United States Patent
`US 10,380,636 B2
`10) Patent No.:
`(12)
`Polachi
`(45) Date of Patent:
`Aug. 13, 2019
`
`
`US010380636B2
`
`(54) SYSTEMS AND METHODS FOR
`STATISTICAL DYNAMIC GEOFENCING
`(71) Applicant: eBay Inc., San Jose, CA (US)
`(72)
`Inventor: Neala F. Polachi, Boston, MA (US)
`(73) Assignee: eBay Inc., San Jose, CA (US)
`
`(*) Notice:
`
`Subject to any disclaimer, the term ofthis
`patent is extended or adjusted under 35
`U.S.C. 154(b) by 82 days.
`
`(21) Appl. No.: 13/707,316
`
`(22)
`
`Filed:
`
`Dec. 6, 2012
`
`(65)
`
`Prior Publication Data
`US 2014/0164118 Al
`Jun. 12. 2014
`;
`
`(51)
`
`Int. Cl.
`G06Q 30/02
`G06 30/00
`(52) U.S. Cl.
`CPC..... G06Q 30/0259 (2013.01); G06 30/0261
`(2013.01)
`
`(2012.01)
`(2012.01)
`
`(58) Field of Classification Search
`CPC ween G06Q 30/02; G06Q 30/0259; GO6Q
`30/0246; G06Q 30/0261; G06Q
`30/0207-30/0277
`USPC..... 705/14.57, 14.45, 14.58, 14.64, 14, 319;
`455/456.3
`See application file for complete search history.
`
`(56)
`
`References Cited
`U.S. PATENT DOCUMENTS
`
`11/2003 Owensby
`6,647,257 B2
`9/2011 Sheha
`8,019,532 B2
`8,335,524 B2* 12/2012 Shutter oe. 455/456.3
`2006/0200305 Al*
`9/2006 Shehaet al. 0... 701/200
`
`2006/0253481 AL*
`11/2006 Guido et al. vce 707/100
`2006/0270421 Al* 11/2006 Phillips... G08B teeasy
`455
`x
`.
`200910197582 ALS
`812009 Lewis rm MeNaLto
`(Continued)
`FOREIGN PATENT DOCUMENTS
`1020120054671 A
`$/2012
`WO-2014089462 A2
`6/2014
`WO-2014089462 A3
`6/2014
`
`KR
`Wo
`WO
`
`OTHER PUBLICATIONS
`
`“Australian Application Serial No. 2013355021, First Examiner
`Report dated Feb. 29, 2016”, 3 pgs.
`(Continued)
`
`Primary Examiner — Matthew T Sittner
`Assistant Examiner — Richard G Reinhardt
`(74) Attorney, Agent, or Firm —SBMC
`
`ABSTRACT
`(57)
`Systems and methodsfor statistical dynamic geofencing are
`discussed. For example, a method for statistical dynamic
`geofencing can include operations such as receiving a loca-
`tion-based campaign request, analyzing demographic data,
`determining a geofence parameter, generating a geofence,
`and distributing location-aware advertisements. The loca-
`tion-based campaign request can includea list of points of
`interest (POIs) and a target demographic parameter. The
`demographic data can include data from geographic areas
`surrounding at least a portion of the POIs as well as data
`related to the target demographic parameter. The geofence
`can be generated based at least in part on the geofence
`parameter, where the geofence parameter directly affects
`either the size or shape of the geofence. The location-aware
`advertisements are distributed to a plurality of mobile
`devices determined to be within the geofence.
`
`20 Claims, 9 Drawing Sheets
`
`72k
`
`730,
`
`7009
`
`Exhibit 1033
`
`Page 01 of 21
`
`740» RECEIVE A LOCATION
` GENERATE A GEOFENCE AROL!
`Exhibit 1033
`
`
`REQUEST
`
` ED CAMPAIGN |ED
`
`ANALYZE DEMOGRAPHIC DATA,
`
`POINT OF INTE!
`
`Samsung etal. v. Hardin etal.
