WO2016201228A1 - A device and method for categorizing data - Google Patents

A device and method for categorizing data Download PDF

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Publication number
WO2016201228A1
WO2016201228A1 PCT/US2016/036895 US2016036895W WO2016201228A1 WO 2016201228 A1 WO2016201228 A1 WO 2016201228A1 US 2016036895 W US2016036895 W US 2016036895W WO 2016201228 A1 WO2016201228 A1 WO 2016201228A1
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WO
WIPO (PCT)
Prior art keywords
computing device
electronic communication
processor
user
database
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PCT/US2016/036895
Other languages
French (fr)
Inventor
Keith A. Raniere
Original Assignee
First Principles, Inc.
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
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Publication date
Priority to US201562174585P priority Critical
Priority to US62/174,585 priority
Application filed by First Principles, Inc. filed Critical First Principles, Inc.
Publication of WO2016201228A1 publication Critical patent/WO2016201228A1/en

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Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computer systems using knowledge-based models
    • G06N5/04Inference methods or devices
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00Commerce, e.g. shopping or e-commerce
    • G06Q30/02Marketing, e.g. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards; Price estimation or determination
    • G06Q30/0241Advertisement
    • G06Q30/0251Targeted advertisement
    • G06Q30/0255Targeted advertisement based on user history
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00Commerce, e.g. shopping or e-commerce
    • G06Q30/02Marketing, e.g. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards; Price estimation or determination
    • G06Q30/0241Advertisement
    • G06Q30/0251Targeted advertisement
    • G06Q30/0261Targeted advertisement based on user location

Abstract

A computing device for receiving an electronic communication from a user of the computing device or a separate computing device, a local storage medium coupled to the processor, the local storage medium storing an identification system for identifying the electronic communication received from the user or separate computing device, and a database system for cataloging electronic communication. The computing device draws inferences and making conclusions regarding the electronic communication and presenting suggestions to the computing device user. Associated methods are also provided.

Description

A DEVICE AND METHOD FOR CATEGORIZING DATA

FIELD OF TECHNOLOGY

The following relates to the field of data collection and pattern recognition and more specifically to embodiments of a device and method for populating a dynamic database including information about one or more users, including relationships associated with time and physical location of one or more database entries,

BACKGROUND

Data collected and entered into a conventional database only provides limited information based on the descriptions for the entries correlating to a single data point. Databases only provide a window into the collected data, when the data was collected and entered into the system. Data collection and categorization databases do not categorize or track the evolution of the data, previously inputted, over a timeframe or update changes to the data based on the perceived changes detected by at least one of the five senses.

Thus, a need exists for a device and method for dynamically categorizing data using information inputted from the identification and parsing of electronic communications including the location and time of the communication.

SUMMARY

A first aspect relates to a computing device comprising a processor capable of receiving electronic communication from at least one of an input device and a separate computing device, a local storage medium coupled to the processor, the local storage medium storing an identification system, an inference engine and a database system, wherein the processor records a time of the electronic communication, a location of the electronic communication and a source of the electronic communication in the database system, wherein the processor determines an action based on information available in the database system; and wherein the processor suggests the action to at least one user of the computing device.

A second aspect relates to a method comprising the steps of receiving, by a processor of a computing device, an electronic communication from an input device of the computing device or a separate computing device, identifying, by the processor, the electronic communication received from the input device or the separate computing device, accessing, by the processor, a database system, entering, by the processor, a record of the electronic communication into the database system wherein the record includes a timestamp, a location, and a source of the electronic communication, determining, by the processor, an action based on at least one record of the database system and presenting, by the processor, the action based on at least one record of the database to at least one user of the computing device.

BRIEF DESCRIPTION OF THE DRAWINGS

Some of the embodiments will be described in detail, with reference to the following figures, wherein like designations denote like members, wherein:

FIG. 1 depicts a schematic view of an embodiment of a computing device;

FIG. 2 depicts a schematic view of an embodiment of the computing device connected to other computing devices over a network;

FIG. 3 depicts a flowchart of an embodiment of a computing device implementing a first embodiment of steps to selectively manage incoming electronic communication; and FIG. 4 depicts a flowchart of an embodiment of a computing device implementing a second embodiment of steps to selectively manage incoming electronic communications.

DETAILED DESCRIPTION

A detailed description of the hereinafter described embodiments of the disclosed system and method are presented herein by way of exemplification and not limitation with reference to the Figures. Although certain embodiments of the present invention will be shown and described in detail, it should be understood that various changes and modifications may be made without departing from the scope of the appended claims. The scope of the present disclosure will in no way be limited to the number of constituting components, the materials thereof, the shapes thereof, the relative arrangement thereof, etc., and are disclosed simply as an example of embodiments of the present disclosure.

As a preface to the detailed description, it should be noted that, as used in this specification and the appended claims, the singular forms "a", '"an" and "the" include plural referents, unless the context clearly dictates otherwise.

