IP Library › Granted Patent US 12,277,580
Granted Patent B2
US 12,277,580 · App. 16/907,586 · Granted Apr 15, 2025

Methods and systems for personalizing visitor experience, encouraging philanthropic activity and social networking

Inventors: Christine Soule (Woodinville, WA); Charles H. Cella (Pembroke, MA); Richard Spitz (Woodinville, WA)
Assignee: Olive Seed Industries, LLC
G06Q30/0279G01C21/206G06F3/013G06F3/0482G06F16/435G06F16/438G06F16/587G06F16/953G06F16/9535G06F16/954G06N20/00G06Q10/047G06Q20/20G06Q30/0201G06Q30/0203G06Q30/0207G06Q30/0214G06Q30/0217G06Q30/0224G06Q30/0236G06Q30/0261G06Q30/0267G06Q30/0271G06Q30/0281G06Q30/0282G06Q50/01G06T5/77G06T11/00G06T11/60G06V20/20G06V20/52G06V40/16G06V40/176H04L63/0861H04L67/12H04L67/535H04N7/15H04N21/2187H04W4/021H04W4/024H04W4/029H04W4/10H04W4/12H04W4/33H04W4/80H04W12/068H04W12/08H04W12/084G06K7/1417G06Q50/26G06V2201/10H04W12/64
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,277,580
App. No.
16/907,586
Granted
Apr 15, 2025
Kind
B2
Abstract

An information technology platform for personalizing an experience of a visitor at a non-profit venue comprising: a network; a server in communication with the network; a mobile computing device to be carried by the visitor, the mobile computing device in communication with the server via the network, wherein the information technology platform determines personalized information about the visitor; a recommendation engine associated with the server, wherein the recommendation engine is to receive the personalized information about the visitor and to output a suggestion for a personalized experience for the visitor, wherein the information technology platform conveys the suggestion for the personalized experience to the visitor, wherein the personalized experience is to encourage philanthropic activity; and a social networking system for digital communication between the visitor and other visitors, and for sharing information or media related to the non-profit venue or to a philanthropic campaign associated with the output suggestion.

Claims (24)

1. An information technology platform for personalizing an experience of a visitor at a non-profit venue, the platform comprising:

a mapping and tracking system for storing a personalized tracking history of a visitor, for generating a live, digital map of a non-profit venue and for mapping and tracking non-profit venue elements, non-profit venue personnel, and a set of visitors at the non-profit venue, wherein the mapping includes a heat map depicting areas of interest in the non-profit venue corresponding to exhibits related to an ongoing philanthropic campaign at which the visitor or set of visitors paused for a time period exceeding a threshold time duration, the heat map corresponding to the set of visitors configured to be segmented based on a plurality of generic visitor profiles, the plurality of generic visitor profiles corresponding to a plurality of selections or sequences of non-profit venue location recommendations generated by a machine learning system based on personal interest data for the set of visitors.

2. The information technology platform of claim 1 , wherein the digital map depicts location information selected from a group consisting of: exhibits; objects; meeting spots; popular photo and video locations; attractions; paths; the visitor; other visitors; visitors having a significance to the visitor including: friends, family, a tour group, a tour guide; a route associated with the visitor including: a recommended route, a pre-planned route, an actual route; entrances; exits; parking; a vehicle associated with the visitor; refreshments; dining; restrooms; retail shops; kiosks; security stations; information assistance stations; docent stations; employees of the non-profit venue and combinations thereof; and wherein the digital map conveys information regarding a topic selected from a group consisting of a philanthropic opportunity, a campaign and combinations thereof.

3. The information technology platform of claim 2 , wherein the digital map includes data selected from a group consisting of high-resolution imagery, high-resolution video, captioning, textual data, live video feed and combinations thereof.

4. The information technology platform of claim 3 , wherein supplemental media are provided by the information technology platform to the visitor based on the personalized tracking history; and wherein the supplemental media are provided by a software product running a program on the mobile computing device carried by the visitor, which, when executed, performs the steps of: tracking a specific path of the visitor through the non-profit venue; storing locations where the visitor stopped and waited; storing the specific path of the visitor on a remote server; providing the digital map to the visitor on the mobile computing device; and at a final end of a visit, assembling a multimedia presentation summarizing specific portions of the non-profit venue that the visitor visited and presenting the multimedia presentation to the visitor.

