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 .
Acknowledgments
Claims 21-39 are cancelled.
Claims 1-20 are pending.
Applicant did not provide Information disclosure statement.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more than the judicial exception itself.
Regarding Step 1 of subject matter eligibility for whether the claims fall within a statutory category (See MPEP 2106.03), claims 1-20 are directed to the statutory category of method and system.
Regarding step 2A-1, Claims 1-20 recite a Judicial Exception. Exemplary independent claim 1 and similarly claim 20 recite the limitations of
accumulating secondary data associated with said file…objects, said secondary data being other than content of said file…objects; arranging said secondary data…generating an object value indicative of the value of at least one of said file …objects to a particular entity; and creating a record…record associating said object value with said at least one of said file…objects.
These limitations, as drafted, are a process that, under its broadest reasonable interpretation cover concepts of accumulating, arranging, and generating/creating data. The claim limitations fall under the abstract idea grouping of mental process (i.e. including an observation, evaluation, judgment, opinion), because the limitations can be performed in the human mind, or by a human using a pen and paper. For example, but for the language of a system, the claim language encompasses simply accumulating data followed by arranging data, generating an object value with respect to the data, and creating a record. These steps are mere data manipulation steps that do not require a computer. Determining a value of something is not novel and has been done before the technological age.
Determining a value of content is with respect to making optimal IT and business decisions as seen on page 1 of Applicant’s specification. It is clear the claimed invention is solving a business problem. These make the claims fall in the abstract idea grouping of certain methods of organizing human activity (fundamental economic principles or practices; business relations). In addition, it is clear the limitations recite these abstract idea groupings, but for the recitations of generic computer components. The mere nominal recitations of generic computer components does not take the limitations out of the mental process and certain methods of organizing human activity grouping. The claims are focused on the combination of these abstract idea processes.
Regarding step 2A-2- This judicial exception is not integrated into a practical application, and the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception.
The claim recites the additional elements of file storage system, system objects, storage device, valuation database, valuation system, processor, memory, accumulator, data aggregator, and value generator.
These components are recited at a high level of generality, and merely automate the steps. Each of the additional limitations is no more than mere instructions to apply the exception using a generic computer component.
The combination of these additional elements is no more than mere instructions to apply the exception using a generic computer components or software. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Further, the claims do not provide for recite any improvements to the functioning of a computer, or to any other technology or technical field; applying or using a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition; applying the judicial exception with, or by use of, a particular machine; effecting a transformation or reduction of a particular article to a different state or thing; or applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception.
The dependent claims have the same deficiencies as their parent claims as being directed towards an abstract idea, as the dependent claims merely narrow the scope of their parent claims. For example, the dependent claims further describe how the value is described such as by a monetary currency. In addition, the dependent claims further describe how the object values are utilized such as to carryout IT policy changes.
Regarding step 2B, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because claim 1 recites
Method which is not considered an additional element
Claim 1 also recites system objects, file storage system, storage device, valuation database
Claim 19 recites area wide network
Claim 20 recites system, processor, memory, accumulator, data aggregator, and value generator.
When looking at these additional elements individually, the additional elements are purely functional and generic, the applicant specifications states a general-purpose computer configurations as seen on page 29.
When looking at the additional elements in combination, the computer components add nothing that is not already present when the steps are considered separately. See MPEP 2106.05
Looking at these limitations as an ordered combination and individually adds nothing additional that is sufficient to amount to significantly more than the recited abstract idea because they simply provide instructions to use generic computer components, recitations of generic computer structure to perform generic computer functions that are used to "apply" the recited abstract idea. Thus, the elements of the claims, considered both individually and as an ordered combination, are not sufficient to ensure that the claim as a whole amounts to significantly more than the abstract idea itself.
Since there are no limitations in these claims that transform the exception into a patent eligible application such that these claims amount to significantly more than the exception itself, claims 1-20 are rejected under 35 U.S.C. 101.
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 for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim 1-16 and 18-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Bhasin et al. (US20130262418A1) herein Bhasin in further view of Curtis (US20180240144A1) herein Curtis.
Regarding claim 1, Bhasin teaches
A method (¶0025-FIG. 3 shows an example method of determining the relative importance of a file based on one or more importance parameters.) Figure 2 also shows a method.