FIG. 1 depicts an embodiment of a computing device 100. A computer device 100 may comprise any device or apparatus which may contain a processor 103, a local storage medium, such as computer readable memory 105, and an input and output device 115. Embodiments of the computer readable memory 1.05 may include permanent storage medium and RAM. Embodiments of computing device 100 may be desktop computers, laptops, tablets, chromebooks, netbooks, smartphones or other mobile or cellular phones, servers, internet connected televisions, video game consoles, smart appliances, media player devices such as an iPod® or iPod-like devices, and media devices integrated with automobiles. Embodiments of computing device 100 may further include a display 118 for presenting content visually to a user, a digital-to-analog converter 113 which may be used to present content to the user auditorily, a receiver 116, a transmitter 117, a power supply 109 for powering the computing device 100, and a voice user interface 108. Furthermore, embodiments of the computing device 100 may be a computing system, a component of or part of a computing system, and may be configured to connect to a local network or Internet enabled network. An embodiment of a network including one or more additional computing devices communicating over the network 7, is shown in FIG. 2. A network may be any system, that links two or more computing devices together. Embodiments of the network 7 may be a cellular network, data network, a Wi-Fi network, tethered devices, local access network (LAN), wide access network (WAN), personal area network (PAN), fiber optic network, intranet, and the like.

Embodiments of processor 103 may be any device or apparatus capable of carrying out the instructions of a computer program. The processor 103 may carry out instructions of the computer program by performing arithmetical, logical, input and output operations of the system. In some embodiments, the processor 103 may be a central processing unit (CPU) while in other

embodiments, the processor 103 may be a microprocessor, or a GPU. In an alternative embodiment of the computing system, the processor 103 may be a vector processor, while in other embodiments the processor may be a. scalar processor. Additional embodiments may also include a cell processor or any other existing processor available. Embodiments of a computing device 100 may not be limited to a single processor 103 or a single processor type, rather, it may include multiple processors and multiple processor types within a single system or computing architecture that may be in communication with each other.

Moreover, embodiments of the computing device 100 may also include a local storage medium, such as memory 105. Embodiments of the local storage medium 105 may be a computer readable storage medium., and may include any form of primary or secondary memory, including magnetic tape, paper tape, punch cards, magnetic discs, hard disks, optical storage devices, flash memory, solid state memory such as a solid state drive, ROM, PROM, EPROM, EEPROM, RAM or DRAM. Moreover, embodiments of local storage medium 105 may be primary memory that includes addressable semi-conductor memory such as flash memory, ROM, PROM, EPROM, EEPROM, RAM, DRAM, SRAM and combinations thereof. Embodiments of a computing device 100 that includes secondary memory may include magnetic tape, paper tape, punch cards, magnetic discs, hard disks, and optical storage devices. Furthermore, additional embodiments using primary memory, secondary memory or a combination thereof may further utilize virtual memory. In an embodiment using virtual memory, a computing device 100 may move the least used pages of primary memory to a secondary storage device. In some embodiments, the secondary storage device may save the pages as swap files or page files. In a system using virtual memory, the swap files or page files may be retrieved by the primary memory as needed.

Embodiments of the local storage medium 105 may be computer readable memory.

Computer readable memory may be a tangible device used to store programs such, as sequences of instructions. In addition, embodiments of the local storage medium 105 may store data such as programmed state information, databases and one or more software components of the inference engine including an interpreter, scheduler and consistency enforcer. For instance, embodiments of the local storage medium 105 may include, contain, or store an identification system 210, an inference engine 2,20 and a database system, 2,30. Embodiments of the identification system 210, inference engine 220 and the database system 230 are described in greater detail infra.

Moreover, the local storage medium 105 may store programs or data on a temporary or permanent basis. In some embodiments, the local storage medium 105 may be primary memory while in alternative embodiments, it may be secondary memory. Additional embodiments may contain a combination of both primary and secondary memory. Although embodiments of the computing device 100 are described as including a local storage medium, a computing device may also be coupled over wireless or wired network to a remote database or remote storage medium, that contains embodiments of the identification system 210, inference engine 220 and the database system 230.

Referring still to FIG. 1, embodiments of computing device 100 may further include an input/output (I/O) interface 115. Embodiments of the I/O interface 115 may act as the communicator between computing device 100 and the world outside of the computing device 100. Inputs may be generated by users such as human beings or they may be generated by other computing systems. Inputs may be performed by an input device while outputs may be received by an output device from the computing device 100. Embodiments of an input device may include one or more of the following devices: a keyboard, mouse, joystick, control pad, remote, trackball, pointing device, touchscreen, light pen, camera, camcorder, microphone (s), biometric scanner, retinal scanner, fingerprint scanner, haptic device or any other device capable of sending signals to a computing device/system. Embodiments of output devices may be any device or component that provides a form of communication from the computing device 100 in a human readable form and/or perceptible form (e.g. perceptible by a human through a human sense). Embodiments of a computing device 1.00 that include an output de vice may include one or more of the following devices: displays, monitors, printers, speakers, headphones, graphical displays, tactile feedback, projector, televisions, plotters, or any other device which communicates the results of data processing by a computing device in. a human-readable form.

With continued reference to FIG. 1, embodiments of computing device 100 may include a receiver 116. Embodiments of a receiver 116 may be a device or component that can receive a form of communication or signal from another device such as a networked computing device. A receiver may receive communication in the forms of radio waves, blue tooth, Wi-Fi signals and other electromagnetic frequencies and convert them into a usable form, such as in combination with an antenna. The receiver 116 may be coupled to the processor of the computing device 100. Embodiments of the receiver 116 coupled to the processor 103 may receive an electronic communication from a separate computing device 401, 402, 403 over a network 7.