5. The information technology platform of claim 2 , wherein supplemental media are provided by the information technology platform to the visitor based on the personalized tracking history; and wherein the supplemental media are provided by a software product running a program on the mobile computing device carried by the visitor, which, when executed, performs the steps of: tracking a specific path of the visitor through the non-profit venue; storing locations where the visitor stopped and waited; storing the specific path of the visitor on a remote server; providing the digital map to the visitor on the mobile computing device; and at a final end of a visit, assembling a multimedia presentation summarizing specific portions of the non-profit venue that the visitor visited and presenting the multimedia presentation to the visitor.

6. The information technology platform of claim 1 , wherein the digital map includes data selected from a group consisting of high-resolution imagery, high-resolution video, captioning, textual data, live video feed and combinations thereof.

7. The information technology platform of claim 1 , wherein supplemental media are provided by the information technology platform to the visitor based on the personalized tracking history; and wherein the supplemental media are provided by a software product running a program on the mobile computing device carried by the visitor, which, when executed, performs the steps of: tracking a specific path of the visitor through the non-profit venue; storing locations where the visitor stopped and waited; storing the specific path of the visitor on a remote server; providing the digital map to the visitor on the mobile computing device; and at a final end of a visit, assembling a multimedia presentation summarizing specific portions of the non-profit venue that the visitor visited and presenting the multimedia presentation to the visitor.

8. The information technology platform of claim 1 , wherein the personal interest data for the set of visitors includes demographic information.

9. The information technology platform of claim 1 , wherein the personal interest data for the set of visitors is obtained from photographs taken by one or more visitors of the set of visitors.

10. The information technology platform of claim 9 , wherein the photographs are analyzed by the machine learning system to obtain the personal interest data for the set of visitors.

11. An information technology platform for personalizing an experience of a visitor at a non-profit venue, the platform comprising:

a mapping and tracking system for storing an aggregated tracking history of a set of visitors at a non-profit venue, wherein the system provides a mapping that includes a heat map depicting areas of interest in the non-profit venue corresponding to exhibits related to an ongoing philanthropic campaign at which the set of visitors paused for a time period exceeding a threshold time duration, the heat map configured to be segmented based on a plurality of generic visitor profiles, the plurality of generic visitor profiles corresponding to a plurality of selections or sequences of non-profit venue location recommendations generated by a machine learning system based on personal interest data for the set of visitors; and

a navigation system for providing a route and directions for a visitor to experience a non-profit venue, wherein the route and directions are selected based at least in part on the areas of interest.

12. The information technology platform of claim 11 , wherein the provided route is based on goodwill or profit factors.

13. The information technology platform of claim 12 , wherein the provided route is optimized to avoid lines or crowds.

14. The information technology platform of claim 12 , wherein the visitor contributes to pre-planning the route before the route is provided.

15. The information technology platform of claim 12 , wherein the provided route is conveyed via a mobile computing device to be carried by the visitor.

16. The information technology platform of claim 11 , wherein the provided route is optimized to avoid lines or crowds.

17. The information technology platform of claim 11 , wherein the visitor contributes to pre-planning the route before the route is provided.

18. The information technology platform of claim 11 , wherein the provided route is conveyed via a mobile computing device to be carried by the visitor.

19. The information technology platform of claim 11 , wherein the personal interest data for the set of visitors includes demographic information.

20. The information technology platform of claim 11 , wherein the personal interest data for the set of visitors is obtained from photographs taken by one or more visitors of the set of visitors.

