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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 12/18/2025 has been entered.
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 1-5 and 8-9 and 11-16 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim 1 is directed to statutory category process. The claim recites “mismatching based on the new user indicating one or more preferred mismatch categories in a match matrix profile, the new user with a second user amongst the plurality of prior users based on the presence of a series of mismatches, including a selectable geographic mismatch wherein the selectable geographic mismatch is rated numerically, and degrees of separation in the social media matrix between different aspects of the received profile information and preferred mismatch categories in the match matrix profile, and the previously received information…………. wherein the atypical interpersonal match is further based on a mismatch between an attribute of a third-party person associated with the new user and the mismatched ones of the plurality of prior users; and providing solely the mismatching to the new user”. The process of matching users based on their dissimilar profile attributes, matching users based on their degrees of separation in social media and matching user by their preferred category such as geographic location such as selectable geographic distance ranges, matching dissimilar attributes which associated to a third-party person and providing only matching users based on mismatching features involve observation, judgement and evaluation and can practically be performed in human mind. Accordingly, recited limitations fall into abstract idea groupings of mental process (see MPEP 2106.04(a)(2)(III)) under Step 2A, prong 1 of the 2019 PEG. Therefore, aforementioned processes can practically be performed in the human mind and directed to an abstract idea.
At step 2A, prong 2, this judicial exception is not integrated into a practical application. In particular, the claim recites additional elements – “receiving profile information from a new user into the social media matrix comprising previously received information of a plurality of prior users….” above additional elements recite insignificant extra-solution activity of user matching related mere data gathering as “obtaining information” as identified in MPEP 2106.05 (g). The claim also recites “relational database” this additional element of database to store data constitutes using a generic computer component to perform a function of storing. The claim further recites “the series of mismatches and degrees of separation being indicative of a desire by the new user for an atypical interpersonal match or separation in a real world relationship between the new user and the mismatched ones of the plurality of prior users, the relational database being capable of indicating the series of mismatches and degrees of separation” which constitutes generally linking the abstract idea of matching to the area of social media. See MPEP 2106.05(h). Viewing the additional limitations together and the claim as a whole, nothing provides integration into a practical application. Therefore, claim is directed to an abstract idea.
At step 2B, the claims don’t include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above the additional elements recites insignificant extra-solution activity of data gathering is well-understood, routine, and conventional. Further, “the series of mismatches and degrees of separation being indicative of a desire by the new user for an atypical interpersonal match or separation in a real world relationship between the new user and the mismatched ones of the plurality of prior users, the relational database being capable of indicating the series of mismatches and degrees of separation” which constitutes generally linking the abstract idea of matching to the area of social media. See MPEP 2106.05(h). Accordingly, claim 1 is not patent eligible.
Dependent claim 2-5 and 8-9 are directed to the same abstract idea as the independent claim from which they depend and further recite limitations – “wherein the social media matrix calculates at least one score relating to the first user to assess the degrees of separation” and further “the mismatching is based on the calculated score”.
The process of scoring degrees of separation and mismatching users based on scores involve observation, judgement and evaluation and can practically be performed in human mind. Accordingly, recited limitations fall into abstract idea groupings of mental process (see MPEP 2106.04(a)(2)(III)) under Step 2A, prong 1 of the 2019 PEG. Therefore, aforementioned processes can practically be performed in the human mind and directed to an abstract idea.
At step 2A, prong 2, this judicial exception is not integrated into a practical application. In particular, the claim recites additional elements – “wherein all of the profile information is stored in the social media matrix”, “wherein the profile information includes geographical information” , “the new user indicates each of the one or more preferred mismatch categories independently” and “the new user indicates each of the one or more preferred mismatch categories by a user-indicated prioritization” above mentioned additional elements recite insignificant extra-solution activity of data storing and designating data for gathering. Profile matching specific mere data gathering as “obtaining information” as identified in MPEP 2106.05 (g). Accordingly, this additional elements do not integrate the abstract idea into a practical application because they don’t impose any meaningful limits on practicing the abstract idea. Therefore, claim 2-5 and 8-9 are directed to an abstract idea.