Embodiments of the computing device 100 may include a transmitter 117. The transmitter 117 may be a device or component that can emit or communicate information using signals, to transmit data or data packets, to other computing devices capable of receiving the information. Examples of acceptable means of communication may include electromagnetic transmission such as radio waves, bluetooth, Wi-Fi and infrared. In alternative embodiments, the transmitter 117 and receiver 116 may be a single unit such as a transceiver, capable of both sending and receiving information and signals containing data.

Moreover, embodiments of the computing device 100 may include a voice user interface 108. Embodiments of a voice user interface 108 may be a speech recognition platform that can convert an analog signal or human voice communication/signal to a digital signal to produce a computer readable format in real-time. One example of a computer readable format is a text format.

Embodiments of the voice user interface 108 may continually process incoming audio by the user operating the computing device 100 or the audio generated by the environment surrounding the computing device 100. For instance, embodiments of the voice user interface 108 coupled to the processor 103 may receive a voice communication from a user without a physical interaction between the user and the device 100. For example, a user may make a comment about his surrounding environment such as general statement regarding the need for repairs. The device 100 may use the voice user interface 108 to record and convert the statement into text. In one embodiment, the voice user interface 108 may be pre-programmed with one or more keywords, triggers or commands that prompt the interface 108 to record or pay particular attention to the phrase recorded by the device 100. Because the voice user interface 108 may continually process incoming audio, once the voice user interface 108 recognizes a trigger/command given by the user, the processor coupled thereto may performs a particular action such as initiate the database system 230 to log information about the audio that triggered the keyword.

In an alternative embodiment, a user may program one or more keywords or phrases that may be set to initiate the device 100 to parse the audio for information. In yet an additional embodiment, a device 100 may track words consistently used by the user. The device 100 may conclude on its own that certain words or phrases merit initiation, recordation and entry into the database system 230.

The continuous processing of audio by the voice user interface 108 may commence when the electronic communication is first received, or the device 100 may be continuously processing audio through the voice user interface 108 so long as power is being supplied to the computing device 100. Furthermore, embodiments of the voice user interface 108 may continuously collect and process incoming audio through one or more microphones of the computing device 100. Alternative embodiments may include external or peripheral accessories that are wired or wirelessly connected to the computing device 100 which may also collect audio for processing by the processor 103 of the computing device 100. Embodiments of the collected and processed audio may be the voice of the user of the computing device 100, audio generated by the surrounding environment. For example, a series of wireless microphones may be placed throughout a location or series of locations collecting audio and submitting the audio to a central device 100 which has the voice user interface loaded in its memory.

FIG. 3 depicts an embodiment of a computing device receiving an electronic communication and generating an entry into the database system 230 then using the entry in the database 230 to draw inferences or conclusions about the data in the inference engine 220 followed by presenting a recommendation or useful information to the user. An electronic communication may be any type of electronic signal which may be recognized and decoded by the computing device 100. Electronic communication may include signals generated and transmitted to the communication device 100 by a separate computing device. For example, electronic communication sent by a separate computing device may include data requested from internet servers, computing devices 401, 402, 403 part of the same network 7 and computing devices communicating from an outside network such as a Verizon smartphone interacting with an AT&T smartphone or desktop computer for example.

Other embodiments of electronic communication may include signals sent by the user to the computing device 100. For instance, the electronic communication submitted by the user may include keystrokes on a keyboard or touch screen, an audio recording, mouse inputs, search engine queries, recorded videos, and browser activity. In addition, electronic communication in general may also include incoming or outgoing emails, text messages, downloads, file transfers, phone calls, VoIP, instructions to load a program into memory, documents, photos and data packets.

In step 301, embodiments of the computing device 100 may receive an electronic communication. The electronic communication may be generated by the user's action on the computing device or the electronic signal may be incoming from a separate computing device such as a networked device 401. Any computing device capable of transmitting an electronic signal to the computing device 100 may suffice. For example, a device such as cellular phone or personal computer may receive a text message, phone call or data packet transmission from another computing device such as a networked computer or cellular phone 401; the user's cellular phone or personal computer may or may not indicate to the user that the electronic communication has initially been received. In another example, the electronic communication received may be a response to a user initiated query such as a user using the computing device 100 to interact with a web server followed by the web server providing a response. Both the action provided by the user on an input device 115 and the response by the web server may be a form of electronic communication with the computing device 100. In step 302, embodiments of the computing device 100 may identify the received electronic communication. The step of identification may include determining various parameters that the computing device 100 may find useful for generating a dynamic database. Embodiments of the computing device 100 may include an identification system 210 stored in a local storage medium 105 that may identify the electronic communication received by the computing device 100. For instance, when the electronic communication is received, the identification system 210 may determine and identify parameters for the dynamic database which may include the source of the communication, the geographic location of both the computing device 100 and/or the device transmitting the electronic communication, the content of the electronic communication, metadata or descriptions of the incoming communication, time of transmission and/or the timing for receipt of the communication, .

in one embodiment, the source of the electronic communication may include a unique identifier such as known contact information, phone number, address, available name, IP address, email address, MAC address, file type, file size, network associated with the transmitting device, servers used to transmit the electronic communication and other various characteristics of the electronic communication's origin and type. For example, the source of the electronic

communication may include information that may allow it to be uniquely identified. In some embodiments, it can take several pieces of information to uniquely identify an entity— e.g. name and address, and the information accompanying the communication may require augmentation from another source like a database in order to provide uniqueness. Those having skill in the art should appreciate that various methods may be employed to identify the content, characteristics and other identifying information of the received electronic signal/communication.