21. The information technology platform of claim 20 , wherein the photographs are analyzed by the machine learning system to obtain the personal interest data for the set of visitors.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 22, 2020
From: SOULE, CHRISTINE; CELLA, CHARLES H.; SPITZ, RICHARD
To: OLIVE SEED INDUSTRIES, LLC
Reel/Frame 052999/0393 →
Continuity (4)
Continuation 16905222 · Jun 18, 2020
Continuation PCTUS2019045220 · Aug 6, 2019
Provisional Application 62715018 · Aug 6, 2018
Related Publication 20200320585A1 · Oct 8, 2020
References Cited (235)
US 6362900B1 · Squilla et al. · 2002 [cited by applicant]
US 7620636B2 · Fasciano · 2009 [cited by applicant]
US 7656312B2 · Fellenstein et al. · 2010 [cited by applicant]
US 7921036B1 · Sharma et al. · 2011 [cited by applicant]
US 8473421B2 · Scalisi · 2013 [cited by applicant]
US 8675016B2 · Vetterli et al. · 2014 [cited by applicant]
US 8965410B2 · Clark et al. · 2015 [cited by applicant]
US 9064282B1 · Carpenter et al. · 2015 [cited by applicant]
US 9131028B2 · Nguyen et al. · 2015 [cited by applicant]
US 9271133B2 · Rodriguez · 2016 [cited by applicant]
US 9418115B2 · Ganick et al. · 2016 [cited by applicant]
US 9702713B2 · Jung et al. · 2017 [cited by applicant]
US 9858538B1 · Johansson et al. · 2018 [cited by applicant]
US 9886845B2 · Rhoads et al. · 2018 [cited by applicant]
US 10009868B1 · Reyes et al. · 2018 [cited by applicant]
US 10026102B2 · Mihalik et al. · 2018 [cited by applicant]
US 10360566B2 · Brown et al. · 2019 [cited by applicant]
US 10382373B1 · Yang et al. · 2019 [cited by applicant]
US 10433106B2 · Sahadi · 2019 [cited by applicant]
US 10491979B1 · Stradley · 2019 [cited by applicant]
US 10502576B2 · Trigoni et al. · 2019 [cited by applicant]
US 10623366B1 · Liyanage et al. · 2020 [cited by applicant]
US 10636062B1 · Mossoba et al. · 2020 [cited by applicant]
US 10636066B2 · Proietti et al. · 2020 [cited by applicant]
US 10636207B1 · Swidersky et al. · 2020 [cited by applicant]
US 10685406B1 · Niderberg et al. · 2020 [cited by applicant]
US 10769542B1 · Dhalwani et al. · 2020 [cited by applicant]
US 10810595B2 · Gospodinov · 2020 [cited by applicant]
US 10859382B1 · Swidersky et al. · 2020 [cited by applicant]
US 10991015B2 · Soderstrom · 2021 [cited by applicant]
US 11022442B1 · Paskaris et al. · 2021 [cited by applicant]
US 11151481B1 · Sun et al. · 2021 [cited by applicant]
US 20020174003A1 · Redmann et al. · 2002 [cited by applicant]
US 20030154114A1 · Lucarelli · 2003 [cited by applicant]
US 20040097242A1 · Hull et al. · 2004 [cited by applicant]
US 20050065809A1 · Henze · 2005 [cited by applicant]
US 20050192025A1 · Kaplan · 2005 [cited by applicant]
US 20060129312A1 · Chou et al. · 2006 [cited by applicant]
US 20080249723A1 · McAllister et al. · 2008 [cited by applicant]
US 20090141048A1 · Fujimoto et al. · 2009 [cited by applicant]
US 20090319306A1 · Chanick · 2009 [cited by applicant]
US 20100023250A1 · Mays et al. · 2010 [cited by applicant]
US 20100164990A1 · Doorn · 2010 [cited by applicant]
US 20100198626A1 · Cho · 2010 [cited by examiner]
US 20100205176A1 · Ji et al. · 2010 [cited by applicant]
US 20100235245A1 · Grossman et al. · 2010 [cited by applicant]
US 20110105092A1 · Felt et al. · 2011 [cited by applicant]
US 20110133892A1 · Nohr · 2011 [cited by applicant]
US 20110295749A1 · Scalisi · 2011 [cited by applicant]
US 20110307478A1 · Pinckney et al. · 2011 [cited by applicant]