At step 2B, the claims don’t include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above the additional elements of mere data gathering and storing, are well-understood, routine or conventional activities. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept, see MPEP 2106.05 (f). Accordingly, claim 2-5 and 8-9 are not patent eligible.
Dependent claim 11-16 are directed to the same abstract idea as the independent claim from which they depend and further recite limitations– “the numerical rating indicates a geographic distance between the new user and ones of the plurality of prior users of 0-5 miles”, “the numerical rating indicates a geographic distance between the new user and ones of the plurality of prior users of 5-25 miles”, “the numerical rating indicates a geographic distance between the new user and ones of the plurality of prior users of 25-50 miles”, “wherein the numerical rating indicates a geographic distance between the new user and ones of the plurality of prior users of 50-500 miles”, “the numerical rating indicates a geographic distance between the new user and ones of the plurality of prior users of greater than 500 miles" and “wherein the attribute of the third-party person comprises a job industry” above mentioned additional elements recite insignificant extra-solution activity of designating data for gathering. Profile matching specific mere data gathering as “obtaining information” as identified in MPEP 2106.05 (g). Accordingly, this additional elements do not integrate the abstract idea into a practical application because they don’t impose any meaningful limits on practicing the abstract idea. Therefore, claim 12-16 are directed to an abstract idea.
At step 2B, the claims don’t include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above the additional elements of mere data gathering and storing, are well-understood, routine or conventional activities. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept, see MPEP 2106.05 (f). Accordingly, claim 11-16 are not patent eligible.
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.
Claim1-5 and 8-15 are rejected under 35 U.S.C. 103 as being unpatentable over Leonard, Melissa (PGPUB Document No. 20100125632), hereafter referred as to “Leonard”, in view of Baker, Scott (PGPUB Document No. 20120005045), hereafter, referred to as “Baker”, in view of Lerner, Clifford (PGPUB Document No. 20150254311), hereafter, referred to as “Lerner”, in further view of Pahls, Colorado et al (PGPUB Document No. 20120123828), hereafter, referred to as “Pahls”.
Regarding claim 1 (Currently amended), Mansouri teaches A method for mismatching users remote from one another using remotely located, computing code that executes a relational database comprised of a social media matrix provided over at least one network, the method comprising(Leonard, Fig. 1 and para 0030 disclose a profile matching method of users using profile attributes in a social media network and receiving users’ information during registration process “The process may initiate at 100 when the user (e.g., a user wishing to locate and/or interact with one or more persons of interest), registers with the system. The user enters information about the client user at 101. Various kinds of information may be obtained from the user”):
receiving profile information from a new user into the social media matrix comprising previously received information of a plurality of prior users(Leonard, Fig. 1 and para 0032 further discloses receiving users profile information (for members or prospect/new users) during user registration process and storing member information in a database structure /social media matrix(element 102 and 104 of Fig. 1) “the information entered by a user at 101 (e.g., through a registration interface illustrated in FIG. 3) is then stored for later retrieval at 102”, para 0055 further discloses data is being stored in a database);
the relational database being capable of indicating the series of mismatches and degrees of separation(Leonard, element 112-113 of Fig. 1 discloses storing scores (indicator for potential matches/mismatches or scores for any attributes) of users; para 0055 further discloses data is being stored in a database; where prior art Lerner discussed later in para 0166 teaches matching attribute degree of separation);
But Leonard does not explicitly teach mismatching based on the new user indicating one or more preferred mismatch categories in a match matrix profile, the new user with a second user amongst the plurality of prior users based on the presence of a series of mismatches, including a selectable geographic mismatch wherein the selectable geographic mismatch is rated numerically, and degrees of separation in the social media matrix between different aspects of the received profile information and preferred mismatch categories in the match matrix profile, and the previously received information, the series of mismatches and degrees of separation being indicative of a desire by the new user for an atypical interpersonal match or separation in a real world relationship between the new user and the mismatched ones of the plurality of prior users, and providing solely the mismatching to the new user, wherein the atypical interpersonal match is further based on a mismatch between an attribute of a third-party person associated with the new user and the mismatched ones of the plurality of prior users; and providing solely the mismatching to the new user.