`IPR2022-01328
`
`Exhibit 1033
`Page 01 of 21
`
`

`

`US 10,380,636 B2
`Page 2
`
`“Australian Application Serial No. 2013355021, Subsequent Exam-
`iners Report dated Jun. 6, 2016”, 3 pgs.
`“Canadian Application Serial No. 2,894,142, Office Action dated.
`Jun. 14, 2016”, 3 pgs.
`“Canadian Application Serial No. 2,894,142, Response filed Dec. 8,
`2016 to Office Action dated Jun. 14, 2016”, 25 pgs.
`Office Action received for Canadian Patent Application No. 2,894,142,
`dated Jun. 13, 2018, 6 pages.
`Response to Office Action filed on Oct. 17, 2017, for Canadian
`Patent Application No. 2,894,142, dated May 10, 2017, 3 pages.
`Response to Office Action filed on Jul. 19, 2018, for Canadian
`Patent Application No. 2,894,142, dated Jun. 13, 2018, 4 pages.
`International Preliminary Report on Patentability and Written Opin-
`ion received for PCT Application No. PCT/US2013/073627, dated.
`Jun. 18, 2015, 8 pages.
`“International Application Serial No. PCT/US2013/073627, Inter-
`national Search Report dated Jul. 18, 2014”, 3 pgs.
`“International Application Serial No. PCT/US2013/073627, Written
`Opinion dated Jul. 18, 2014”, 6 pgs.
`“Canadian Application Serial No. 2,894,142, Office Action dated.
`May 10, 2017”, 4 pgs.
`Office Action received for Canada Patent Application No. 2,894,142,
`dated Apr. 25, 2019, 7 pages.
`
`* cited by examiner
`
`(56)
`
`References Cited
`U.S. PATENT DOCUMENTS
`
`3/2012 Tengler et al.
`2012/0054028 Al*
`........ 705/14.49
`
`5/2012 Phillips et al.
`2012/0129553 Al*
`wes 455/456.3
`.
`2012/0265841 Al* 10/2012 Ross wees HO4W 4/029
`709/217
`2012/0276928 Al* 11/2012 Shutter 0.00... G06Q 30/02
`455/456.3
`vs 705/14.45
`
`........... 705/14.58
`
`...
`4/2014 Angell et al.
`6/2014 Wuersch et al.
`
`2014/0095296 Al*
`2014/0156410 Al*
`
`OTHER PUBLICATIONS
`
`“Australian Application Serial No. 2013355021, Office Action dated
`Sep. 15, 2016”, 3 pgs.
`“Australian Application Serial No. 2013355021, Response filed
`May 30, 2016 to First Examiner Report dated Feb. 29, 2016”, 22
`pgs.
`“Australian Application Serial No. 2013355021, Response filed
`Sep. 13, 2016 to Subsequent Examiners Report dated Jun. 6, 2016”,
`11 pgs.
`“Australian Application Serial No. 2013355021, Response filed
`Sep. 20, 2016 to Office Action dated Sep. 15, 2016”, 4 pgs.
`
`Exhibit 1033
`
`Page 02 of 21
`
`Exhibit 1033
`Page 02 of 21
`
`

`

`U.S. Patent
`
`Aug. 13, 2019
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`Sheet 1 of 9
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`Page 04 of 21
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`

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`U.S. Patent
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`Aug.13, 2019
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`Sheet 3 of 9
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`U.S. Patent
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`Aug. 13, 2019
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`U.S. Patent
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`Aug.13, 2019
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`Sheet 5 of 9
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`

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`U.S. Patent
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`Aug.13, 2019
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`Sheet 6 of 9
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`Exhibit 1033
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`Page 08 of 21
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`

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`U.S. Patent
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`Aug.13, 2019
`
`Sheet 7 of 9
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`Exhibit 1033
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`Exhibit 1033
`Page 09 of 21
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`

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`Exhibit 1033
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`Page 10 of 21
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`Exhibit 1033
`Page 10 of 21
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`

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`Aug. 13, 2019
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`

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`US 10,380,636 B2
`
`1
`SYSTEMS AND METHODS FOR
`STATISTICAL DYNAMIC GEOFENCING
`
`TECHNICAL FIELD
`
`This application relates generally to data processing
`within a network-based system operating over a distributed
`network or data processing on a mobile device, and more
`specifically to systems and methods for implementing sta-
`tistical dynamic geofencing.
