KR20130049676A - User-experienced search system and method for mobile applications - Google Patents

Abstract

PURPOSE: A user experience-based mobile application search system and a method thereof are provided to efficiently classify applications and to differentiate reliable applications and valuable applications by having references about actual categories for application classification. CONSTITUTION: A metadata generating unit(110) generates application metadata by using situation information. A search unit(120) searches for applications or automatically recommends the same based on the metadata. The metadata generating unit upgrades the metadata by using new situation information. The situation information includes action-based information, personal information including schedule information of a user, environmental information including weather information, location information including a location and an address of the user, time information including weather, date, and time information, and packaging information of the application. [Reference numerals] (110) Metadata generating unit; (120) Search unit

Description

User Experience-based Mobile App Search System and Method {User-Experienced Search System and Method for Mobile Applications}

The present invention relates to a user experience based mobile app search system and method, and more particularly, to a user experience based mobile app search system and method that can search or recommend a personalized app (apllication).

Recently, the number of smartphone subscribers is increasing to about 15 million mobile smart devices.

The smartphone market has grown exponentially and is no longer unique in the global mobile phone market.

The smartphone market is formed around Apple's iOS, Google's Android, RIM's Blackberry, and Microsoft's Windows phone 7.

Unlike existing feature phones, smartphones provide not only built-in applications, but also hundreds of thousands of downloadable applications around online application markers provided for each platform.

In other words, the biggest difference between smartphones and existing feature phones is that search and distribution of applications are provided through a new ecosystem.

In this ecosystem, various people, such as smartphone users, app developers, network operators, and ecosystem providers, pursue their own interests.

Apple's app store has more than 350,000 apps, and Google's Android Market has more than 250,000 apps.

In addition, companies such as Microsoft, HP, and RIM are struggling to increase the amount of apps.

However, due to the exponential growth of apps, users are no longer exposed to the difficulty of searching and downloading the apps they need rather than the fun or convenience of installing and using various apps. Confusion is occurring.

In other words, customers have the advantage of being able to search for and download the desired application, while the recommendation of the application that wants the right app is not enough, and the producer or the publisher is also an active customer with only simple purchase information and evaluation. It is difficult to understand the needs.

An embodiment of the present invention is to build a metadata for a mobile app using a technology that recognizes context collected from a sensor, such as a mobile device, and to create a personalized app based on this. To provide a user experience based mobile app search system and method that can be searched or recommended.

In accordance with another aspect of the present invention, there is provided a user experience-based mobile app search system, including: a metadata generator configured to generate app metadata using context information; And a searcher searching for or automatically recommending an app based on the app metadata.

Preferably, the metadata generating unit upgrades the app metadata using new context information.

Preferably, the context information includes behavior-based information including user's movement information, personal information including user's schedule management information, environment information including weather information, location information including address and location of the user, season and date. , At least one of time information including time and packaging information of the app.

Preferably, the situation information is characterized in that the data collected by the sensor of the mobile device is processed in the form of a predetermined log file.

Preferably, the storage device for storing the app metadata or the upgraded app metadata.

Preferably, the search unit may further include basic information of the name, package name, number of downloads, version, and producer information of the application, to search or recommend it.

Preferably, the app metadata may be generated from the behavior-based information by using statistical learning of an AI (Artificial Intelligence) technique using a Bayesian network and a support vector machine (SVM).

Preferably, a comparison unit for comparing the new application metadata and the application metadata; Further comprising, the search unit is characterized in that to recommend the app (application) based on the comparison result.

In accordance with another aspect of the present invention, there is provided a user experience-based mobile app search method. The method may further include: generating a metadata of an application using context; And a search step of searching for or automatically recommending an application based on the app metadata.

Preferably, the metadata generation step is characterized by upgrading the app metadata by using the new context information.

Preferably, the context information includes behavior-based information including user's movement information, personal information including user's schedule management information, environment information including weather information, location information including address and location of the user, season and date. , At least one of time information including time and packaging information of the app.

Preferably, the situation information is characterized in that the data collected by the sensor of the mobile device is processed in the form of a predetermined log file.