However, in the same field of endeavor of user profile querying/retrieving Baker teaches mismatching based on the new user indicating one or more preferred mismatch categories in a match matrix profile, the new user with a second user amongst the plurality of prior users based on the presence of a series of mismatches(Baker, Fig. 31 A and para 0097 disclose matching mismatching profile attributes such as gender (element 302 ), age(element 303 ), location (element 304) by distance etc. “Users can choose their age range preference 303 and geographic proximity from a specified zip code 304. In this example, the user has identified himself as a male seeking a female, between the ages of 30 and 35, and within 50 miles of zip code 01234”; where Fig. 32-34 disclose matching matrix of profile attributes ), including a selectable geographic mismatch wherein the selectable geographic mismatch is rated numerically(Baker, Fig. 31 A and para 0097 further disclose matching mismatching geolocation by selecting a distance range from a zip code “Users can choose their age range preference 303 and geographic proximity from a specified zip code 304”; here the examiner interprets the limitation “selectable geographic mismatch is rated numerically” as selection of distance numerically a range such as 50 miles represents 0-50 miles etc.); and providing solely the mismatching to the new user(Baker, Fig. 31 B and para 0098 further disclose providing a list matched persons/members based on selected criteria and which implies if non-common (mismatching) profile attributes are being selected by the searcher then the display would provide as list having matching attributes “Once the user chooses to search the site's database using the search criteria, he is brought to a display as shown in FIG. 31 B. In this display, the members that match the search criteria are displayed in a list of pictures and text 311, along with the search criteria 310. Within list 311, each member 312 that meets the search criteria will be displayed with basic information on the member, generally including age, location and other cursory information”).
Here the examiner interprets “mismatching based on the new user indicating one or more preferred mismatch categories in a match matrix profile” to mean matching users based on their uncommon/dissimilar profile attribute categories.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to incorporate the feature of matching users based on mismatching or uncommon attributes between users of Baker into the matching of profile feature of Leonard to produce an expected result of providing matching users based on what user desires. The modification would be obvious because one ordinary skill in the art would be motivated to improve the selection process by viewing all needed data points relate to one another in a single display (Baker, para 0030).
But Leonard and Baker don’t explicitly teach and degrees of separation in the social media matrix between different aspects of the received profile information and preferred mismatch categories in the match matrix profile, and the previously received information, the series of mismatches and degrees of separation being indicative of a desire by the new user for an atypical interpersonal match or separation in a real world relationship between the new user and the mismatched ones of the plurality of prior users, wherein the atypical interpersonal match is further based on a mismatch between an attribute of a third-party person associated with the new user and the mismatched ones of the plurality of prior users;
However, in the same field of endeavor of user profile matching Lerner teaches and degrees of separation in the social media matrix between different aspects of the received profile information and preferred mismatch categories in the match matrix profile, and the previously received information, the series of mismatches and degrees of separation being indicative of a desire by the new user for an atypical interpersonal match or separation in a real world relationship between the new user and the mismatched ones of the plurality of prior users(Lerner, para 0166 teaches how degrees of data separation between two users preferring to avoid first degree of separation between matching users “The potential dates for the viewing user may be selected from users on the social networking system that are indirectly connected to the viewing user. An indirectly connected user is a connection in the social networking system that is not directly connected to the viewing user. That is, an indirectly connected user has at least two degrees of separation from the viewing user. A degree of separation is the number of links from the viewing user "; where Baker in Fig. 31 A and para 0097 discloses member desiring a match by considering matched and mismatched (similar and dissimilar) attributes in received profile information),
Here the examiner interprets “separation in a real world relationship between the new user and the matched ones of the plurality of prior users” to mean dating or meeting someone at higher degree of separation would provide security in terms of privacy of matching users.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to incorporate the feature of considering degrees of data separation during profile attribute matching or mismatching of Lerner into the match or mismatch profile feature of Leonard and Baker to produce an expected result of providing privacy between to meeting users. The modification would be obvious because one ordinary skill in the art would be motivated to incorporate the degree of separation factor of users into compatibility score between users for providing a ranked matches to viewing users (Lerner, para 0006).