Accumulating secondary data associated with said file system objects, said secondary data being other than content of said file system objects
(See para 0025- At 300, 310, 320, 330 and 340 information relating to the file is gathered.)(See para 0029-0030-At 330 file sharing information is gathered, for example the number of users whom a file is shared with (accessible to) and/or the relationship in an organization database between different users who share the file (for example whether they all work in the same department or different departments and their relative levels in the organization…At 340 file access information is gathered. This information may be gathered at the kernel level, for example when a particular file is accessed. The information may be used to generate an importance parameter relating to file access, for example the frequency with which a file is accessed. In this disclosure the frequency with which a file is accessed is not used alone to determine the relative importance of the file, however the frequency of access may be used together with other importance parameters to determine the relative importance of the file.) This shows secondary data is accumulated with file system objects, this secondary data does not deal with content inside the actual files but characteristics of the file such as access and sharing information. The system deals with multiple files (i.e. file system objects) as seen in para 0003.
arranging said secondary data in a storage device; (See para 0039- The kernel space 510 may host an event feeder 520 which is a component of the operating system which provides information about the files )(See para 0040-The user space may host an attribute feeder 560 which filters and/or processes information from the event feeder 520 in order to generate one or more importance parameters which are passed on or made available to the ICE 110. The ICE 110 determines the relative importance of the file and communicates with the MPE 120 which applies an appropriate information management policy to the file based on the file's relative importance.) This shows the information gathered is arranged in the storage device 100 because it is sent to ICE item 110 which is part of the storage device 100. (See fig. 1C).
generating an object value indicative of the value of at least one of said file system objects to a particular entity;
(See para 0031-At 350 one or more importance parameters are generated based on the gathered information. The importance parameters may correspond directly to the gathered information, or may be a filtered or modified subset of the gathered information. At 360 the relative importance of the file is determined based on the importance parameters and weightings or rules associated with the various importance parameters. Thus an importance parameter associated with a higher weighting will have more influence on the determination of relative importance than an importance parameter associated with a relatively lower rating.) This shows the system determines a file’s/object’s value by determining importance parameters and relative importance. The entity here is the enterprise and/or user as seen in 0002.
Creating a record…said record associating said object value with said at least one of said file system objects. (See ¶0034-As the files are automatically classified according to their relative importance, in some implementations a report may be run to indicate the amount of storage space used up by files of each category (e.g. space occupied by confidential files, personal critical files, business critical files etc.).) This shows a record is created in way of a report with security importance.
Even though Bhasin teaches report, it doesn’t teach a value database. However Curtis teaches a valuation database (See para 0046- In alternative embodiments the pricing database 257 and value database 252 can be incorporated into a single value and pricing database (not shown). ) This shows a database that includes values/importance of items.
Bhasin and Curtis are analogous art because they are from the same problem-solving area of classification of data. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined Bhasin’s invention by incorporating the method of Curtis because Bhasin can use the database of Curtis to store reports regarding the importance of the files. Storing the report allows for organization of data to access at a later time. In addition, this would make the system of Bhasin more sophisticated since there would be an additional database that would be able to keep track of importance of files.
Regarding claim 20, Bhasin teaches
A valuation system… a processor configured to execute code... memory configured to store data and said code, said code including (See figure 1A-1C) (See para 0036- FIG. 4 shows one example of a possible structure of a device 100 which may be used to carry out the teachings described herein. The device has processing resources 400 which may for instance be provided by one processor a plurality of processors. The device has a memory 500 which may be split into a kernel space 510 and a user space 550. The kernel space 510 stores an operating system (e.g. Windows, Unix, Android, IOS etc.), while the user space 550 stores various programmes. The operating system and programmes may comprise machine readable instructions which are executable by the processing resources 400.)
an accumulator configured to accumulate secondary data associated with said file system objects, said secondary data being non-object-content data (See para 0025- At 300, 310, 320, 330 and 340 information relating to the file is gathered.)(See para 0029-0030-At 330 file sharing information is gathered, for example the number of users whom a file is shared with (accessible to) and/or the relationship in an organization database between different users who share the file (for example whether they all work in the same department or different departments and their relative levels in the organization). At 340 file access information is gathered. This information may be gathered at the kernel level, for example when a particular file is accessed. The information may be used to generate an importance parameter relating to file access, for example the frequency with which a file is accessed. In this disclosure the frequency with which a file is accessed is not used alone to determine the relative importance of the file, however the frequency of access may be used together with other importance parameters to determine the relative importance of the file.) This shows secondary data is accumulated with file system objects, this secondary data does not deal with content inside the actual files but characteristics of the file such as access and sharing information. The system here is the accumulator since it carries out the function of the accumulator.