`
`BACKGROUND
`
`The ever increasing use of smart phones, such as the
`iPhone® (from Apple, Inc. of Cupertino, Calif.), with data
`connections and location determination capabilities
`is
`slowly changing the way people interact, shop for products
`and services, and even manage accounts. Smart phones can
`provide users with nearly instant information regarding a
`wide range of information, such as product availability,
`friend locations, or pricing. For example, applications such
`as RedLaser™ (from eBay, Inc. of San Jose, Calif.) allow a
`smart phone user to scan a bar code and instantly check
`prices across online and local retail outlets. Smart phones
`also commonly include mechanisms, such as global posi-
`tioning system (GPS) receivers, that allow the devices to
`constantly update location information. These technology
`changes are also driving changes in the way merchants and
`brand advertisers target and deliver advertising, particularly
`mobile advertising.
`
`BRIEF DESCRIPTION OF THE DRAWINGS
`
`Some embodimentsare illustrated by way of example and
`not limitation in the figures of the accompanying drawings
`in which:
`FIG. 1 is a block diagram depicting a system for using
`statistical dynamic geofences to assist in targeted publica-
`tion distribution, according to an example embodiment.
`FIG.2 is a block diagram illustrating an environment for
`operating a mobile device, according to an example embodi-
`ment.
`
`FIG. 3 is a block diagram illustrating a mobile device,
`according to an example embodiment.
`FIG. 4 is a block diagram illustrating a network-based
`system for using statistical dynamic geofences to assist in
`targeted publication distribution, according to an example
`embodiment.
`FIG.5 is a block diagram illustrating geofencing modules,
`according to an example embodiment.
`FIG. 6 is a diagram illustrating geofence updating via
`statistical analysis, according to an example embodiment.
`FIG.7 is a flowchart illustrating a method of generating
`and using statistical dynamic geofences to assist in targeted
`publication distribution, according to an example embodi-
`ment.
`
`FIG. 8 is a flowchart illustrating a method of updating
`statistical dynamic geofences to refine targeted publication
`distribution, according to an example embodiment.
`FIG. 9 is a diagrammatic representation of a machine in
`the example form of a computer system within which a set
`of instructions for causing the machine to perform any one
`or more of the methodologies discussed herein may be
`executed.
`
`DEFINITIONS
`
`Location—For the purposesof this specification and the
`associated claims, the term “location” is used to refer to a
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`geographic location, such as a longitude/latitude combina-
`tion or a street address. The term locationis also used within
`
`this specification in reference to a physical location associ-
`ated with a merchant, an event, or other similar physical
`destination.
`
`Point of Interest (POI)—Forthe purposes of this speci-
`fication and the associated claims, the term is used in a
`manner similar to location, and refers to or identifies a
`geographic (physical) location. For example, a POI may be
`a retail store, such as Starbucks, and may identify that retail
`store by name, address, GPS coordinates, or any other
`known method of identifying a unique physical location.
`Real-time—Forthe purposesofthis specification and the
`associated claims, the term “real-time” is used to refer to
`calculations or operations performed on the fly as events
`occuror input is received by the operable system. However,
`the use of the term “real-time” is not intended to preclude
`operations that cause some latency between input and
`response, so long as the latency is an unintended conse-
`quence induced by the performance characteristics of the
`machine.
`
`Context—For the purposes of this specification and the
`associated claims, the term “context” is used to refer to
`environmental inputs, such as location, time, and weather
`conditions, among others. The context generally refers to
`conditions describing an individual’s (e.g., user’s) environ-
`ment and/or activities. For example, context information can
`include a user’s location, direction of movement, current
`activity (e.g., working, driving, playing golf, shopping,etc.),
`current weather conditions, time of day, and time of year
`(e.g., season), among other things. In certain examples,
`context
`information about a user can also include past
`events, purchase history, or other historical data about the
`user.