But Leonard, Baker and Lerner don’t explicitly teach wherein the atypical interpersonal match is further based on a mismatch between an attribute of a third-party person associated with the new user and the mismatched ones of the plurality of prior users;
However, in the same field of endeavor of user profile matching Pahls teaches wherein the atypical interpersonal match is further based on a mismatch between an attribute of a third-party person associated with the new user and the mismatched ones of the plurality of prior users(Pahls, 0038 discloses mismatching or filtering out number of people based on any attributes which can be associated to any third-partly person; as disclosed by Pahls, a user can search potential dates or person to meet based on one’s political “like” or “dislike” bias such as a liberal wishing not to meet a liberal by selecting/indicating his/her dislikes to meet a person having that political view by filtering out certain type of people “…….suggest people for the user to date or otherwise contact who gave similar scores to the image, or use the scores as a compatibility factor to be used in conjunction with other compatibility factors in matching people based on similar likes, dislikes, interests, political views, etc " );
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to incorporate the feature of matching users based on mismatching attribute of Pahls into the match or mismatch profile feature of Leonard, Baker and Lerner to produce an expected result of providing matching users based on what user desires. The modification would be obvious because one ordinary skill in the art would be motivated to improve the compatibility between matching persons by considering both like and dislike attributes (Pahls, para 0038).
Regarding claim 2 (Previously Presented), Leonard, Baker, Lerner and Pahls teach all the limitations of claim 1 and Leonard further teaches wherein all of the profile information is stored in the social media matrix (Leonard, Fig. 1 and para 0032 further discloses receiving users profile information during user registration process and storing member information in a database structure /social media matrix(element 102 and 104 of Fig. 1) “the information entered by a user at 101 (e.g., through a registration interface illustrated in FIG. 3) is then stored for later retrieval at 102”, para 0055 further discloses data is being stored in a database).
Regarding claim (Previously Presented), Leonard, Baker, Lerner and Pahls teach all the limitations of claim 2 and Lerner further teaches wherein the social media matrix calculates at least one score relating to the first user to assess the degrees of separation(Lerner, para 0032 discloses how degrees of separation scoring is being used for attributes to match compatibility between users “In addition to the common interests, the compatibility score may also incorporate the degree of separation between the viewing user and the preliminary matching user. ").
Regarding claim 4 (Previously Presented), Leonard, Baker, Lerner and Pahls teach all the teach all the limitations of claim 3 and Leonard further teaches wherein the mismatching is based on the calculated score (Leonard, para 0041 disclose matching users (prospect) based on matching scores “Matching and attribute scores may be used at 122 to estimate the proximity of users to prospects at 121 (e.g., the system uses matching scores, that represent estimated levels of certain attributes that individual users are seeking and attribute scores, that represent the estimated attributes that individual users possess, to determine optimal matches)” ; where Barker in Fig. 31 A and para 0097 disclose matching mismatched profile attributes).
Regarding claim 5 (Previously Presented), Leonard, Baker, Lerner and Pahls teach all the limitations of claim 1 and Leonard further teaches wherein the profile information includes geographical information (Leonard, para 0031 disclose user geographical information/zip code in the profile “Users may enter information about themselves through a registration interface such as that shown in FIG. 3. Such information may comprise a user's gender 132, … zip code 137” ).