Preferably, the storing step of storing the app metadata or the upgraded app metadata.

Preferably, the searching step may further include the basic information of the name of the app, the package name, the number of downloads, the version, and the producer information.

Preferably, the app metadata may be generated from the behavior-based information by using statistical learning of an AI (Artificial Intelligence) technique using a Bayesian network and a support vector machine (SVM).

Preferably, a comparison step of comparing the new application metadata and the application metadata; Further, wherein the searching step is characterized in that to recommend the app (application) based on the comparison result.

According to the user experience-based mobile app search system and method according to the present invention, an application user can search for an app based on more various criteria, and also have an advantage of searching for and using an app specialized for the user.

According to the user experience based mobile app search system and method according to the present invention, companies such as Apple or Google have criteria for more practical categories for classifying applications, thereby effectively classifying overflowing apps and unreliable apps. It is possible to have a more realistic criterion to distinguish between and worthwhile apps.

According to the user experience-based mobile app search system and method according to the present invention, the app developer can receive feedback in real time on the area of the empty application and the user's response based on the user's experience. It is possible to get more than just evaluation.

According to the user experience-based mobile app search system and method according to the present invention, the operator providing the communication network can help the traffic management by performing the prediction of the network load in advance based on the analysis of the use of the app. By intensively investing in a telecom infrastructure of the required nature, it is also effective to help establish a strategy that is more advantageous than competitors.

1 is a view showing a schematic diagram of a user experience based mobile app search system according to the present invention.
2A is a diagram illustrating an embodiment of a user experience based mobile app search system search unit according to the present invention.
2B is a view showing how the context information used in the user experience based mobile app search system according to the present invention is different from the classification criteria of the existing app search system.
3 is a diagram illustrating an embodiment of a network configuration including a user experience based mobile app search system according to the present invention.
4 is a diagram illustrating an embodiment of basic information provided in a user experience based mobile app search system according to the present invention.
5 is a diagram illustrating a process of extracting basic information of FIG. 4.
6A is a diagram illustrating an embodiment of context information collected by a mobile device in a user experience based mobile app search system according to the present invention.
6B is a diagram illustrating an embodiment of a sensor for collecting context information used in a user experience based mobile app search system according to the present invention.
6C shows one embodiment of data collected by the sensor of the present invention.
7 is a view showing an embodiment of the app metadata generated by the metadata generator in the present invention.
8 is a diagram illustrating a process of generating app metadata in a user experience based mobile app search system of the present invention.
9 is a flowchart illustrating a user experience based mobile app search method of the present invention.
10 is a flowchart illustrating a recommendation of an application in the user experience based mobile app search method of the present invention.
11 is a view showing the configuration of a user experience based mobile app search system of the present invention.

In order to fully understand the present invention, operational advantages of the present invention, and objects achieved by the practice of the present invention, reference should be made to the accompanying drawings and the accompanying drawings which illustrate preferred embodiments of the present invention.

BEST MODE FOR CARRYING OUT THE INVENTION Hereinafter, the present invention will be described in detail with reference to the preferred embodiments of the present invention with reference to the accompanying drawings. Like reference symbols in the drawings denote like elements.

1 is a view showing a schematic diagram of a user experience based mobile app search system according to the present invention.

The user experience based app search system 100 of the present invention includes a metadata generator 110 and a searcher 120.

The metadata generator 110 generates application metadata by using context.

The searcher 120 searches for or automatically recommends an app based on the app metadata.

Application of the user experience based app search system of the present invention enables a personalized app search.

The present invention is to make it possible to search for an app based on the situational awareness of the mobile device.

There are various types of mobile devices of the present invention such as smart phones, tablet PCs, MIDs, and the like.

Mobile device devices provide several sensors (acceleration, illuminance, location information, sound) inside them, and various applications of mobile devices utilize information sensed by these sensors to provide richer user interaction than ever before. Doing.

The present invention extracts a context using sensors existing inside without a sensor additionally attached to a mobile device, and generates app metadata for use in app search using the extracted context.

As an example, when searching for a calendar app, office workers A and B work in a team within the same company.