US 20120054302A1 · Priyadarshan et al. · 2012 [cited by applicant]
US 20120105644A1 · Purvis et al. · 2012 [cited by applicant]
US 20120109954A1 · White · 2012 [cited by applicant]
US 20120176477A1 · Givon · 2012 [cited by applicant]
US 20120185512A1 · McCully et al. · 2012 [cited by applicant]
US 20120192235A1 · Tapley et al. · 2012 [cited by applicant]
US 20120278721A1 · Beidel · 2012 [cited by applicant]
US 20130085832A1 · Witherspoon, Jr. et al. · 2013 [cited by applicant]
US 20130111574A1 · Celante et al. · 2013 [cited by applicant]
US 20130137464A1 · Kramer et al. · 2013 [cited by applicant]
US 20130183924A1 · Saigh et al. · 2013 [cited by applicant]
US 20130232030A1 · Gockeler et al. · 2013 [cited by applicant]
US 20130257906A1 · Tang et al. · 2013 [cited by applicant]
US 20130273968A1 · Rhoads et al. · 2013 [cited by applicant]
US 20130275886A1 · Haswell et al. · 2013 [cited by applicant]
US 20130282421A1 · Graff · 2013 [cited by examiner]
US 20130317944A1 · Huang et al. · 2013 [cited by applicant]
US 20130332509A1 · Schwartz et al. · 2013 [cited by applicant]
US 20140019867A1 · Lehtiniemi et al. · 2014 [cited by applicant]
US 20140052490A1 · Barr et al. · 2014 [cited by applicant]
US 20140129942A1 · Rathod · 2014 [cited by applicant]
US 20140152698A1 · Kim et al. · 2014 [cited by applicant]
US 20140162693A1 · Wachter et al. · 2014 [cited by applicant]
US 20140172476A1 · Goulart · 2014 [cited by examiner]
US 20140172553A1 · Goulart · 2014 [cited by examiner]
US 20140228055A1 · Karaoguz · 2014 [cited by applicant]
US 20140237076A1 · Goldman et al. · 2014 [cited by applicant]
US 20140247279A1 · Nicholas et al. · 2014 [cited by applicant]
US 20140278860A1 · Lee et al. · 2014 [cited by applicant]
US 20140278861A1 · Bush et al. · 2014 [cited by applicant]
US 20140279012A1 · Scofield et al. · 2014 [cited by applicant]
US 20140279034A1 · Samuel · 2014 [cited by applicant]
US 20140280316A1 · Ganick et al. · 2014 [cited by applicant]
US 20140358437A1 · Fletcher · 2014 [cited by examiner]
US 20140358632A1 · Graff et al. · 2014 [cited by applicant]
US 20140358664A1 · Wheeler · 2014 [cited by applicant]
US 20140365313A1 · Reese et al. · 2014 [cited by applicant]
US 20150006426A1 · Sobhani et al. · 2015 [cited by applicant]
US 20150018015A1 · Clark et al. · 2015 [cited by applicant]
US 20150036926A1 · Choi et al. · 2015 [cited by applicant]
US 20150040074A1 · Hofmann et al. · 2015 [cited by applicant]
US 20150085056A1 · Van Broeck · 2015 [cited by applicant]
US 20150134556A1 · Spinner et al. · 2015 [cited by applicant]
US 20150142688A1 · Jackson et al. · 2015 [cited by applicant]
US 20150154667A1 · Hicks et al. · 2015 [cited by applicant]
US 20150161684A1 · Raikula · 2015 [cited by applicant]
US 20150170042A1 · Perkowitz et al. · 2015 [cited by applicant]
US 20150174481A1 · Tobin · 2015 [cited by applicant]
US 20150177006A1 · Schulz · 2015 [cited by examiner]
US 20150241238A1 · Bass et al. · 2015 [cited by applicant]
US 20150242899A1 · Farhi · 2015 [cited by examiner]
US 20150254579A1 · Ford · 2015 [cited by applicant]
US 20150254903A1 · Sumner et al. · 2015 [cited by applicant]
US 20150262200A1 · Fredette · 2015 [cited by applicant]
US 20150286873A1 · Davis et al. · 2015 [cited by applicant]
US 20150310507A1 · Woodward · 2015 [cited by examiner]
US 20150317829A1 · Carter et al. · 2015 [cited by applicant]