`
`Geofence—Forthe purposesof this specification and the
`associated claims, the term “geofence” is used to refer to
`various regions or boundaries of interest that
`include a
`geographic area within a distanceortravel time to a point of
`interest. However, a geofence need not be limited to any
`geometric shape or an arbitrary boundary drawn on a map.
`A geofence can be used to determine a geographical area of
`interest for calculation of demographics, advertising, or
`similar purposes. Geofences can be used in conjunction with
`the advertisement generation and delivery concepts dis-
`cussed herein. For example, a geofence can be usedto assist
`in determining whether a user (or mobile device associated
`with the user) is within a geographic area of interest to a
`particular advertiser (e.g., a local merchant) or capable of
`traveling to the particular advertiser in a specified period of
`time. If the user is within a geofence established by the
`merchant, the systems discussed herein can use that infor-
`mation to generate a dynamic advertisement from the adver-
`tiser and deliver the offer to the user (e.g., via a mobile
`device associated with the user).
`Additional detail regarding providing and receiving loca-
`tion-based services,
`including geo-location and geofence
`concepts, can be found in U.S. Pat. No. 7,848,765, titled
`“Location-Based Services,” granted to Phillips et al., which
`is hereby incorporated by reference.
`
`DETAILED DESCRIPTION
`
`Example systems and methods are described for using
`statistical dynamic geofencing for targeting publication
`delivery to mobile devices, among other things. Also
`described are systems and methods for generating, updating,
`and utilizing statistical dynamic geofences. In the following
`
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`US 10,380,636 B2
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`3
`description, for purposes of explanation, numerousspecific
`details are set forth in order to provide a thorough under-
`standing of example embodiments. It will be evident, how-
`ever, to one skilled in the art, that the present invention may
`be practiced without these specific details. It will also be
`evidentthat statistical dynamic geofencing is not limited to
`the examples provided and may include other scenarios not
`specifically discussed.
`Geofences can be used within a location-aware publica-
`tion system to target publications for distribution within
`limited geographical areas. Geofences can be defined in
`terms of GPS coordinates (e.g.,
`latitude and longitude)
`combined with a radius measured in meters or feet, for
`example. Alternatively, geofences can also be defined
`according to a series of GPS coordinates defining a bound-
`ing box. In yet other examples, a geofence can be any
`geometric shape defined by a mathematical formula and
`anchored by a GPS coordinate. Other methods of defining,
`maintaining, and using geofences can be used without
`limitation with the systems and methods discussed herein.
`One challenge identified by the inventors in effective use
`of geofences for targeting publication distribution can
`include accurately predicting whether the geofence is likely
`to include target consumers whoare likely to respond to the
`publication. A solution to this challenge can include the use
`of statistical analysis of demographic data, such as census
`data, in geographic areas of interest to determine optimal
`geofence size, shape, and even placement. Targeting publi-
`cations, such as advertisements, for distribution within lim-
`ited geographical areas can allow merchants and other
`advertisers to selectively target publications based on sta-
`tistical analysis of data, such as demographic data.
`With the increased popularity of mobile devices, such as
`the iPhone®, with location-aware capabilities, the useful-
`ness of location-aware publication systems has increased.
`Location-aware publication systems can receive location
`data on mobile devices directly from individual mobile
`devices or from a carrier, such as AT&T or Verizon. In some
`examples, the location data may also include, or be able to
`be correlated with, demographic data associated with the
`users of the mobile devices. In such examples, a location-
`aware publication system can analyze historical trends in
`location and demographic data to generate geofences to
`target locations around POIs.
`In an example, a coffee franchise may want to target
`certain demographic characteristics (target demographic
`parameters) of potential customers around each franchise
`location. A location-aware publication system can utilize
`general census-type demographic datato initially generate a
`set of geofences around (or associated with) each of the
`target POIs. In an example, the demographic characteristic
`might be average income, and the publication system can
`analyze demographic data in geographic areas surrounding
`a POI to determine the size and/or shape required for a
`geofence to encompass a certain predicted number or den-
`sity of individuals with the target demographic (e.g., average
`income over $80,000/year).