A finishes the morning meeting during the week and runs the 'jorte' application between 10 and 11 o'clock to check and reschedule. After that, run ‘jorte’ several times to check and change the schedule.

Since Monday is the start of the week, we keep track of our schedule more closely, and Thursday keeps our schedule tighter to prepare for the weekly meetings on Friday.

However, B has a schedule similar to A but does not have a separate schedule, so the schedule frequently overlaps or twists during work. Difficult to manage his schedule, he recommends and uses jorte.

The process of recommending 'jorte' to B by the user experience based app search system according to the present invention is as follows.

Office worker A collects the context when he runs jorte during the weekday on his smartphone.

The contexts collected are time, location used, area used, day of the week, and behavior during execution.

When the context of A is collected, the information used with 'jorte' is displayed as statistics through the Bayesian network, SVM, etc.

Statistical information classified through learning is added as meta information at application execution time.

The generated meta data of 'jorte' is used to recommend 'jorte' to office worker B who needs an application to use for scheduling.

The weekday days of office worker B and also the context of time, location, space, area, etc. are collected and displayed as statistics through Bayesian network, SVM, etc.

If the generated value is similar to the meta data of the 'jorte' and the 'jorte' is not installed, B is recommended to be 'jorte'.

As an example 2, the case of searching for a bus bus app.

Officer A goes to work by bus. In order to catch a bus between 8:00 and 8:30 in the morning, he uses an application called “Seoul Bus” to check the bus time and go to the bus stop.

As you usually leave your home, check the bus time and decide whether to walk or run. That's why he doesn't always miss the bus.

Office worker B also goes to work by bus. He steps to the stop to catch a bus between 7:50 and 8:10 in the morning.

However, his bus was jagged, so after arriving at the bus stop, he often learned about the situation and waited for the next bus.

While office worker A goes on a bus, he collects the context of running Seoul Bus. The contexts collected are time, location used, area used, day of the week, and behavior during execution. When A's context is collected, information using ‘Seoul Bus’ is shown as a statistical value through Bayesian network, SVM, etc. Statistical information classified through learning is added as meta information at application execution time. The generated meta data of 'Seoul Bus' is used when recommending 'Seoul Bus' to office worker B who needs to check the bus schedule when he goes to work in the morning. While office worker B is on the bus, the context of time, location, space, area, etc. is also collected and displayed as statistics through Bayesian network and SVM. If the generated value is similar to the meta data of 'Seoul Bus' and 'Seoul Bus' is not laid, B is recommended to 'Seoul Bus'.

You can never miss a bus using the application called 'Seoul Bus', which is recommended for smartphones.

2A is a diagram illustrating an embodiment of a user experience based mobile app search system search unit according to the present invention.

The app search system of the present invention enables user experience based search 220, unlike providing only the information of the title, price, and category of the app provided for the conventional search 210 of the app.

2B is a view showing how the context information used in the user experience based mobile app search system according to the present invention is different from the classification criteria of the existing app search system.

The conventional app search system 230 of the mobile device provided only basic information of the name, type, manufacturer, category, evaluation order, and price of an application.

However, the user experience-based app search system 240 of the present invention provides the information 250 based on the contextual information obtained from the user's experience in using the app in addition to the basic information 230 of the app.

Through the user experience-based app search system of the present invention, the problem of app search provided based on simple level categories, product descriptions, and unspecified user ratings determined by existing ecosystem managers is solved. Based on the exact usage pattern of the generated app, it can be systematically databased and provided to various stakeholders.

Context refers to information that defines the characteristics of a situation, such as a person, place, thing, object, or time, that affects the interaction between a user and another user, system, or device application in relation to ubiquitous computing. it means.

More specifically, network connection status, communication bandwidth, and computing contexts such as printers, displays, and workstations, user contexts including people's profiles, locations, and surroundings, lighting and noise levels. There are physical contexts such as traffic conditions and temperature, and time contexts such as time, week, month and season.

Such contextual information may be used by the system to identify and gather information through various sensing devices and applications, to provide various application services, or to infer a third conclusion by combining with other contextual information.

