etc., that they can rely upon to be accurate, the system provides users with a single interface for quickly obtaining all of this information without needing to navigate to numerous websites that may or may not have the information that they are seeking” (¶ [0033), as suggested by Hayford. Furthermore, one of ordinary skill in the art would have recognized that the teachings of Hayford are compatible with the system of Gross as they share capabilities and characteristics; namely, they are both systems configured to obtain user preferences and perform a search for real-estate corresponding to the user preferences.
Claim 3: Gross/Hayford teaches the limitations of claim 1. Furthermore, Gross teaches the following:
Wherein pre-stored features […] are stored. (¶[0137]: users can search for real estate/building stock that meets particular criteria of interest. This is done by providing search parameters to Lead Generator engine which then identifies matching properties and outputs a report to a client device); (¶ [0141]-¶ [0142]: the selection of search parameters may be achieved through an interactive interface on a device. The selection screen includes a number of query selection boxes, buttons, pull-down elements, etc.); (¶ [0340]: users can customize and weight features directly within the interface using a slider, a set of radio buttons, or similar types of input mechanisms).
Gross does not explicitly teach wherein the feature ordering or positional values are stored. However, Hayford teaches the following:
Wherein the […] feature orderings or positional values are stored. (¶ [0015]: where each preference criteria indicates at least one degree of importance that the user assigns to a corresponding attribute of the good/service, and storing the plurality of preference criteria); (¶ [0036]: the system enables flexible preferences of the user, e.g., a user may categorize preferences as “musts”, “wants”, “haves”, “do not wants”, etc.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include in the system of Gross the ability to store feature orderings or positional values, as taught by Hayford, since the claimed invention is merely a combination of old elements. In combination, each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination are predictable. Furthermore, one of ordinary skill in the art would have recognized that the teachings of Hayford are compatible with the system of Gross as they share capabilities and characteristics; namely, they are both systems configured to obtain user preferences and perform a search for real-estate corresponding to the user preferences.
Claim 4: Gross/Hayford teaches the limitations of claim 1. Furthermore, Gross teaches the following:
Wherein the user can add or rename or remove features to the system. (¶ [0141]-¶ [0142]: the selection of search parameters may be achieved through an interactive interface on a device. The selection screen includes a number of query selection boxes, buttons, pull-down elements, etc.); (¶[0139]: a user may refine their search with different parameters).
Claim 5: Gross/Hayford teaches the limitations of claim 1. Furthermore, Gross teaches the following:
Wherein non-personal user data can be chosen to create a profile. (¶ [0249]: Homeowner profiles may be developed based on identified engagements made by homeowners, records types and dates of product/service purchases, and group behaviors); (¶ [0197]: a user’s social networking account can be mined for relevant interests and possessions. For example, pictures of an individual may include background scenes, identifiable objects, etc. These items can be image processed, and tagged to identify relevant items. The collected user data can then be compiled by an advertiser).
Claim 6: Gross/Hayford teaches the limitations of claim 1. Furthermore, Gross teaches the following:
Wherein non-personal user data from more than one profile may be merged or combined. (¶ [0197]: a user’s social networking account can be mined for relevant interests and possessions. For example, pictures of an individual may include background scenes, identifiable objects, etc. These items can be image processed, and tagged to identify relevant items. The collected user data can then be compiled by an advertiser).
Claim 7: Gross/Hayford teaches the limitations of claim 1. Furthermore, Gross teaches the following:
Wherein the class is a residential property. (¶ [0137]: users can search for real estate/building stock that meets particular criteria of interest, including visual aesthetics, architectural features, etc. This is done by providing search parameters to Lead Generator engine which then identifies matching properties and outputs a report to a client device); (¶ [0085]: preferred embodiments are presented in the context of single family residential housing structures).
Claim 9: Gross/Hayford teaches the limitations of claim 1. Furthermore, Gross teaches the following:
Wherein the global score includes a recommendation as to whether to proceed with a decision. (¶ [0152]: a match is retrieved for the user, and the user can be prompted to confirm that the match is correct by checking a selection box); ¶ [0154]: after confirming, the user can be prompted to see if they want to see more details); (¶ [0322]: homeowner/user can be presented with a graphical representation of the score of the home. For example, the homeowner/user is given a percentage score).
Claim 12: Gross/Hayford teaches the limitations of claim 1. Furthermore, Gross does not explicitly teach, however Hayford does teach, the following:
Wherein the descending order of features corresponds to a descending importance of the respective features. (¶ [0036]: the system enables flexible preferences of the user, e.g., a user may categorize preferences as “musts”, “wants”, “haves”, “do not wants”, etc.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system of Gross with the teachings of Hayford by incorporating the features for enabling a user to receive, from a user, a descending order of features corresponding to a descending importance of the respective features, as taught by Hayford. One of ordinary skill in the art would have been motivated to make this modification with the purpose to “generate a ranked list which accurately reflects a user's desired product or service, e.g., a real estate property” (¶ [0048]), as suggested by Hayford. Furthermore, one of ordinary skill in the art would have recognized that the teachings of Hayford are compatible with the system of Gross as they share capabilities and characteristics; namely, they are both systems configured to obtain user preferences and perform a search for real-estate corresponding to the user preferences.