`In certain examples,
`the
`geofence maynotbe centered on a particular POI, but rather
`allowedto float within a defined geographic area in order to
`best capture the target demographic. In these examples, the
`defined float geography can be centered or otherwise tied to
`one or more POIs,
`in order to ensure that the targeted
`audience is within a certain distance of an advertiser’s
`
`physical locations.
`In these examples, the target demographics can include
`population density, average income, age ranges, percentage
`of male or females, average education level, active mobile
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`device usage, or any other similar demographic character-
`istic. Geofences can also be generated based on other data
`susceptible to statistical analysis, such as competitors (loca-
`tionsor density) or WiFi hotspots, among other things. Some
`additional example target demographics can include: house-
`hold income, marital status, sex, age, ethnicity, race, pro-
`fession, average number of children, no children, median
`age, and male/female median age, among other things. Data
`sources for demographic data can include United States
`government collected census data, such as is available
`within a ZIP code database (from ZIP-CODES.COM, www.
`zip-codes.com/zip-code-database.asp (last visited Dec. 5,
`2012)).
`In certain examples, statistical dynamic geofences can be
`generated and subsequently updated based on one or more
`target parameters. Referring back to the coffee franchise
`example, once an initial geofence has been generated and
`used to target distribution of a mobile advertisement,
`response results to the advertisement can be monitored and
`analyzed to update subsequent geofencesfor targeting future
`advertisement distribution. For example,
`the publication
`system can monitor click-throughs(or similar indications of
`interest in the distributed advertisement) and correlate the
`click-throughs with demographic data to determine whether
`the advertisement is reaching the target audience. Based on
`analysis of the click-through-related demographic data, the
`size or shape of the geofence can be updated in an attempt
`to increase the predicted numberoftarget recipients match-
`ing a certain characteristic.
`In other examples, demographic data analysis may deter-
`mine that the size or shape of a geofence should shift over
`the course of a day. For example, between the hours of 7:00
`AM and 9:00 AM,the demographic data may indicate that
`target population density is high, allowing for a small radius
`geofence to be used in delivering targeted publications(e.g.,
`advertisements or coupon offers). However, between 9:01
`AM and 3:00 PM, the demographic data may indicate that
`a muchlarger radius needs to be considered to capture a
`similar potential audience. In this example,
`the dynamic
`geofence may changein size depending upon time of day of
`distribution by the publication system.
`Example System
`FIG. 1 is a block diagram depicting a system 100 for using
`statistical dynamic geofences to assist in targeted publica-
`tion distribution, according to an example embodiment. In
`an example, system 100 can include users 110A-110N
`(collectively referred to as either user 110 or users 110
`depending upon context) and a network-based publication
`system 120.
`In an example,
`the users 110A-110N can
`connect to the network-based publication system 120 via
`mobile devices 115A-115N (collectively referred to as
`mobile device 115). Users 110A-110N can also connect to
`the network-based publication system 120 via clients 140A-
`140N (collectively referred to as client 140 or clients 140).
`In certain examples, users 110 can receive publications, on
`mobile devices 115 or clients 140, from the network-based
`publication system 120 transmitted over network 105, but
`the users 110 may not otherwise make any sort of direct
`connection with the network-based publication system 120.
`In an example, the users 110 can configure an account on
`the network-based publication system 120. The account can
`be accessed by a user, such as user 110A, using mobile
`device 115A or client 140A,if user 110A meets the specified
`access criteria or rules. In an example, the access rules can
`include user identification and/or mobile device identifica-
`tion. A user account on the network-based publication sys-
`tem 120 can allow the userto define specific POIs of interest
`
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`US 10,380,636 B2
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`5
`or provide other user data that can be used by the network-
`based publication system 120 for targeting publications. In
`some examples, the network-based publication system 120
`can monitor user behavior and create geofences based on
`past and predicted user behaviors. In certain examples, the
`network-based publication system 120 can be used by
`merchants as a location-based advertising platform, where
`users, such as users 110, opt-in to location-based advertise-
`ments. For example, Best Buy (of Minneapolis, Minn.) may
`use the network-based publication system 120 to provide
`location-based advertising to users 110 via mobile devices
`115. In this example, the network-based publication system
`120 can use statistical dynamic geofences, as discussed
`herein, to target a geographic area that is likely to include a
`segment of users 110 that meet a target demographic param-
`eter. In this example, Best Buy would define an advertising
`campaign that includes a target demographic and a list of
`POIs relevant to the campaign.
