WO2013184383A3 - App recommendation using crowd-sourced localized app usage data - Google Patents
App recommendation using crowd-sourced localized app usage data Download PDFInfo
- Publication number
- WO2013184383A3 WO2013184383A3 PCT/US2013/042483 US2013042483W WO2013184383A3 WO 2013184383 A3 WO2013184383 A3 WO 2013184383A3 US 2013042483 W US2013042483 W US 2013042483W WO 2013184383 A3 WO2013184383 A3 WO 2013184383A3
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- app
- usage data
- apps
- crowd
- recommendation
- Prior art date
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/29—Geographical information databases
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/958—Organisation or management of web site content, e.g. publishing, maintaining pages or automatic linking
Abstract
Apps may be tagged with location data when they are used. Mobile device may anonymously submit app usage data. Aggregated app usage data from many mobile devices may be analyzed to determine apps that are particularly relevant to a given location (i.e., exhibiting a high degree of localization). Analysis may include determining the app usage intensity, whether hotspots exist or not at a given location, the spatial entropy of a particular app, the device populations in a particular area, etc. Based on the localized app analysis, apps may be ranked according to local relevance, and, based on this ranking, app recommendations may be provided to a user.
Applications Claiming Priority (10)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US201261655427P | 2012-06-04 | 2012-06-04 | |
US61/655,427 | 2012-06-04 | ||
US201261657403P | 2012-06-08 | 2012-06-08 | |
US61/657,403 | 2012-06-08 | ||
US201261699705P | 2012-09-11 | 2012-09-11 | |
US61/699,705 | 2012-09-11 | ||
US13/842,724 US9510141B2 (en) | 2012-06-04 | 2013-03-15 | App recommendation using crowd-sourced localized app usage data |
US13/843,291 US9195721B2 (en) | 2012-06-04 | 2013-03-15 | Mobile device with localized app recommendations |
US13/843,291 | 2013-03-15 | ||
US13/842,724 | 2013-03-15 |
Publications (2)
Publication Number | Publication Date |
---|---|
WO2013184383A2 WO2013184383A2 (en) | 2013-12-12 |
WO2013184383A3 true WO2013184383A3 (en) | 2014-05-15 |
Family
ID=49712802
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/US2013/042483 WO2013184383A2 (en) | 2012-06-04 | 2013-05-23 | App recommendation using crowd-sourced localized app usage data |
Country Status (1)
Country | Link |
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WO (1) | WO2013184383A2 (en) |
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US9390378B2 (en) | 2013-03-28 | 2016-07-12 | Wal-Mart Stores, Inc. | System and method for high accuracy product classification with limited supervision |
US9436919B2 (en) | 2013-03-28 | 2016-09-06 | Wal-Mart Stores, Inc. | System and method of tuning item classification |
US9483741B2 (en) | 2013-03-28 | 2016-11-01 | Wal-Mart Stores, Inc. | Rule-based item classification |
US9913100B2 (en) | 2014-05-30 | 2018-03-06 | Apple Inc. | Techniques for generating maps of venues including buildings and floors |
US10108748B2 (en) | 2014-05-30 | 2018-10-23 | Apple Inc. | Most relevant application recommendation based on crowd-sourced application usage data |
US9402161B2 (en) | 2014-07-23 | 2016-07-26 | Apple Inc. | Providing personalized content based on historical interaction with a mobile device |
WO2016039676A1 (en) * | 2014-09-11 | 2016-03-17 | Telefonaktiebolaget L M Ericsson (Publ) | Pre-processing of user data |
US9971972B2 (en) | 2014-12-30 | 2018-05-15 | Oath Inc. | Predicting the next application that you are going to use on aviate |
WO2016166558A1 (en) | 2015-04-16 | 2016-10-20 | Google, Inc. | Native application search result adjustment based on user specific affinity |
US9529500B1 (en) | 2015-06-05 | 2016-12-27 | Apple Inc. | Application recommendation based on detected triggering events |
US10169474B2 (en) | 2015-06-11 | 2019-01-01 | International Business Machines Corporation | Mobile application discovery using an electronic map |
WO2017017664A1 (en) * | 2015-07-30 | 2017-02-02 | Wix.Com Ltd. | System integrating a mobile device application creation, editing and distribution system with a website design system |
US10672042B2 (en) | 2016-01-08 | 2020-06-02 | International Business Machines Corporation | Method for tailored mobile application rating insights |
WO2017213560A1 (en) * | 2016-06-08 | 2017-12-14 | Telefonaktiebolaget Lm Ericsson (Publ) | Voice or multimedia session analysis in a wireless communication network |
US10200810B2 (en) * | 2016-06-12 | 2019-02-05 | Apple Inc. | Proactive actions on mobile device using uniquely-identifiable and unlabeled locations |
CN109766138A (en) * | 2017-11-08 | 2019-05-17 | 广东欧珀移动通信有限公司 | Application program prediction model is established, preloads method, apparatus, medium and terminal |
US10945190B2 (en) | 2019-01-04 | 2021-03-09 | Apple Inc. | Predictive routing based on microlocation |
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2013
- 2013-05-23 WO PCT/US2013/042483 patent/WO2013184383A2/en active Application Filing
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Also Published As
Publication number | Publication date |
---|---|
WO2013184383A2 (en) | 2013-12-12 |
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