Claim 14: Gross/Hayford teaches the limitations of claim 1. Furthermore, Official Notice has been taken by the Examiner to address the following claim limitations:
Wherein mathematics and statistics are brought into the thought processes of an evaluating human brain, thereby creating a basis for a form of artificial intelligence that can be used by modern computer systems to carry out an automated decision based on user input.
The limitations directed towards bringing mathematics and statistics “into the thought processes of an evaluating human brain” are considered to be common knowledge and well-known practices performed by humans. As an example, it is common knowledge that academic institutions provide courses/classes which introduce mathematical and statistical knowledge into the thought processes of observing human students. Moreover, the applicant’s specification fails to provide any further clarification of a particular, technical means by which this limitation is performed. Thus, under broadest reasonable interpretation in view of the specification, this limitation is analogous to well-known practices which have been performed by human beings for decades- at the very least, in academic settings.
Furthermore, as previously noted by the Examiner herein, the “thereby” limitation of the claim merely describes an intended use of the claimed invention and, therefore, is not given patentable weight herein. However, even when given patentable weight, this limitation is also considered to be common knowledge and a well-known practice performed by humans. As an example, it is common knowledge that mathematics and statistics are used as a basis by human programmers to create various AI applications that can be executed by modern computers to carry out automated decisions based on inputs. Moreover, the applicant’s specification fails to provide any further clarification of a particular, technical means by which this limitation is performed. Thus, this limitation, when given patentable weight, is analogous to well-known practices performed by humans.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include in the system of Gross the well-known practice of bringing mathematics and statistics into the thought processes of an evaluating human brain, since the claimed invention is merely a combination of old elements. In combination, each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination are predictable.
Claim 15: Gross/Hayford teaches the limitations of claim 1. Furthermore, Gross teaches the following:
Wherein order two or more features may be grouped so that their relative proportions are preserved while still allowing the scoring of one of the grouped features individually. (¶ [0350]-¶ [0353]: a Homescore and Curbscore consists of an automated calculation involving a selected set of desired parameters/features, a set of respective individual rating factors determined for each features, and a set of corresponding weighting factors specified for each feature as customized); (¶ [0354]: the product of each Rating*weight is computed, and then a cumulative sum is identified for a structure specific curbscore).
Claim 16: Gross/Hayford teaches the limitations of claim 15. Furthermore, Gross teaches the following:
Wherein order two or more features may be grouped so that the importance, weight or ranking of each grouped feature is equal to the other features within that group prior to scoring. (¶ [0350]-¶ [0353]: a Homescore and Curbscore consists of an automated calculation involving a selected set of desired parameters/features, a set of respective individual rating factors determined for each features, and a set of corresponding weighting factors specified for each feature as customized); (¶ [0340]: users can customize and weight features directly within the interface using a slider, a set of radio buttons, or similar types of input mechanisms).
Claim 20: Gross/Hayford teaches the limitations of claim 1. Furthermore, Gross does not explicitly teach, however Hayford does teach, the following:
Allow two or more features to be grouped together to form a single group in which all of the features within the group have equal importance, the system being configured to include such feature groups within the stored calculation rules used for processing the ordered features and generating the global decision score. (¶ [0036]: the system enables flexible preferences of the user, e.g., a user may categorize preferences as “musts”, “wants”, “haves”, “do not wants”, etc.); (¶ [0045]: the system generates a set of scores for each of the user’s top preferences for one property using the prioritized preferences); (¶ [0047]: Once the system has scored all the relevant properties for each user preference, it can generate a composite score for each property using the generated preference scores. Equation (1) shows that the composite score is calculated from multiplying the preferences scores with the user selected weighting values).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system of Gross with the teachings of Hayford by incorporating the features for allowing two or more features to be grouped together to form a single group in which all of the features within the group have equal importance, the system being configured to include such feature groups within the stored calculation rules used for processing the ordered features and generating the global decision score, as taught by Hayford. One of ordinary skill in the art would have been motivated to make this modification with the purpose to “generate a ranked list which accurately reflects a user's desired product or service, e.g., a real estate property” (¶ [0048]), as suggested by Hayford. Furthermore, one of ordinary skill in the art would have recognized that the teachings of Hayford are compatible with the system of Gross as they share capabilities and characteristics; namely, they are both systems configured to obtain user preferences and perform a search for real-estate corresponding to the user preferences.