`Example Operating Environment
`FIG.2 is a block diagram illustrating an environment 200
`for operating a mobile device 115, according to an example
`embodiment. The environment 200 is an example environ-
`ment within which methods for using statistical dynamic
`geofences can be implemented. The environment 200 can
`include a mobile device 115, a communication connection
`210, a network 220, servers 230, a communication satellite
`270, a merchant server 280, and a database 290. The servers
`230 can optionally include location based service applica-
`tion (LBS) 240,
`location determination application 250,
`publication application 260, and geofence application 265.
`The database 290 can optionally include demographic data
`292, user profiles 294, and/or location history 296. The
`mobile device 115 represents one example device that can be
`utilized by a user to receive publications. The mobile device
`115 maybe any of a variety of types of devices (for example,
`a cellular telephone, a personal digital assistant (PDA), a
`Personal Navigation Device (PND), a handheld computer, a
`tablet computer, a notebook computer, or other type of
`movable device). The mobile device 115 may interface via
`a connection 210 with a communication network 220.
`
`Depending on the form of the mobile device 115, any of a
`variety of types of connections 210 and communication
`networks 220 may be used.
`For example, the connection 210 may be Code Division
`Multiple Access (CDMA) connection, a Global System for
`Mobile communications (GSM) connection, or other type of
`cellular connection. Such connection 210 may implement
`any of a variety of types of data transfer technology, such as
`Single Carrier Radio Transmission Technology (1xRTT),
`Evolution-Data Optimized (EVDO) technology, General
`Packet Radio Service (GPRS) technology, Enhanced Data
`rates for GSM Evolution (EDGE) technology, or other data
`transfer technology (e.g., fourth generation wireless, 4G
`networks). When such technology is employed, the com-
`munication network 220 may include a cellular network that
`has a plurality of cell sites of overlapping geographic
`coverage, interconnected by cellular telephone exchanges.
`These cellular telephone exchanges may be coupled to a
`network backbone (for example, the public switched tele-
`phone network (PSTN), a packet-switched data network, or
`other types of networks).
`In another example, the connection 210 may be a Wi-Fi
`or IEEE 802.11x type connection, a Worldwide Interoper-
`ability for Microwave Access (WiMAX) connection, or
`another type of wireless data connection. In such an embodi-
`ment, the communication network 220 may include one or
`more wireless access points coupled to a local area network
`
`20
`
`25
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`30
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`40
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`45
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`6
`(LAN), a wide area network (WAN), the Internet, or other
`packet-switched data network.
`In yet another example, the connection 210 may be a
`wired connection, for example an Ethernet link, and the
`communication network may be a LAN, a WAN,the Inter-
`net, or other packet-switched data network. Accordingly, a
`variety of different configurations are expressly contem-
`plated.
`A plurality of servers 230 may be coupled via interfaces
`to the communication network 220, for example, via wired
`or wireless interfaces. These servers 230 may be configured
`to provide various types of services to the mobile device
`115. For example, one or more servers 230 may execute LBS
`applications 240, which intemperate with software execut-
`ing on the mobile device 115, to provide LBSs to a user.
`LBSs can use knowledgeof the device’s location, and/or the
`location of other devices, to provide location-specific infor-
`mation, recommendations, notifications,
`interactive capa-
`bilities, and/or other functionality to a user. For example, an
`LBS application 240 can provide location data to a network-
`based publication system 120, which can then be used to
`provide location-aware publications from the network-based
`publication system 120, where servers 230 can be operating
`with the network-based publication system 120. Knowledge
`of the device’s location, and/or the location of other devices,
`maybe obtained through interoperation of the mobile device
`115 with a location determination application 250 executing
`on one or moreofthe servers 230. Location information may
`also be provided by the mobile device 115, without use of a
`location determination application, such as application 250.