Embodiments of the computing device identifying the electronic communication may further identify the content of the electronic communication. In some embodiments, the incoming electronic communication may be in a text based format. The text may be parsed for keywords and descriptions of the electronic communication. Examples of a text based electronic communication that may be parsed may include email, text message, MS word .doc files and .pdf files. In another embodiment, the computing device may convert the incoming electronic communication into textual format that may be parsed for keywords. For example, audible language such as a phone call or recorded message may be transcribed into text and parsed by the computing device 100 for keywords and identifying language that may help describe the content of the electronic communication. Keywords may include any noun and the computing device may additionally modify the noun identify functional relationships between the keywords and the user. For example, a keyword may be associated with a noun such as a backyard. The computing device may recognize "my backyard" and identify "my backyard" into the relationship wherein the backyard is the user's as opposed to the user identifying "my friend's backyard" which belongs to someone else. The computing device may identify spatial relationships between one or more of the keywords to determine the content of the keyword. For example the keyword "my backyard" may be further identified by having an additional keyword associated with it such as '"the pool" in "my backyard".

Furthermore, in some embodiments where the electronic communication is a file being transmitted, identification of the content of the file may be determined using metadata associated with the file. For example, if a user receives an electronic communication such as a music track from an Mp3 server such as iTunes®, identification system 210 may gather metadata from the track which may include the artist's name, song title, album the song is on, the date of publishing, the price paid, iTunes® user name and a serial key associated with the download. The metadata is not strictly limited to files such as music, any file type including video, text, web pages, GPS and even cellular phone communications may also include identifying information in the form of metadata. For example, website metadata may include the web address, page title, associated keywords, date of transmission, date the file was last modified and a brief description of the file.

The computing device 100 may further utilize the identification system 210 to determine the location and position of the computing device 100 and/or the location of the device transmitting the electronic communication. The location and position of either computing device may be acquired using a global positioning system (GPS), ceil tower triangulation, Wi-Fi network triangulation, Wi- Fi positioning system (WPS), satellite positioning, Bluetooth® and RFID or a combination thereof. In some embodiments, a combination of positioning methods may be used which may offer more precise locations. For example, an embodiment may determine the origin point of an electronic communication transmission by receiving both GPS to determine the general position and then RFID to ping the transmitting device's precise position in relation to one or more RFID broadcasting points. In some embodiments, the positioning system determining the location may be physical hardware within the computing device which tracks and broadcasts the position of the device. In another embodiment, the positioning system may include software capable of determining positioning from external hardware such as satellites, cell towers and Wi-Fi enabled routers acting access points.

Embodiments of the identification system 210 may further identify the electronic communication 302 by tracking the time of transmission by the transmitting device or the time of receipt of the electronic communication by the computing device 100. In one embodiment, the ttansmitting device may timestamp the file, or place a timestamp in the metadata of the electronic communication, which may be read by the recipient device 100. The recipient device may track the point in time wherein the electronic communication is first received. In an alternative embodiment, a transmitting device may not provide a time stamp. The computing device receiving the transmission may have to make a determination of the time that the transmission of the electronic communication occurred. One method that may be employed is to contact the transmitting device and calculate the time it takes to contact and receive a response from the device. For example, the computing device 100 may send a small test packet of information to the transmitting device requesting a response. From there, the computing device may calculate an estimated transmission time to determine the approximate amount of time it took to receive the electronic communication and accord an appropriate time of transmission to electronic communication originally received from the transmitting de vice.

The computing device 100 may further generate a database entry using the database system 230. In one embodiment, the database system 230 may be used to track, record and/or catalog all information identified by the identification system 210 during step 302. The database system 230 may use the fields populated by the identification system 210 to create a dynamic database which can track or change its database entries based on new information derived from, incoming electronic communication, information for one or more entries may change over the course of time and the database may be dynamically updated when those changes occur. Unlike static database systems, a dynamic database may identify database entries as being older or newer entries of one another and the database system may maintain all entries from each point in time that a new entry is created and updated. Both the changes and the consistent nature of a database entry over the course of its existence may provide details and data that may be useable by the computing device when assisting the user. For instance a database entry that receives a new entry every day may be determined to be something important to the user, or the object of the entry is more prone to being manipulated and changed versus an entry that is rarely updated because the entry reflects information that does not fluctuate or is rarely used by the user. For example, a database entry comprising information about reminders will fluctuate more frequently than information in the database about household appliances. Entries for reminders may be entered hourly, daily and weekly, while a household appliance entry may be entered upon purchase, repair or replacement.

in one embodiment, the dynamic database generated by the database system 230 may allow the user access to multiple entries of the same item over a period of time. The computing device 100 and the user may examine the entries and determine how the content of the entry has changed over the time period. A user or the computing device may track and view the depictions of changes in each entry and view how the database entry has evolved, devolved or remained stable or a certain period of time. The database system 230 may include for each entry written descriptions, photographs, video depictions, rendered or composite images, or any other known means to present a representation of the database entry. For example, electronic communication may be received in 2009 regarding the purchase of a house with subsequent communication concerning the features desired by the purchaser, receipts, credit card bills or purchase orders for building materials. From the date of purchase and during the years of ownership, electronic communications received or transmitted may include keywords describing improvements or damage to the house. The database system 230 may record and track changes to physical objects in the real word and may subsequently update each database entry in chronological order to reflect the changes to the physical object over time. For example, under a database entry entitled "home," the most current entry may reflect the user's home in its current condition. The user or the computing device 100 may search through the previous entries at different time periods entitled "home" and view how the house has evolved and changed since the date of purchase all the way to the present. The evolution of a database entry such as the one for "home" may be depicted using written descriptions, photographs, rendered or composite images, video, or any other means that may be used to depict and describe the object of the database entry. In this example, the database entry may reflect additions and upgrades to the home at different points in time or even a new home may have been bought since the original purchase. The entry may also reflect damage to the home such as fires, floods and break-ins.