a data aggregator configured to arrange said secondary data in said memory, (See para 0040-The user space may host an attribute feeder 560 which filters and/or processes information from the event feeder 520 in order to generate one or more importance parameters which are passed on or made available to the ICE 110. The ICE 110 determines the relative importance of the file and communicates with the MPE 120 which applies an appropriate information management policy to the file based on the file's relative importance.) This shows the information gathered is arranged in the storage device 100 because it is sent to ICE item 110 which is part of the storage device 100. (See fig. 1C). Storage device includes the memory. The system here is the data aggregator since it carries out the function of the data aggregator.
a value generator configured to generate an object value indicative of the value of at least one of said file system objects to a particular entity, (See ¶0031-At 350 one or more importance parameters are generated based on the gathered information. The importance parameters may correspond directly to the gathered information, or may be a filtered or modified subset of the gathered information. At 360 the relative importance of the file is determined based on the importance parameters and weightings or rules associated with the various importance parameters. Thus an importance parameter associated with a higher weighting will have more influence on the determination of relative importance than an importance parameter associated with a relatively lower rating.) This shows the system determined object value importance parameters and relative importance. The system here is the value generator since it carries out the function of the value generator. The entity here corresponds to the user and/or enterprise as seen in para 0002.
and to create a record…to associate said object value with said at least
one of said file system objects. (See ¶0034-As the files are automatically classified according to their relative importance, in some implementations a report may be run to indicate the amount of storage space used up by files of each category (e.g. space occupied by confidential files, personal critical files, business critical files etc.).) This shows a record is created in way of a report with security importance.
Even though Bhasin teaches report, it doesn’t teach a value database. However Curtis teaches a valuation database (See para 0046- In alternative embodiments the pricing database 257 and value database 252 can be incorporated into a single value and pricing database (not shown). ) This shows a database that includes values/importance of items.
Bhasin and Curtis are analogous art because they are from the same problem-solving area of classification of data. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined Bhasin’s invention by incorporating the method of Curtis because Bhasin can use the database of Curtis to store reports regarding the importance of the files. Storing the report allows for organization of data to access at a later time. In addition, this would make the system of Bhasin more sophisticated since there would be an additional database that would be able to keep track of importance of files.
In addition, Bhasin teaches the functionally being performed by the accumulator, data aggregator, and valued generator as discussed above but does so with one system rather than the 3 units claimed. However it is well settled that making elements separable does not convey a patentable distinction. In reDulberg, 289 F.2d 522, 523, 129 USPQ 348, 349 (CCPA 1961)
It would have been obvious to have modified Bhasin to have included where the functionality was performed by separate units because it would have provided a predictable result in performing the functions.
There is no unexpected results by performing the steps using 3 units because the outcome would be the same.
Regarding Claim 2, Bhasin and Curtis teach the limitations of claims 1 and, however Bhasin further teaches
wherein said step of generating an object value includes generating a plurality of object values, each object value indicative of a distinct value of said at least one of said file system objects from a different perspective. (See ¶0034- As the files are automatically classified according to their relative importance, in some implementations a report may be run to indicate the amount of storage space used up by files of each category (e.g. space occupied by confidential files, personal critical files, business critical files etc.).) This shows plurality of object values such as confidential or personal critical. The fact that these are classified with different rating means they are classified with a different perspective. (See ¶0032-it may be categorized as personal critical if it is not shared (accessible to one user only), or business critical if accessed by several different users.) This shows different perspectives as well.
Regarding Claim 3, Bhasin and Curtis teach the limitations of claims 2, however Bhasin further teaches
wherein one of said plurality of object values is indicative of
a value of said at least one of said file system objects from a data security perspective (See ¶0034- As the files are automatically classified according to their relative importance, in some implementations a report may be run to indicate the amount of storage space used up by files of each category (e.g. space occupied by confidential files, personal critical files, business critical files etc.).) The fact that is classifies confidential files means it is from security perspective.
Regarding Claim 4, Bhasin and Curtis teach the limitations of claims 2, however Bhasin further teaches
wherein one of said plurality of object values is indicative of a value of said at least one of said file system objects from a business continuity perspective. (See ¶0032-If the file is the only one existing in the storage system and is accessed regularly (above a certain frequency) it may be categorized as personal critical if it is not shared (accessible to one user only), or business critical if accessed by several different users) This shows a file system object is classified business critical because it is critical for the business because many users use the file.