One embodiment of the context information 250 used for the app search in the present invention may include an app usage pattern, behavior-based information, personal preference information, location information, time information.

3 is a diagram illustrating an embodiment of a network configuration including a user experience based mobile app search system according to the present invention.

The user mobile device 300 refers to smart devices having an app ecosystem, such as smartphones and tablet PCs.

The mobile device 300 includes an application manager 301 for managing application-oriented information, a context collection module 302 for collecting mobile context information, and an internal storage 303 for processing and storing the collected context information. Include.

The mobile device 300 transmits the situation information stored in the internal storage 303 to the server 330 or provides a search interface for displaying or recommending an app search result transmitted from the server 330.

The user information processing module 331 included in the server 330 is a module in charge of managing each user using various mobile devices. This module distinguishes and manages the user's app ecosystem and manages each user's required profile to provide account services.

The user information DB 332 stores account information generated by the user information processing module and manages information of each user in the DB.

The metadata generation unit 333 of the app search system according to the present invention generates the app metadata by processing the context information received by the mobile device, that is, the data on the app usage information, extracting and organizing it according to the required data schema.

The search unit 335 performs a function of searching for an app or recommending an app based on the generated app metadata.

The application metadata stored in the server side returns a result of the search query to the client (mobile device) through the search unit 335. The search unit 335 provides a recommendation or information on an optimal app for a user's situation, which is updated in real time.

App search system according to the present invention may be configured to include a storage unit 334, the storage unit stores the metadata generated by the metadata generator 333.

In addition, the app metadata is upgraded to reflect the context information collected by the use of other users, and the upgraded metadata is stored.

In other words, the dynamically generated client's usage information of a specific app for each client (mobile device) is stored in accordance with the app-oriented schema and updated and managed by continuous events.

The basic information providing unit 336 extracts static information for each ecosystem existing in the outside 340 and provides basic information provided in the app search. Static information provides each app's information in each device, webpage and dedicated program.

It has the characteristics of a system that requires periodic or temporary update or use of information between mobile devices and app metadata server. Therefore, a communication network 310 capable of supporting an operation mode of a client and a server suitable for a communication connection method is required.

The application online market 340 refers to an app sales total provided for each mobile app ecosystem individually. Here, the basic information of the user-based app search system of the present invention is collected and collected.

4 is a diagram illustrating an embodiment of basic information provided in a user experience based mobile app search system according to the present invention.

4 is a diagram illustrating an example of basic information of a calendar program for Android called 'jorte' which is a calendar application.

Information described in FIG. 4 includes application name, application ID, application category, package name, version, class name, permission, rating, creator, and the like.

5 is a diagram illustrating a process of extracting basic information of FIG. 4.

It provides application basic information about app search by platform of each mobile device.

The mobile device 510 300 of FIG. 3 extracts the ID of the applica- tion and the package name and transmits the extracted ID to the transmission network (520).

Based on the app ID and the package name, the application online market 340 transmits the rating, the number of downloads, the version, the authority information, and the producer information to the basic information provider 336 (530).

The storage unit 334 stores the basic information of the app from the basic information providing unit 336 (540) and provides the metadata of the app to the search unit 335 (550).

Basic information of the app corresponds to the first stage of the app metadata of the present invention.

6A is a diagram illustrating an embodiment of context information collected by a mobile device in a user experience based mobile app search system according to the present invention.

The behavioral context and motion information 610 indicates the current degree of movement of the user using the app by using the speed, altitude, and location information that can be received from the GPS.

That means you walk, run, or ride a vehicle.

2. From the 3-axis accelerometer, we can see the type of vibration activity. It is possible to speculate on behaviors such as vigorous movements and provide additional information beyond the speed (GPS) of walking and running.

By the motion information 610, it is possible to know whether the app is an app that is mainly used while moving in a car or an application that is used while walking or running (moving).

Spatial = Location = Spatial context 620 can distinguish between whether it is indoors or outdoors through GPS information and information about the WIFI access point.

If you're outdoors, you can use GPS coordinates to find out where your location is.