In step 304, the computing device 100 in some embodiments may analyze the one or more database entries to draw inferences, conclusions and make predictions based on the user's habits. The computing device may incorporate an inference engine 22,0 to scan through the database system 230 and determine correlating patterns amongst the timeline of a database entry or for patterns between different database entries and the entries' associated timeline. An inference engine 220 may be any computer program that uses a knowledge base to derive answers, make prediction or simulate the thought reasoning process of humans. In this embodiment, the inference engine 220 may use the data collected from the database system 230 as its knowledge base for making predictions, inferences, conclusions and recognizing patterns in an effort to assist or gain more knowledge about the user.

The inference engine 220 may focus on the evolution of a single database entry timeline or the inference engine may use the knowledge derived from multiple database entry timelines to simulate the human reasoning process. Using a database entry for a user's car as an example, electronic communication may be tracked and recorded in the database system and used to predict habits about the specific entry over time. A database entry tracking car purchases of a user may include such relevant information as the number purchased vehicles over the last 20 years, the locations the vehicles were purchased from, the make and model of the vehicle, whether the vehicle was new or used, whether the vehicle was purchased for the user or spouse, whether purchase habits have changed from when the individual was a teenager vs. as an adult, whether vehicle purchases differ if they are purchased prior to the summer or prior to the winter. From just the database entry about the vehicle throughout the years, the computing device's inference engine 220 may be able to draw conclusions or make predictions and inferences regarding how often a user purchases vehicles, where they are likely to purchase a vehicle, how much they may be willing to spend, how far the user is willing to travel to purchase the vehicle at the right price, type of vehicle, the make and model expected to purchase, whether the user is shopping for themself or another individual, and whether the user was pleased with the purchase at various times throughout the life of the purchased vehicle. In another example of an embodiment, the database system, 2,30 may record electronic communication which may include data that may be separated and sorted into numerous categories. A computing device's database system 230 may create several organized data entries. In one embodiment, the entries may be identified by the inference system, 2,20 as being interrelated to one another. The inference engine 220 may recognize the relationships between different entries when recognizing patterns, making inferences and drawing conclusions. The inference engine 220 may notice the interdependence of the plurality of database entries and may use one or more of those interdependent entries when it perform its reasoning functions. For example, the computing device 100 may receive electronic communication regarding shopping lists exchanged between a user and another computing device. The identification system 210 may categorize the content of the electronic communication by store, types of products, cost, whether products are purchased online or offline, frequency of purchases and how far a consumer is willing to travel to make the purchase. The database system 230 may record and derive multiple categories of database entries based on the information gleaned from the electronic communication and consistently, update these shopping lists, the users involved, the age of the consumer and changes in pricing or purchasing habits, and even seasonal changes in habits. From this information, the inference engine 220 may be able to predict not only current buying and selling habits, but also future buying and selling habits based on previous trends of the user. Past and present actions entered in the database may assist the inference engine 220 when predicting future trends. The buying and selling habits may be viewed as database entries over a timeline, correlated with or found to be interdependent with other information entered in the database such as income changes, geographic locations, family size, inflation, days of the week, time of the year and who the electronic information exchanges take place with to determine purchasing habits and predict shopping habits as changes in other database entries occur. The computing device's inference engine 220 may be able to make predictions and derive a correlation between different database entries, such as recognizing the changes in a user's shopping habits as their income increases. The computing device may be able to make suggestions for shopping that may have previously been unattainable by the user when the database entry reflects an income increase for the user.

Furthermore, in some embodiments, an individual, or user may contribute to the classification and inference processes via input mechanisms— e.g. the user may add annotations that the inference engine 220 may otherwise not be able to deduce or infer. Likewise, the user may be able to add intelligence to the inference engine 220 to ensure more appropriate results.

In step 305, the computing device may examine all the information generated in each database entry of the database system 230 and the computing device may consider the reasoning of the inference engine 220 in step 304 when making a determination of an action to be initiated or presented to the user. For example, the computing device 100 may determine a correlation between the user's action of signing up for an early morning class and stopping for coffee at the local coffee house before arriving at the class. Based on this correlation, the computing device may determine that it should perform the action of submitting a reminder to the user about stopping for coffee. Alternatively, the computing device using the correlation between the time, location, content and source of the electronic communication in the database system, may arrive at the same conclusion that the user usually purchases a coffee on the way to class, however instead of submitting a reminder, the computing device 100 may also observe database entries about spending habits and available money. The computing device may determine that the best action may be to suggest a cheaper alternative to purchasing coffee from the coffee house, or suggest coupons that will save money. As the database system becomes more robust, or the status of the user changes and is reflected in the database entries, the computing device may also amend its determinations and evolve in a manner that reflects the available data in the database system 230. in an alternative embodiment, the computing device may become reactionary and reflexive to updated entries in the database system 230, wherein upon each updated entry to the database; the inference engine reanalyzes the database and draws conclusions and inferences. This embodiment may simulate the human brain and thought process wherein whenever there are new pieces of data entering, the computing system reanalyzes their decisions as well as the world around them to determine if it should continue with the previous course of action or change the course of action previously determined to be the best.