`In certain examples, the mobile device 115 may have some
`limited location determination capabilities that are aug-
`mented by the location determination application 250. In
`some examples, the servers 230 can also include publication
`application 260 for providing location-aware publication of
`data such as advertisements or offers. In certain examples,
`location data can be provided to the publication application
`260 by the location determination application 250. In some
`examples, the location data provided by the location deter-
`mination application 250 can include merchant information
`(e.g., identification of a retail location). In certain examples,
`the location determination application 250 can receive sig-
`nals via the network 220 to further identify a location. For
`example, a merchant may broadcast a specific JEEE 802.11
`service set identifier (SSID) that can be interpreted by the
`location determination application 250 to identify a particu-
`lar retail location. In another example, the merchant may
`broadcast an identification signal via radio-frequency iden-
`tification (RFID), near-field communication (NFC), or a
`similar protocol that can be used by the location determi-
`nation application 250. In addition to examples using these
`various mechanisms to identify a particular location, these
`mechanisms(e.g., SSIDs, RFIDs NFC, and on forth) can be
`used as secondary authentication factors, which are dis-
`cussed in more detail below.
`In certain examples, the geofence application 265 can
`leverage the LBS application 240 or the location determi-
`nation application 250 to assist in generating and/or updat-
`ing geofences based on current or historical statistics.
`Example Mobile Device
`FIG. 3 is a block diagram illustrating the mobile device
`115, according to an example embodiment. The mobile
`device 115 mayinclude a processor 310. The processor 310
`maybe any ofa variety of different types of commercially
`available processors
`suitable for mobile devices
`(for
`example, an XScale architecture microprocessor, a Micro-
`processor without Interlocked Pipeline Stages (MIPS)archi-
`
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`US 10,380,636 B2
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`7
`tecture processor, or another type of processor). A memory
`320, such as a Random Access Memory (RAM), a Flash
`memory, or other type of memory, is typically accessible to
`the processor. The memory 320 maybeadaptedto store an
`operating system (OS) 330, as well as application programs
`340, such as a mobile location enabled application that may
`provide LBSs to a user. The processor 310 may be coupled,
`either directly or via appropriate intermediary hardware, to
`a display 350 and to one or more input/output (1/O) devices
`360, such as a keypad, a touch panel sensor, a microphone,
`and the like. Similarly, in some embodiments, the processor
`310 may be coupled to a transceiver 370 that interfaces with
`an antenna 390. The transceiver 370 may be configured to
`both transmit and receive cellular network signals, wireless
`data signals, or other types of signals via the antenna 390,
`depending on the nature of the mobile device 115. In this
`manner, the connection 210 with the communication net-
`work 220 may be established. Further, in some configura-
`tions, a GPSreceiver 380 may also make use of the antenna
`390 to receive GPS signals.
`Example Platform Architecture
`FIG. 4 is a block diagram illustrating a network-based
`system 400 for using statistical dynamic geofences to assist
`in targeted publication distribution, according to an example
`embodiment. The block diagram depicts a network-based
`system 400 (in the exemplary form of a client-server sys-
`tem), within which an example embodiment can be
`deployed. A networked system 402 is shown,in the example
`form of a network-based location-aware publication or pay-
`ment system, that provides server-side functionality, via a
`network 404 (e.g., the Internet or WAN) to one or more
`client machines 410, 412. FIG.4 illustrates, for example, a
`webclient 406 (e.g., a browser, such as the Internet Explorer
`browser developed by Microsoft Corporation of Redmond,
`Wash. State) and a programmatic client 408 (e.g., PAYPAL
`payments smart phoneapplication from PayPal, Inc. of San
`Jose, Calif.) executing on respective client machines 410
`and 412. In an example, the client machines 410 and 412 can
`be in the form of a mobile device, such as mobile device 115.
`In yet another example, the programmatic client 408 can be
`the RedLaser mobile shopping application from eBay, Inc.
`of San Jose, Calif.
`An Application Programming Interface (API) server 414
`and a web server 416 are coupled to, and provide program-
`matic and web interfaces respectively to, one or more
`application servers 418. The application servers 418 host
`one or more publication modu