Regarding Claim 5, Bhasin and Curtis teach the limitations of claims 1, however Bhasin further teaches
wherein said secondary data includes data associated with said particular entity but not directly associated with any particular subset of said file system objects. (See ¶0029-0030- At 330 file sharing information is gathered, for example the number of users whom a file is shared with (accessible to) and/or the relationship in an organization database between different users who share the file (for example whether they all work in the same department or different departments and their relative levels in the organization). At 340 file access information is gathered. This information may be gathered at the kernel level, for example when a particular file is accessed. The information may be used to generate an importance parameter relating to file access, for example the frequency with which a file is accessed. In this disclosure the frequency with which a file is accessed is not used alone to determine the relative importance of the file, however the frequency of access may be used together with other importance parameters to determine the relative importance of the file.) This shows secondary data that is associated with files in an enterprise. Files can be associated with an enterprise (See background). This secondary data is associated with an enterprise but not directly associated with any subset of filing system objects since this data does not deal with the actual content of what is in the file object but characteristics of the file objects such as access/sharing information.
Regarding Claim 6, Bhasin and Curtis teach the limitations of claims 1, however Curtis further teaches
wherein said object value is expressed in the form of a particular monetary currency. (See para 0052- Since cash, in particular U.S. dollars is one of the main currencies throughout the world, the cash offer is significant to making the program work. ) This teaches monetary currency of US dollars.
Bhasin and Curtis are analogous art because they are from the same problem-solving area of determining 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 combined Bhasin’s invention by incorporating the method of Curtis because Bhasin can use the monetary value to determine importance value for the files. This would be another parameter Bhasin can use, which adds another layer of sophistication to the system.
Regarding Claim 7, Bhasin and Curtis teach the limitations of claims 1, however Bhasin further teaches
wherein said step of generating an object value includes: generating compound data based at least in part on said secondary data accumulated from different sources; and (See figure 3) This shows compound data in determining value for the file objects, this includes the secondary data that is accumulated from different information gathering sources such as access information and sharing information.
using said compound data to generate said object value. (See ¶0032-At 350 one or more importance parameters are generated based on the gathered information. The importance parameters may correspond directly to the gathered information, or may be a filtered or modified subset of the gathered information. At 360 the relative importance of the file is determined based on the importance parameters and weightings or rules associated with the various importance parameters. ) Object value or importance is calculated based on the secondary compound data seen above.
Regarding Claim 8, Bhasin and Curtis teach the limitations of claims 7, however Bhasin further teaches
wherein said compound data includes user activity data associated with said file system objects, said user activity data indicative of activity of users of said file storage system with respect to said file system objects. (See ¶0029-30At 330 file sharing information is gathered, for example the number of users whom a file is shared with (accessible to) and/or the relationship in an organization database between different users who share the file (for example whether they all work in the same department or different departments and their relative levels in the organization). At 340 file access information is gathered. This information may be gathered at the kernel level, for example when a particular file is accessed. The information may be used to generate an importance parameter relating to file access, for example the frequency with which a file is accessed. In this disclosure the frequency with which a file is accessed is not used alone to determine the relative importance of the file, however the frequency of access may be used together with other importance parameters to determine the relative importance of the file.) This shows user activity with respect to file objects that include sharing files, accessing files, and frequency of accessing the files.
Regarding Claim 9, Bhasin and Curtis teach the limitations of claims 1, however Bhasin further teaches
Accumulating primary data indicative of content of said individual ones of said file system objects; (See ¶0027-0028-At 310 the presence of particular keywords in the file is determined. Such key words may be pre-set by a system administrator and this information may be obtained by searching the contents of the file at 340. The presence or absence of particular key words may in itself be an importance parameter.
At 320 the author of the file is determined. The author of a file is an importance parameter. Certain authors may have a greater importance attached to their files, due to their role in an organization.) This shows primary data of individual file. This can be done for multiple files. Primary data deals with content of the actual file system objects.
Arranging said primary data in said storage device. (See ¶0040-The user space may host an attribute feeder 560 which filters and/or processes information from the event feeder 520 in order to generate one or more importance parameters which are passed on or made available to the ICE 110. The ICE 110 determines the relative importance of the file and communicates with the MPE 120 which applies an appropriate information management policy to the file based on the file's relative importance.) This shows the information gathered is arranged in the storage device because it is sent to ICE item 110 which is the storage device to determine importance of the file.