Embodiments of the method for categorizing data may include step 306, presenting the determined action to a user. In these embodiments, the computing device may, once it determines an action based on the correlations between data in the database system., disclose to the user the action that the computing device recommends. The action may be presented through an output device on the computing device 100 or may be transmitted to a networked device such as a cell phone, tablet or laptop, wherein the networked device's output device, such as a display or graphical user interface, may present the proposed action to the user.

Embodiments of the presentation of the action may be in the form of a message or text on a display screen, email, alert, reminder, or an audible suggestion through at least one speaker. In another embodiment, the computing device may open a third party program to assist the user with performing the action. For example, the computing device 100 may open a navigation program in a situation where the suggested action requires travel to a specific location. In other instances, such as when the suggested action requires viewing media content, the computing device or a networked device may open a media viewing program such as a media player, or website such as iTimes®, YouTube© or Netflix® program. Another embodiment of a presentation may include opening a web page to present information to the user or encourage the user to sign up or purchase an item.

In one embodiment, the computing device may assist the user by presenting information in the most logical order depending on the entries in the database system 230, the current location and the time of day. For example, a. user searching for a place to eat may be presented with results based on their preferences, nearby location, and the food establishments open at the specific time of day or that cater to food appropriate at the current time of day. For instance, if the user is searching for someplace to eat early in the morning and the user typically enjoys eggs or pancakes for breakfast foods, the computing device may determine the best breakfast for the user would be a nearby diner within a certain distance of the user's current GPS coordinates. In another embodiment, the computing device upon examining the most recent electronic communication discussing a scenario with another individual, followed by the user preparing for the discussed scenario within a relatively short timeframe thereafter, the computing device may draw the conclusion that the user is meeting with the individual that the user discussed the scenario with. Using the breakfast example above, the individual who contacted the user may have discussed the possibility of having breakfast together on Saturday morning. On Saturday morning, the user is searching for places to eat breakfast. The computing device may draw the conclusion that the user and the individual who sent the electronic communication about breakfast will be eating together. Subsequently, the computing device may assemble information about the individual, in the correspondence of electronic communication and include that person's known preferences when determining the action to present to the user. The computing device may suggest and present a destination to the user that would accommodate both parties taking part in the meal.

On the other hand, if the user places the search at nighttime, the computing device may more appropriately examine the database system for the user's preferences for dinner and thus may not recommend a diner but rather a steakhouse or another appropriate location given the time of day. Furthermore, the computing device when presenting search results may take into account more than one database entry when determining the appropriate action and presentation. Such additional information may include family size, current income, cost of nearby restaurants, the user's overall willingness to spend money, known allergies and food preferences. In an alternative embodiment, once the user agrees to the suggested action presented by the computing device, the computing device may organize the gathering or submit relevant information to all parties involved. For example, the computing device may submit an. electronic communication to the parties attending the rendezvous, including GPS information, date, time, and other information relevant to the itinerary.

Referring to the drawings, FIG. 4 depicts an embodiment of a computing device/system 100 that may receive an incoming electronic communication, such as from a separate computing device 401, 402, 403, identify the source of the communication, update the database system 230, update the inference engine 220 and selectively determine whether a new action should be presented to the user. In step 601, embodiments of the computing device 100 may receive an electronic communication from the user directly and/or a separate computing device, such as devices 401, 402, 403. For example, a user's cellular phone may receive a text message or a phone call from an acquaintance operating their cellular phone, in step 602, embodiments of the computing device 100 may identify the electronic communication. Embodiments of the computing device 100 may include an identification system 210 stored in a local storage medium 105 that may identify the electronic communication received by the computing device 100. For instance, when the electronic communication is received, the identification system 210 may determine and identify a source, a geographic location, a cellular phone number, a unique identifier, an identity, such as a known contact or available name, and other various characteristics of the electronic communication including the content of the conversation and the time of the transmission, in addition, the identification system 210 may parse the content of the electronic communication including transcribing a phone call or incoming message, such as the text of a text message or an email. Those having skill in the art should appreciate that various methods may be employed to identify the content, characteristics and other identifying information of the received electronic

signal/communication.

In step 603, once the electronic communication has been identified, embodiments of the computing device 100 may access the database system 230 stored on a local storage medium 105 of the computing device 100 to enter the identifying feature of the electronic communication described in step 602. Embodiments of the database system 230 may populate, organize and store the information identified by the identification system, 210 for each database entry. In step 603, once the database system has been accessed, the computing device 100 may determine whether or not the information identified by the identification system 210 has been previously entered into a database entry or whether a new database entry needs to be created.