US 20150341549A1 · Petrescu et al. · 2015 [cited by applicant]
US 20150358390A1 · Starr et al. · 2015 [cited by applicant]
US 20150365517A1 · Tam · 2015 [cited by applicant]
US 20160063488A1 · Gary et al. · 2016 [cited by applicant]
US 20160063993A1 · Dolan et al. · 2016 [cited by applicant]
US 20160080907A1 · Saleem · 2016 [cited by applicant]
US 20160117651A1 · Davis · 2016 [cited by applicant]
US 20160140227A1 · Lymberopoulos et al. · 2016 [cited by applicant]
US 20160148270A1 · Vigier et al. · 2016 [cited by applicant]
US 20160170998A1 · Frank et al. · 2016 [cited by applicant]
US 20160180402A1 · Sabah et al. · 2016 [cited by applicant]
US 20160205358A1 · Dickinson · 2016 [cited by applicant]
US 20160212591A1 · Kim et al. · 2016 [cited by applicant]
US 20160242010A1 · Parulski et al. · 2016 [cited by applicant]
US 20160335666A1 · Dodor et al. · 2016 [cited by applicant]
US 20160345163A1 · Monaghan et al. · 2016 [cited by applicant]
US 20160358459A1 · Singhar et al. · 2016 [cited by applicant]
US 20160364012A1 · Govezensky et al. · 2016 [cited by applicant]
US 20170068872A1 · Short et al. · 2017 [cited by applicant]
US 20170193124A1 · Wong · 2017 [cited by applicant]
US 20170193792A1 · Rodriguez et al. · 2017 [cited by applicant]
US 20170228804A1 · Soni et al. · 2017 [cited by applicant]
US 20170249651A1 · Pulitzer · 2017 [cited by applicant]
US 20170249712A1 · Branscomb et al. · 2017 [cited by applicant]
US 20170270560A1 · Duggal et al. · 2017 [cited by applicant]
US 20170270827A1 · Channabasappa et al. · 2017 [cited by applicant]
US 20170301001A1 · Wilkinson et al. · 2017 [cited by applicant]
US 20170307382A1 · Kim et al. · 2017 [cited by applicant]
US 20170315767A1 · Rao · 2017 [cited by applicant]
US 20170337494A1 · Deluca et al. · 2017 [cited by applicant]
US 20170364951A1 · Richardson · 2017 [cited by applicant]
US 20180014149A1 · Krzych et al. · 2018 [cited by applicant]
US 20180069817A1 · Constantinides · 2018 [cited by examiner]
US 20180073889A1 · Vigilante et al. · 2018 [cited by applicant]
US 20180075461A1 · Hirakawa · 2018 [cited by applicant]
US 20180126271A1 · Katzir · 2018 [cited by applicant]
US 20180145941A1 · Jeon et al. · 2018 [cited by applicant]
US 20180154962A1 · Ko et al. · 2018 [cited by applicant]
US 20180165371A1 · Tatro · 2018 [cited by applicant]
US 20180176441A1 · Burgess · 2018 [cited by applicant]
US 20180189714A1 · Azpitarte et al. · 2018 [cited by applicant]
US 20180240151A1 · D'Andrea et al. · 2018 [cited by applicant]
US 20180240176A1 · Cronin et al. · 2018 [cited by applicant]
US 20180253576A1 · Talbot · 2018 [cited by applicant]
US 20180288213A1 · Bjontegard · 2018 [cited by applicant]
US 20180322514A1 · Sargent et al. · 2018 [cited by applicant]
US 20180336575A1 · Hwang · 2018 [cited by examiner]
US 20180349413A1 · Shelby et al. · 2018 [cited by applicant]
US 20180349700A1 · Percuoco et al. · 2018 [cited by applicant]
US 20180350144A1 · Rathod · 2018 [cited by applicant]
US 20180352373A1 · Sahadi · 2018 [cited by applicant]
US 20180352378A1 · Sahadi · 2018 [cited by examiner]
US 20190043281A1 · Aman · 2019 [cited by applicant]
US 20190043493A1 · Mohajer et al. · 2019 [cited by applicant]
US 20190069147A1 · Charlton et al. · 2019 [cited by applicant]
US 20190095454A1 · Sahadi · 2019 [cited by examiner]
US 20190215660A1 · Slushtz et al. · 2019 [cited by applicant]
US 20190279096A1 · Nijs et al. · 2019 [cited by applicant]