Claim 6-7, cancelled.
Regarding claim 8(Previously Presented), Leonard, Baker, Lerner and Pahls teach all the limitations of claim 1 and Leonard further teaches wherein the new user indicates each of the one or more preferred mismatch categories independently (Leonard, para 0059 discloses member desiring a match by considering matched and mismatched (dissimilar) attributes indicated by users as their preference in received profile information “The matching model matches each user to those that are estimated to have similar and/or dissimilar characteristics to those that the user has previously indicated higher or lower preference for. Rating data may be used to refine what is understood about users and/or user matching preferences. This data may be used in matching users one to another”).
Regarding claim 9 (Previously Presented), Leonard, Baker, Lerner and Pahls teach all the limitations of claim 1 and Leonard further teaches wherein the new user indicates each of the one or more preferred mismatch categories by a user-indicated prioritization (Leonard, para 0059 discloses member desiring a match by considering matched and mismatched (dissimilar) attributes indicated by users as their preference priority in received profile information “The matching model matches each user to those that are estimated to have similar and/or dissimilar characteristics to those that the user has previously indicated higher or lower preference for. Rating data may be used to refine what is understood about users and/or user matching preferences. This data may be used in matching users one to another”).
Claim 10, cancelled.
Regarding claim 11 (Previously Presented), Leonard, Baker, Lerner and Pahls teach all the limitations of claim 1 and Baker further teaches wherein the numerical rating indicates a geographic distance between the new user and ones of the plurality of prior users of 0-5 miles (Baker, Fig. 32 and para 0100 further disclose numerical rating indicating a distance between 0-5 miles “Users can choose their age range preference 303 and geographic proximity from a specified zip code 304”).
Regarding claim 12 (Previously Presented), Leonard, Baker, Lerner and Pahls teach all the limitations of claim 1 and Baker further teaches wherein the numerical rating indicates a geographic distance between the new user and ones of the plurality of prior users of 5-25 miles(Baker, Fig. 32 and para 0100 further disclose numerical rating indicating a distance between 5-25 miles “Users can choose their age range preference 303 and geographic proximity from a specified zip code 304”).
Regarding claim 13 (Previously Presented), Leonard, Baker, Lerner and Pahls teach all the limitations of claim 1 and Baker further teaches wherein the numerical rating indicates a geographic distance between the new user and ones of the plurality of prior users of 25-50 miles(Baker, Fig. 32 and para 0100 further disclose numerical rating indicating a distance between 25-50 miles).
Regarding claim 14 (Previously Presented), Leonard, Baker, Lerner and Pahls teach all the limitations of claim 1 and Baker further teaches wherein the numerical rating indicates a geographic distance between the new user and ones of the plurality of prior users of 50-500 miles (Baker, Fig. 32 and para 0100 further disclose numerical rating indicating a distance between 0-50 miles and para 0102 further discloses that this range can be expanded “As these search criteria are modified while in the graph viewing option, axes ranges will adjust accordingly and data points will appear and disappear dynamically as the displayed data set reflects the new search parameters. To the extent that the user feels that there are too few or too many data points to review, he can modify his search to expand or reduce the number of instances, or data points, on the graph for better visualizations”).
Regarding claim 15 (Previously Presented), Leonard, Baker, Lerner and Pahls teach all the limitations of claim 1 and Baker further teaches wherein the numerical rating indicates a geographic distance between the new user and ones of the plurality of prior users of greater than 500 miles(Baker, Fig. 32 and para 0100 further disclose numerical rating indicating a distance between 0-50 miles and para 0102 further discloses that this range can be expanded “As these search criteria are modified while in the graph viewing option, axes ranges will adjust accordingly and data points will appear and disappear dynamically as the displayed data set reflects the new search parameters. To the extent that the user feels that there are too few or too many data points to review, he can modify his search to expand or reduce the number of instances, or data points, on the graph for better visualizations”).