The spatial context 620 may indicate information about where the application is mainly executed, in which neighborhood, and in which building.

Environmental context, environmental information 630 may be mainly information such as weather. The way to get this information is to query the GPS coordinates and retrieve the information from the Meteorological Agency or other informational sources, and then roughly combine the weather, temperature and humidity at the time the application is running.

Temporal = TIME = time context 640 encompasses the concept of a wide range of time.

For example, you can find out which applications have a lot of seasonal influences, and you can find information about what time of day you use and how many times a week you use.

Personal Context, Personal Information (650) Depending on the user's consent information, it may include information about a person's job, gender, and age. It is also possible to combine information such as those used mainly in time.

Application, app packaging information 660 is information about the use of the application that can be obtained from the system for application packaging information (size, update time, version information, etc.) for the application.

6B is a diagram illustrating an embodiment of a sensor for collecting context information used in a user experience based mobile app search system according to the present invention.

The motion situation information 610 may determine whether sleep, weather, and movement are performed by the 3-axis acceleration sensor.

The spatial situation information 620 distinguishes whether it is currently indoor or outdoors by GPS.

The environmental information 630 may query information about the coordinates of the GPS and combine information such as weather, temperature, and humidity at the time of execution of the application by retrieving information from the Meteorological Agency or other information providing site.

The time context 640 collects from the clock of the mobile device.

The personal information 650 is collected from the user information DB 332 of the server.

App packaging information 660 is collected from a dedicated server provided for each mobile platform.

6C shows one embodiment of data collected by the sensor of the present invention.

The information collected by the sensor includes acceleration, illuminance, sound, location by GPS, and information on the mobile device itself.

7 is a view showing an embodiment of the app metadata generated by the metadata generator in the present invention.

App metadata is generated by the metadata generating unit 110 by processing the situation information collected by the sensor of the mobile device.

It includes main motion information to be executed from the motion situation information, the user's actions mainly used, and the user's situation information mainly used.

From the spatial situation information, the main use location (address information), indoor or outdoor frequency, and main use area information are included.

It provides the main weather, temperature, and seasonal information that the app runs from the environmental information.

From the time context, you can find out how much time your app is mainly used, what day of the week is used, and the average daily usage.

From the personal information, the user's occupation, gender, and age can be known.

System information can be known from the app packaging information.

8 is a diagram illustrating a process of generating app metadata in a user experience based mobile app search system of the present invention.

The mobile device 300 includes an application manager 301 for managing application-oriented information, a context collection module 302 for collecting mobile context information, and an internal storage 303 for processing and storing the collected context information. Include.

The metadata generation unit 333 of the app search system according to the present invention generates the app metadata by processing the context information received by the mobile device, that is, the data on the app usage information, extracting and organizing it according to the required data schema.

App search system according to the present invention may be configured to include a storage unit 334, the storage unit stores the metadata generated by the metadata generator 333.

In addition, the app metadata is upgraded to reflect the context information collected by the use of other users, and the upgraded metadata is stored.

In other words, the dynamically generated client's usage information of a specific app for each client (mobile device) is stored in accordance with the app-oriented schema and updated and managed by continuous events.

The basic information providing unit 336 extracts static information for each ecosystem existing in the outside 340 and provides basic information provided in the app search. Static information provides each app's information in each device, webpage and dedicated program.

The search unit 335 performs a function of searching for an app or recommending an app based on the generated app metadata.

The application metadata stored in the server side returns a result of the search query to the client (mobile device) through the search unit 335. The search unit 335 provides a recommendation or information on an optimal app for a user's situation, which is updated in real time.

9 is a flowchart illustrating a user experience based mobile app search method of the present invention.

The metadata generating unit generates application metadata using context information (S910).

The search unit searches for or automatically recommends an app based on the app metadata (S920).

10 is a flowchart illustrating a recommendation of an application in the user experience based mobile app search method of the present invention.

In the process of using A by the application 1, the mobile device collects context information (S1010).