US 20190301888A1 · Gürel et al. · 2019 [cited by applicant]
US 20190313020A1 · Snyder · 2019 [cited by applicant]
US 20190378176A1 · O'Brien · 2019 [cited by applicant]
US 20190394617A1 · Scully et al. · 2019 [cited by applicant]
US 20200033882A1 · Zysk, Jr. et al. · 2020 [cited by applicant]
US 20200111034A1 · Sahadi · 2020 [cited by applicant]
US 20200126125A1 · Sanjay et al. · 2020 [cited by applicant]
US 20200272676A1 · Priness et al. · 2020 [cited by applicant]
US 20200302510A1 · Chachek · 2020 [cited by examiner]
US 20200380267A1 · Lee · 2020 [cited by applicant]
US 20210134033A1 · Anttila et al. · 2021 [cited by applicant]
US 20230177259A1 · Rathus et al. · 2023 [cited by applicant]
CA 2887283A1 · 2014 [cited by applicant]
CA 3028646A1 · 2019 [cited by applicant]
CN 109313630A · 2019 [cited by applicant]
JP 2005031733A · 2005 [cited by applicant]
JP 2005275960A · 2005 [cited by applicant]
KR 2005019919A · 2005 [cited by applicant]
KR 20180057088A · 2018 [cited by applicant]
WO 0021009A1 · 2000 [cited by applicant]
WO 0042593A1 · 2000 [cited by applicant]
WO 2007081320A1 · 2007 [cited by applicant]
WO 2010102325A1 · 2010 [cited by applicant]
WO 2014117771A1 · 2014 [cited by applicant]
WO 2015148693A1 · 2015 [cited by applicant]
WO 2016043663A1 · 2016 [cited by applicant]
WO 2016081626A1 · 2016 [cited by applicant]
WO WO2016135536A1 · 2016 [cited by examiner]
WO 2016164607A1 · 2016 [cited by applicant]
WO 2017019650A1 · 2017 [cited by applicant]
WO 2017184646A1 · 2017 [cited by applicant]
WO 2019245578A1 · 2019 [cited by applicant]
Wirz et al., Inferring crowd conditions from pedestrians location traces for real-time crowd monitoring during city-scale mass gatherings, 2012, IEEE, pp. 367-372 (Year: 2012). [cited by examiner]
“7 Top Tech Ways to Measure Traffic at Trade Shows”, Jun. 13, 2017, Meetings.Skift.com (Year: 2017). [cited by examiner]
Wirz et al. publised article “Probing crowd density through smartphones in city-scale mass gatherings”, 2013, EPJ.org, https://epjdatascience.springeropen.com/counter/pdf/10.1140/epjds17.pdf (Year: 2013). [cited by examiner]
U.S. Appl. No. 16/905,222, filed Jun. 18, 2020, Soule. [cited by applicant]
U.S. Appl. No. 16/907,513, filed Jun. 22, 2020, Soule. [cited by applicant]
U.S. Appl. No. 16/907,710, filed Jun. 22, 2020, Soule. [cited by applicant]
U.S. Appl. No. 16/907,852, filed Jun. 22, 2020, Soule. [cited by applicant]
U.S. Appl. No. 16/907,904, filed Jun. 22, 2020, Soule. [cited by applicant]
U.S. Appl. No. 16/908,000, filed Jun. 22, 2020, Soule. [cited by applicant]
U.S. Appl. No. 16/908,033, filed Jun. 22, 2020, Soule. [cited by applicant]
U.S. Appl. No. 16/908,070, filed Jun. 22, 2020, Soule. [cited by applicant]
U.S. Appl. No. 19/908,106, filed Jun. 22, 2020, Soule. [cited by applicant]
PCT International Search Report and Written Opinion for International Application No. PCT/US2019/045220 dated Feb. 17, 2020, 25 pages. [cited by applicant]
Miajd, M. et al., “Impact of machine learning on improvement of user experience in museums,” 2017 Artificial Intelligence and Signal Processing (AISP), 2017, pp. 195-200. [cited by applicant]
Abstract from Yu, Z. et al., “Personalized Travel Package With Multi-Point-of-Interest Recommendation Based on Crowdsourced User Footprints (English),” IEEE Transactions on Human-Machine Systems, vol. 46, Issue 1, pp. 1… [cited by applicant]