Claim16 is rejected under 35 U.S.C. 103 as being unpatentable over Leonard, Melissa (PGPUB Document No. 20100125632), hereafter referred as to “Leonard”, in view of Baker, Scott (PGPUB Document No. 20120005045), hereafter, referred to as “Baker”, in view of Lerner, Clifford (PGPUB Document No. 20150254311), hereafter, referred to as “Lerner”, in view of Pahls, Colorado et al (PGPUB Document No. 20120123828), hereafter, referred to as “Pahls”, in further view of Gu, Shanlin et al (PGPUB Document No. 20140289142), hereafter, referred to as “Gu”
Regarding claim 16 (Currently Amended), Leonard, Baker, Lerner and Pahls teach all the limitations of claim 1 but don’t explicitly teach wherein the attribute of the third-party person comprises a job industry.
But Leonard, Baker, Lerner and Pahls don’t explicitly teach wherein the attribute of the third-party person comprises a job industry.
However, in the same field of endeavor of user profile matching Gu teaches wherein the attribute of the third-party person comprises a job industry(Gu, Fig. 18 and para 0107 disclose any person having job industry attribute “Job type filtering filters job type 731 of job seeker preferences for job type 910 against job type 731 of job information 720; Location filtering filters location 922 against location 723; Industry filtering filters industry 331 of job seeker preferences for industry 930 against industry 331 of employer industry Information 330 "),
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to incorporate the feature of matching users based on mismatching of job industry of Gu into the match or mismatch profile feature of Leonard, Baker, Lerner and Pahls to produce an expected result of providing user desired attribute. The modification would be obvious because one ordinary skill in the art would be motivated to improve matching inefficiencies and accuracy by keyword matching extracted from user profile (Gu, para 0006).
Response to Arguments
I. 35 U.S.C §101
Regarding the abstract idea rejection the applicant on page 4 para 3 argued that “claim 1 includes the relational database, in fact, is used to determine matches, mismatches and degrees of separation, which accounts to significantly more than an abstract idea. In a typical relational database, entries in the database table are in rows, and the columns of each row dictate the attributes of the entry in that row, and each row is related to other entries using the relationships between the attributes. See, e.g., Wikipedia.com.
Consequently, the use of the single relational database to provide the matches, mismatches, and degrees of separation is counterintuitive to the skilled artisan. Thus, the embodiments should not be deemed mere abstract ideas, but rather are tied to a computer, in a non-generic, counterintuitive way, to provide unknown functionality”.
Applicant above mentioned arguments not found persuasive as determining matches, mismatches and degree of separation between two users can practically performed in human mind by comparing and judging users’ attributes. Fuhrer, storing data in a relational data base that organizes data in rows and columns may considered as extra solution activity of data storing where relational database is a generic computer component to perform function of storing [(Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334 (Fed. Cir. 2015) (storing and retrieving information in memory)]. Therefore, it does not amount to significantly more than the abstract idea.
The applicant further in the last paragraph on page 4 stated that “The Examiner then indicated on page 9 of the Office Action dated 8/23/23 that in light of the amendments the $101 abstract idea rejection was withdrawn”.
In response to the above mentioned statement, the examiner would like to mention that during the continued examination (non-final mailed on 3/24/2025) upon through analysis of claim limitations, the examiner has changed his position. The updated detail §101 abstract idea rejection analysis is presented in the 101 rejection section of this office action.
II. 35 U.S.C §103
Applicant’s arguments filed on 12/3/2025 have been fully considered but are
moot because the independent claim 1 has been amended with newly added
features which applicant’s arguments are directed towards. Since claims have been amended with new features, a new ground of rejection is presented.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ABDULLAH A DAUD whose telephone number is (469)295-9283. The examiner can normally be reached M~F: 9:30 am~6:30 pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Amy Ng can be reached at 571-270-1698. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/ABDULLAH A DAUD/Examiner, Art Unit 2164 /AMY NG/Supervisory Patent Examiner, Art Unit 2164