Regarding Claim 10, Bhasin and Curtis teach the limitations of claims 9, however Bhasin further teaches
wherein said step of accumulating primary data includes scanning said individual ones of said file system objects to obtain said content from said individual ones of said file system objects. (See ¶0027-0028-At 310 the presence of particular keywords in the file is determined. Such key words may be pre-set by a system administrator and this information may be obtained by searching the contents of the file at 340. The presence or absence of particular key words may in itself be an importance parameter.
At 320 the author of the file is determined. The author of a file is an importance parameter. Certain authors may have a greater importance attached to their files, due to their role in an organization.) This shows primary data of individual file. This can be done for multiple files. Primary data deals with content of the actual file system objects. The system is scanning these files when it is gathering the content information.
Regarding Claim 11, Bhasin and Curtis teach the limitations of claims 9, however Bhasin further teaches
wherein said step of accumulating primary data includes
Categorizing said individual ones of said file system objects based at least in part on said content of said individual ones of said file system objects. (See ¶0027-0028-At 310 the presence of particular keywords in the file is determined. Such key words may be pre-set by a system administrator and this information may be obtained by searching the contents of the file at 340. The presence or absence of particular key words may in itself be an importance parameter.
At 320 the author of the file is determined. The author of a file is an importance parameter. Certain authors may have a greater importance attached to their files, due to their role in an organization.) This shows primary data of individual files. These are later categorized with respect to item 110 as seen in Fig. 4. In another interpretation the information gathered from primary data includes categorizing information into importance parameters as seen here (See 0031-At 350 one or more importance parameters are generated based on the gathered information.)
Regarding Claim 12, Bhasin and Curtis teach the limitations of claims 9, however Bhasin further teaches
further comprising utilizing at least a portion of said primary data and said secondary data to generate compound data, said compound data being indicative of relationships between individual ones of said file system objects. (See figure 3- this shows utilizing primary and secondary data to generate compound data that item 110 uses to determine importance of a file) Compound data includes relationships between the file objects with respect to uniqueness information that is gathered. (See ¶0026-At 300 information relating to the uniqueness of the file is gathered. The ‘uniqueness’ of the file means the uniqueness compared to other files in a storage system.)
Regarding Claim 13, Bhasin and Curtis teach the limitations of claims 12, however Bhasin further teaches
wherein said step of utilizing at least a portion of said primary data and said secondary data to generate compound data includes estimating the similarity of two or more different ones of said file system objects, based at least in part on said primary data. (See ¶0026-At 300 information relating to the uniqueness of the file is gathered. The ‘uniqueness’ of the file means the uniqueness compared to other files in a storage system. The ‘storage system’ in which the comparison is made depends upon the context and may be the storage medium on which the file is stored, or may be a larger storage system. Thus the comparison may be to other files on the same storage medium only, other files on the same device, other files belonging to the same user, or other files in the enterprise storage system as a whole (if the system is applied in an enterprise setting). The specific comparison used to determine uniqueness may be set by a system administrator and may for instance be determined by scanning files with a program operating at the application level.) This shows the system determines uniqueness of a file compared to another file. Uniqueness is a measure of similarity between files. The art is capable of this being based on primary data and secondary data since the criteria is set by the system administrator.
Regarding Claim 14, Bhasin and Curtis teach the limitations of claims 1, however Bhasin further teaches
wherein said step of accumulating secondary data includes
Accessing metadata associated with said individual ones of said file system objects. (See ¶0028-29 At 320 the author of the file is determined. The author of a file is an importance parameter. Certain authors may have a greater importance attached to their files, due to their role in an organization. At 330 file sharing information is gathered, for example the number of users whom a file is shared with (accessible to) and/or the relationship in an organization database between different users who share the file (for example whether they all work in the same department or different departments and their relative levels in the organization). This shows meta-data is accessed which is data about the file data.
Regarding Claim 15, Bhasin and Curtis teach the limitations of claims 1, however Bhasin further teaches
wherein said step of accumulating secondary data includes accumulating data indicative of an infrastructure of said file storage system. (See fig. 1A- this shows infrastructure of file storage system) Obtaining the secondary data is done with respect to this infrastructure of the files.
Regarding Claim 16, Bhasin and Curtis teach the limitations of claims 1, however Bhasin further teaches
further comprising expressing said object value of said at least one of said file system objects relative to object values of others of said file system objects. (See ¶0034-As the files are automatically classified according to their relative importance, in some implementations a report may be run to indicate the amount of storage space used up by files of each category (e.g. space occupied by confidential files, personal critical files, business critical files etc.).) Determining storage space used up by the files compared to other files shows a relative measure of the files to each other.