In step 604, the database system 230 may search the database for identical or related content to the electronic communication. A single electronic communication may include a plethora of content that may be identified and categorized into multiple database entries. For instance an electronic communication may include discussion with the user about numerous subjects and this the database system may parse the communication and categorize each subject into its own database entry and thus perform the searching function of whether a database entry has been created, for each subject the computing device determines warrants a database entry. After the search is completed and it is determined whether or not a database entry exists, the computing device may write the entry to the database. In a situation where the topic being entered into the database has never been written into an entry before, the database may create a new database entry and input all corresponding information identified by the identification system 210. In an embodiment wherein a previous related data entry exists, the database system 230 may create a sub-entry into the database. The sub-entry may include all the information identified in the identification system and associated with an identified keyword at a certain point in time. The sub-entry may be plotted and associated with data of a certain point in time for the overall database entry. The point in time of reference for the data may be attributed to the timestamp when the data was received. A common database entry may be the inclusion of all sub-entries and the first entry in a database, which refer to a keyword in common between the entries of the database. The common database entry may include ail entries associated with a keyword, even if the physical object is not the same object over time. The replacement of one object for another object in the physical world that serves the same function as the keyword used to create the original database entry may still be considered to be represented by the keyword. For example, a database entry for "my car-" will reflect how my car has changed over time, for all cars ever considered to be my car. For example, my car in 2005 may be a red 2005 Corvette. I may own the 2005 corvette until 2010. Each sub-entry from 2005-2010 may depict the changes to the

Corvette, including repairs, additions, damage and modifications. In the year 2011, "my car" may be reflected in the database entry as a 2011 Ferrari. Even though the Corvette is not a Ferrari, they may commonly be referred to as "my car" in a common database entry that reflects the changes to "my car" over time.

Alternatively, the identification system 210 may use the content of the data to determine whether or not the date of receipt is the appropriate time to accord the database entry. For example, if the content of an electronic communication is reminiscent of a point in time that has already past, cues may be taken from the parsing of language to identify when the discussed event occurred. Accordingly, the database entry may reflect the date of occurrence of the reminiscent memory as opposed to the date the reminiscing occurred. For example, the computing device may receive an incoming electronic communication between two colleagues reminiscing about their first day of work at their current job. The content of the interaction may not have occurred on the date of the communication but rather the first day of work. A computing device may search the database to determine the first date of work, or the conversation may include cues regarding the first day of work. The date may be appropriately determined and the database may enter the content of the communication at the appropriate place along a database entry's timeline, in further embodiments, the database entry may reflect the date of the occurrence of the reminiscent memory in addition to the date the reminiscing occurred so that a user can search for all of the times that they reminisced about a particular event.

In step 606, the computing system 100 may determine whether the additional, content written to the database system 210, which may be in the form of a new entry or sub-entry, affect previous, conclusions, inferences and reasoning performed by the inference engine 220. In some embodiments, the updated database may lead to new inferences, conclusions and generally reasoning regarding the data in the database. A modification to the pool of data in the database sy stem and the potential effect on the inference engine, may lead to different conclusion by the computing device regarding the best action to propose to the user. In one instance, the computing system may determine that the action previously proposed is no longer proper and thus may recalculate a new action. Subsequently, if a new action is determined, the computing device may alert the user to the new action or suggestion, as shown in step 607 A. In an embodiment where the new data entered into the database system does not affect the outcome of previously determined actions, the computing system may not alert the user, as shown in step 607B. In step 607A, the system may accommodate for discrepancies between the originally proposed action and the new action. For example, if the user has already acted upon the original action, and it conflicts with or is in some way incompatible with the currently suggested action, embodiments of the system may accommodate for a discrepancy between the new action and the currently suggested action.

Ref erring now to FIGs. 1-4, embodiments of a processor 103 of a computing device/system 100 may execute or implement steps according to software loaded in its memory 105. Embodiments of the software may be any set of machine readable instructions which may direct the processor 103 of the computing device/system 100 to perform one or more specific operations. In alternative embodiments, the software may be a source code, binary code or a combination thereof. In some embodiments, the software may be in the form of application software. As seen in the exemplary embodiment depicted in FIG.l, the software may be loaded into the computer readable memory 105 of the computing system 100. In alternative embodiments, the software may be embedded software which may reside in the firmware of embedded systems.

Embodiments of the computing device 100 executing the steps of software may authenticate and/or analyze incoming communication from both a first user and electronic data coming from a second user. Moreover, embodiments of the computing system 100 may also covert voice, audio and video signals from an electronic communication into computer readable data, such as text for being parsed and entered into the database system. Embodiments of an electronic communication from a separate computing device or system 401, 402, 403 may be a SMS message, a MMS message, a text message, an email, a radio link, a signal from the Internet, a satellite communication, a signal sent over a cellular network, Wi-Fi network, or Bluetooth® network, or any communication using an electrical signal or electromagnetic waves.

Embodiments of computing system 100 running the software described herein may execute or implement the steps of receiving, by a processor 103 of the computing device 100, an electronic communication, identifying, by the processor 103, the electronic communication received, recording, by the processor 103, the identified information of the electronic communication, recognizing, by the processor 103, a correlation between the recorded information of the electronic communication and previously recorded electronic communication, determining, by the processor 103, an action based on the correlation between one or more recorded electronic communications, presenting, by a processor 103, an action to a user.