Claims 17-18 are rejected under 35 U.S.C. § 103 as being unpatentable over Gross, in view of Hayford, in further view of Balasia et al. U.S. Publication No. 2019/0259002, hereafter known as Balasia.
Claim 17: Gross/Hayford teaches the limitations of claim 1. Furthermore, Gross does not explicitly teach, however Balasia does teach, the following:
Wherein features can be chosen to save as a template for future use. (¶ [0072]: a user may generate a client-side query, including a search for real estate such as a house/apartment/etc.); (¶ [0059]: user-determined characteristics, user-customizable parameters, and customized filtering are stored in a memory and persist over a predetermined period of time, such as several months. As a result, the user characteristics/parameters/filters can be utilized repeatedly, e.g., every time a user logs into the system).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include in the system of Gross/Hayford the ability to enable a user to save features as a template for future use, as taught by Balasia, since the claimed invention is merely a combination of old elements. In combination, each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination are predictable. Furthermore, one of ordinary skill in the art would have recognized that the teachings of Balasia are compatible with the system of Gross as they share capabilities and characteristics. Namely, they are both systems that enable users to search for real estate properties based on user-selected parameters.
Claim 18: Gross/Hayford teaches the limitations of claim 17. Furthermore, Gross does not explicitly teach, however Balasia does teach, the following:
Wherein features from more than one template may be merged or combined. (¶ [0072]: see above); (¶ [0059]: user-determined characteristics, user-customizable parameters, and customized filtering are stored in a memory and persist over a predetermined period of time, such as several months. As a result, the user characteristics/parameters/filters can be utilized repeatedly, e.g., every time a user logs into the system); (¶ [0103]: the system search engine may suggest adjustments to various preference parameters, then repeat the scoring, sorting, and ranking processes to generate a new set of personalized ranked search results).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include in the system of Gross/Hayford the ability to merge or combine features from more than one template, as taught by Balasia, since the claimed invention is merely a combination of old elements. In combination, each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination are predictable. Furthermore, one of ordinary skill in the art would have recognized that the teachings of Balasia are compatible with the system of Gross as they share capabilities and characteristics. Namely, they are both systems that enable users to search for real estate properties based on user-selected parameters.
Claim 10 is rejected under 35 U.S.C. § 103 as being unpatentable over Gross, in view of Hayford, in further view of Thomas et al. U.S. Publication No. 2012/0246024, hereafter known as Thomas.
Claim 10: Gross/Hayford teaches the limitations of claim 1. Furthermore, Gross does not explicitly teach, however Thomas does teach, the following:
Wherein user can record their reasons for feature arrangement and scores. (¶ [0046]: a self-service home buying application includes a notes feature that allows a user to take notes associated with available properties. User may use the notes as a reminder of the pros and cons associated with the properties, and the user may update their preferences according to the pros and cons); (¶ [0059]: the system may provide a notification to the user which highlights a subset of homes that best match the buyer’s preferences).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include in the system of Gross/Hayford the ability to enable a user record their reasons for feature arrangement and scores, as taught by Thomas, since the claimed invention is merely a combination of old elements. In combination, each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination are predictable. Furthermore, one of ordinary skill in the art would have recognized that the teachings of Thomas are compatible with the system of Gross as they share capabilities and characteristics. Namely, they are both systems that enable users to search for real estate properties based on user-selected parameters/preferences.
Claim 19 is rejected under 35 U.S.C. § 103 as being unpatentable over Gross, in view of Hayford, in further view of Wade et al. U.S. Publication No. 2011/0289077, hereafter known as Wade.
Claim 19: Gross/Hayford teaches the limitations of claim 1. Furthermore, Gross does not explicitly teach, however Wade does teach, the following:
Wherein a total monetary value for a property is divided according to the proportions of the scored and weighted features to indicate a monetary value of each feature. (¶ [0026]: a preference stack interface is provided that allows a user to customize the display of a set of data. The preference stack interface can be integrated into a real estate search program that displays properties to the user based on search criteria provided by the user); (¶ [0028]: important criteria can be added to the stack in order of relative importance, and the important criteria can be associated with a weight); (¶ [0036]: a user can assess the cost impact of a particular criterion by selecting the criterion object in the preference stack).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include in the system of Gross the ability to divide a total monetary value for a property according to the proportions of the scored and weighted features to indicate a monetary value of each feature, as taught by Wade, since the claimed invention is merely a combination of old elements. In combination, each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination are predictable. Furthermore, one of ordinary skill in the art would have recognized that the teachings of Wade are compatible with the system of Gross as they share capabilities and characteristics. Namely, they are both systems that enable users to search for real estate properties based on user-selected parameters/criteria.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/JORGE G DEL TORO-ORTEGA/Examiner, Art Unit 3628
/SHANNON S CAMPBELL/Supervisory Patent Examiner, Art Unit 3628