Regarding Claim 18, Bhasin and Curtis teach the limitations of claims 1, however Bhasin further teaches
further comprising utilizing said object value of said at least one of said file system objects to inform IT policy changes relating to said particular entity. Informing of the IT policy changes are seen with respect to item 120 which is the MPE (See ¶0023-In one example, the information management policy engine (MPE) 120 of the present disclosure may be implemented as a plug-in to an existing information management system. In this case the MPE 120 actively or passively obtains the relative importance of the file from the ICE 110. The MPE 120 converts the relative importance into settings or policies used by the information management system. As discussed above, in some implementations the relative importance may be expressed as an information management policy (IM) profile. In some implementations there may be a plurality of possible IM profiles and each profile may be mapped by the MPE 120 to an archive, back-up and security policies of the information management system. An example mapping is given in the table below.
IM Profile Back-up Policy Archive Policy Security Policy Business Create 3 copies of No archiving, as Encrypt data Critical file; Back-up every the data should using 2048 bit change to the file always be encryption available. Personal Backup every Archive to a local Encrypt data Critical change of file office using 1024 bit encryption Personal Backup No archiving No encryption General incremental data required once a week. Run full backup monthly General Backup No archiving No encryption incremental data required once a week. Run full backup monthly Confidential Backup every Archive to most 2048 bit change of file available storage encryption Other Backup once a Archive to No encryption month) cheapest storage required)
Regarding Claim 19, Bhasin and Curtis teach the limitations of claims 1, however Bhasin further teaches
wherein said step of accumulating secondary data includes accessing said file system objects of said file storage system over a wide area network. (See ¶0015-For example the remote storage system may be a server, NAS (network attached storage), SAN (storage area network), storage provided by a data centre etc.) (See ¶0039-The kernel space 510 may host an event feeder 520 which is a component of the operating system which provides information about the files or file accesses to applications running in the user space 550. For example, the event feeder 520 may detect file system or network access to a file and provide information about the file and the file access to applications in the user space 550.) This shows that the files can be accessed over a network.
Claim 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Bhasin et al. (US20130262418A1) herein Bhasin in further view of Curtis (US20180240144A1) herein Curtis in further view of Pather et al. (US20040002972A1) herein Pather.
Regarding Claim 17, Bhasin and Curtis teach the limitations of claims 1, however they do not teach
wherein said step of expressing said object value of said at least one of said file system objects relative to object values of others of said file system objects includes expressing said object value relative to a base value that is equal to a lowest object value of said object values of said others of said file system objects.
However Pather teaches wherein said step of expressing said object value of said at least one of said file system objects relative to object values of others of said file system objects includes expressing said object value relative to a base value that is equal to a lowest object value of said object values of said others of said file system objects. (See ¶0561-For example, referring to FIGS. 20 and 21, diagrams illustrates a scheme wherein texts 2036, 2136 are categorized into low, medium, and high priority. As described above, a plurality of other training sets may be employed to provide greater or higher resolution distinctions of priorities. The text classifier 2020, 2120 is trained by a group of texts 2047, 2147 that are high priority and a group of texts 2048, 2148 that are low priority, and by a group of texts 2150 that are medium priority. Thus, the text 2036, 2136 to be analyzed is input into the classifier 2020, 2120, which outputs a scalar number 2049, 2149, that can measure the likelihood that the text being analyzed is of high priority, if so desired, or medium priority or low priority, for example. ) This shows a base value which is the lowest value with respect to low priority.
Bhasin and Pather are analogous art because they are from the same problem-solving area of classification. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined Bhasin’s invention by incorporating the method of Pather because Bhasin can use the priority ranking to further classify the files to the users. In addition to confidential or critical files, Bhasin can further classify into high, medium, or low priority. This gives more insight into the values of the files.
Conclusion
The prior art made of record and not relied upon considered pertinent to Applicant’s disclosure.
Desai (20220343483) Discloses a system and method for determining a like grade and value or range of values for collectible cards.
Cole (20200327565) Discloses a method, computer system, and computer program product that aggregates sample data regarding a plurality of factors associated with employment and geographic location; performs iterative analysis on the sample data using machine learning to construct a predictive model; populates, using the predictive model, a database with predicted values of real estate demand for a selected set of predefined geographic regions
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MUSTAFA IQBAL whose telephone number is (469)295-9241. The examiner can normally be reached Monday Thru Friday 9:30am-7:30 CST.
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/MUSTAFA IQBAL/Primary Examiner, Art Unit 3625