Extended European Search Report dated Apr. 7, 2022 for European Patent Application No. 19846136.0, 5 pages. [cited by applicant]
Gil, A. et al., “Personalized multimedia touristic services for hybrid broadcast mobile receivers (English),” IEEE Transactions on Consumer Electronics, vol. 56, Issue 1, Apr. 16, 2010, 3 pages. [cited by applicant]
Lu, J. et al., “Location-based Intelligent Services of Scenic Areas,” IEEE, Apr. 2012, pp. 1882-1885. [cited by applicant]
Martin, J. et al., “SCALEX—A Personalized Multimedia Information System for Museums and Exhibitions,” Proceedings of the First International Conference on Automated Production of Cross Media Content for Multi-Channel Di… [cited by applicant]
Rubino, I. et al., “MusA: Using Indoor Positioning and Navigation to Enhance Cultural Experiences in a Museum,” Sensors, Dec. 2013, www.mdpi.com/journal/sensors, vol. 13, pp. 17445-17471. [cited by applicant]
Villarrubia, G. et al., “Hybrid Indoor Location System for Museum Tourist Routes in Augmented Reality,” IEEE, Jul. 2014, 8 pages. [cited by applicant]
Aliannejadi, M. et al., “Personalized Ranking for Context-Aware Venue Suggestion,” http://arXiv.org/licenses/nonexclusive-distrib/1.0/, May 20, 2017, 3 pages. [cited by applicant]
Celikten, E. et al., “Extracting Patterns of Urban Activity from Geotagged Social Data (Abstract),” ip.com, Apr. 15, 2016, 2 pages. [cited by applicant]
Balduini, M. et al., “Recommending Venues Using Continuous Predictive Social Media Analytics,” IEEE Internet Computing, vol. 18, Issue 5, Sep. 2014, pp. 28-35. [cited by applicant]
Chianese, A. et al., “SmARTweet: A Location-Based Smart Application for Exhibits and Museums,” 2013 International Conference on Signal-Image Technology & Internet-Based Systems, 2013 IEEE, pp. 408-415. [cited by applicant]
Yu, Z. et al., Personalized Travel Package With Multi-Point-of-Interest Reommendation Based on Crowdsourced User Footprints, IEEE Transactions on Human-Machine Systems, Feb. 2016, vol. 46, Issue 1, pp. 151-158. [cited by applicant]
U.S. Appl. No. 16/907,278, filed Jun. 21, 2020, Soule. [cited by applicant]
U.S. Appl. No. 16/907,540, filed Jun. 22, 2020, Soule. [cited by applicant]
U.S. Appl. No. 16/907,662, filed Jun. 22, 2020, Soule. [cited by applicant]
U.S. Appl. No. 16/907,803, filed Jun. 22, 2020, Soule. [cited by applicant]
U.S. Appl. No. 16/907,977, filed Jun. 22, 2020, Soule. [cited by applicant]
U.S. Appl. No. 16/907,946, filed Jun. 22, 2020, Soule. [cited by applicant]
U.S. Appl. No. 16/907,033, filed Jun. 22, 2020, Soule. [cited by applicant]
U.S. Appl. No. 16/907,106, filed Jun. 22, 2020, Soule. [cited by applicant]
Ayala, I. et al., “iMuseumA: An Agent-Based Context-Aware Intelligent Museum System,” Sensors, Nov. 2014, vol. 14, pp. 21213-21246, www.mdpi.com/journal/sensors. [cited by applicant]
Buvaneswari, N. et al., “Comprehensive Personalized Recommendation Technologies,” 2016 Fifth International Conference On Recent Trends in Information Technology, IEEE, Apr. 2016, 5 pages. [cited by applicant]
Ng, K.H. et al., “Treasure codes: augmenting learning from physical museum exhibits through treasure hunting,” Personal and Ubiquitous Computing, Mar. 2018, vol. 22, pp. 739-750. [cited by applicant]
Osche, P. et al., “Walk the line: Toward an efficient user model for recommendations in museums,” 11th International Workshop on Semantic and Social Media Adaptation and Personalizaiton (SMAP 2016), Oct. 2016, pp. 38-88. [cited by applicant]