Further embodiments of the computing device 100 running software may execute or implement the steps of receiving, by a processor 103 of a computing device 100, an electronic communication from an input device 115 or a separate computing device such as a networked device 401, 402, 403, identifying, by the processor 103, the electronic communication received from the input device or separate computing device, accessing, by the processor 103, a database system 230 to determine an entry level, in response to receiving the electronic communication, wherein if a database entry previously exists for the subject matter of the electronic communication, a sub-entry is added and if there is not a database entry for the subject matter of the electronic communication, a new entry in the database system is added, followed by entering, by the processor 103, a record of the electronic communication into the database system, wherein the record being entered includes a timestamp of the electronic communication, a location of the communication, the content of the communication and the source of the communication. Moreover, a computing device 100 running software may further execute or implement the steps of evaluating, by a processor 103, the data present in the database system, and determining, by the processor 103, an action to be performed based on at least one record of the database system. Some embodiments may also include the step of presenting, by a processor 103, an action based on the evaluation of the database system which may include one or more records or actions to one or more users of the computing device.

While this disclosure has been described in conjunction with the specific embodiments outlined above, it is evident that many alternatives, modifications and variations will be apparent to those skilled in the art. Accordingly, the preferred embodiments of the present disclosure as set forth above are intended to be illustrative, not limiting. Various changes may be made without departing from the spirit and scope of the invention, as required by the following claims. The claims provide the scope of the coverage of the invention and should not be limited to the specific examples provided herein.

Claims

CLAIMS The claims are as follows:
1. A computing device comprising:
a processor capable of receiving electronic communication from at least one of an input device and a separate computing device;
a local storage medium coupled to the processor, the local storage medium storing an
identification system, an inference engine and a database system;
wherein the processor records a time of the electronic communication, a location of the
electronic communication and a source of the electronic communication in the database system;
wherein the processor determines an action based on information available in the database system; and
wherein the processor suggests the action to at least one user of the computing device.
2. The computing device of claim 1, wherein the separate computing device is a network
computing device.
3. The computing device of claim 1, wherein the separate computing device is a cellular telephone.
4. The computing device of claim 1 , wherein the location of the electronic communication is
determined by at least one of GPS, cell tower triangulation and trianguiation of wireless networks.
5. The computing device of claim 1, wherein the source of electronic communication is at least one additional user of the computing device.
6. The computing device of claim 1, wherein the processor determines an action from an inference drawn between two or more entries in the database system.
7. The computing device of claim 1 wherein the processor determines an action from an inference between two or more sub-entries of a. database system entry
8. The computing device of claim 1, wherein the electronic communication is at least one of an audio file, a video file, an electronic document, SMS message, a MMS message, a phone call, and at least one data packet.
9. A method comprising the steps of:
receiving, by a processor of a computing device, an electronic communication from an input device of the computing device or a separate computing device;
identifying, by the processor, the electronic communication received from the input device or the separate computing device;
accessing, by the processor, a database system;
entering, by the processor, a record of the electronic communication into the database system wherein the record includes a timestamp, a location, and a source of the electronic communication;
determining, by the processor, an action based on at least one record of the database system; presenting, by the processor, the action based on at least one record of the database to at least one user of the computing device.
10. The method of claim 9, wherein the separate computing device is a network computing device.
11. The method of claim 9, wherein the separate computing device is a cellular telephone.
12. The method of claim 9, wherein the method further includes the step of determining the location of the electronic communication by at least one of GPS, cell tower triangulation and triangulation of wireless networks.
13. The method of claim 9, wherein the method further comprises an additional step of determining the source of electronic communication , wherein the processor tracks at least one user of the computing device and at least one user of the separate computing device.
14. The method of claim 9, wherein the method comprises an additional step of drawing at least one inference based on two or more entries in the database system.
15. The method of claim 9, wherein the step of presenting further comprises the step of at least one of displaying the action based on at least one record of the database to at least one user of the computing device and audibly notifying the user through one or more speakers of the computing system.
16. The method of claim 9, wherein the electronic communication is at least one of an audio file, a video file, an electronic document, SMS message, a MMS message, a phone call, and at least one data packet.
17. A method of categorizing data, comprising the steps of:
receiving, by a processor of a computing device, one or more electronic communications from an input device of the computing device or a separate computing device; identifying, by the processor, the one or more electronic communication received from the input device or the separate computing device;
parsing, by the processor, the one or more electronic communications received from the input device or the separate computing device into one or more keywords;
creating, by the processor, a database entry for each of the one or more electronic
communications for each one or more keywords, wherein one or more electronic communications containing common keywords form a common database entry; organizing, by the processor, each common database entry into a chronological order, wherein each subsequent entry after the oldest entry is a sub-entry of the common database entry.
18. The method of claim 17, wherein the one or more keywords includes a noun.
19. The method of claim 18, wherein the keyword further identifies the relationship between a user and the one or more keywords.
20. The method of claim 17, wherein each database entry tracks a change in a physical object over time.
PCT/US2016/036895 2015-06-12 2016-06-10 A device and method for categorizing data WO2016201228A1 (en)

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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20110072395A1 (en) * 2004-12-03 2011-03-24 King Martin T Determining actions involving captured information and electronic content associated with rendered documents
US20120064917A1 (en) * 2007-12-12 2012-03-15 Andrew Jenkins System and method for generating a recommendation on a mobile device
US8719198B2 (en) * 2010-05-04 2014-05-06 Microsoft Corporation Collaborative location and activity recommendations

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20110072395A1 (en) * 2004-12-03 2011-03-24 King Martin T Determining actions involving captured information and electronic content associated with rendered documents
US20120064917A1 (en) * 2007-12-12 2012-03-15 Andrew Jenkins System and method for generating a recommendation on a mobile device
US8719198B2 (en) * 2010-05-04 2014-05-06 Microsoft Corporation Collaborative location and activity recommendations

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