Based on the situation information (action-based contextual information) collected by the metadata generating unit 110, using statistical learning of AI (Artificial intelligence) technique using a Bayesian network and a support vector machine (SVM) (S1020). By generating the app metadata (S1030).

User B is based on the context information (action-based context information) collected by the metadata generating unit 110 based on the context information (S1040) collected by the mobile device sensor Bayesian Network (Bayesian Network), SVM ( App metadata is generated by using statistical learning of AI (Artificial intelligence) technique using a support vector machine (S1050) (S1060).

The search unit 335 compares the application metadata generated on the mobile device of B with the application metadata generated on the mobile device of A (S1070) and recommends App 1 to the B if similar. (S1080).

11 is a view showing the configuration of a user experience based mobile app search system of the present invention.

The user experience based app search system of the present invention may further include a comparator (not shown) for comparing different app metadata.

Various situation information data is collected by sensors embedded in the mobile device (1110 and 1113).

Based on the collected contextual information data, app metadata is generated (1111, 1114) using statistical learning of AI (Artificial Intelligence) technique using a Bayesian network and a support vector machine (SVM) (1112).

However, the app metadata generated from A is the result obtained by using app 1 (application1), and B is the metadata obtained in everyday life.

The comparison unit (not shown) compares the application metadata of B and the metadata obtained as a result of using the application 1 of A (1115), and the search unit 120 determines the application 1 based on the comparison result. (application 1) is recommended to B (1116).

As described above, optimal embodiments have been disclosed in the drawings and the specification. Although specific terms have been employed herein, they are used for purposes of illustration only and are not intended to limit the scope of the invention as defined in the claims or the claims. Therefore, those skilled in the art will understand that various modifications and equivalent other embodiments are possible therefrom. Accordingly, the true scope of the present invention should be determined by the technical idea of the appended claims.

Claims (16)

A metadata generator which generates application metadata using context information; And
And a search unit for searching for or automatically recommending an app based on the app metadata. The method of claim 1, wherein the metadata generating unit
User experience based mobile app search system, characterized in that for upgrading the app metadata using the new context information. The method of claim 1, wherein the situation information
Behavior-based information including user's movement information, personal information including user's schedule management information, environment information including weather information, location information including address and location of the user, time information including season, date and time And at least one of packaging information of the application. The method of claim 1, wherein the situation information
The user experience-based mobile app search system, characterized in that the data collected by the sensor of the mobile device is processed in the form of a predetermined log file. 3. The method according to claim 1 or 2,
The user experience-based mobile app search system further comprises; a storage unit for storing the app metadata or the upgraded app metadata. According to claim 1, The search unit
A user experience-based mobile app search system, characterized in that the search further includes the basic information of the name, package name, number of downloads, version, and producer information of the application. The method of claim 3, wherein
A user experience based mobile app search system that generates the app metadata from the behavior based information using statistical learning of AI (Artificial Intelligence) technique using Bayesian Network and support vector machine (SVM). . The method of claim 1,
A comparison unit for comparing new application metadata with the application metadata; Further comprising:
The search unit is a user experience based mobile app search system, characterized in that for automatically recommending the app (application) based on the comparison result. A metadata generation step of generating application metadata using context information; And
And a search step of searching for or automatically recommending an app on the basis of the app metadata. The method of claim 9, wherein the metadata generation step
User experience based mobile app search method, characterized in that to upgrade the app metadata using the new context information. The method of claim 9, wherein the situation information
Behavior-based information including user's movement information, personal information including user's schedule management information, environment information including weather information, location information including address and location of the user, time information including season, date and time And at least one of packaging information of the application. The method of claim 9, wherein the situation information
User experience-based mobile app search method characterized in that the data collected by the sensor of the mobile device is processed into a predetermined log file form. 11. The method according to claim 9 or 10,
And storing the app metadata or the upgraded app metadata. The method of claim 9, wherein the searching step
A user experience-based mobile app search method, characterized in that the search further includes the basic information of the name, package name, number of downloads, version, producer information of the application (application). The method of claim 11,
A user experience based mobile app search method comprising generating the app metadata from the behavior based information using statistical learning of AI (Artificial Intelligence) technique using Bayesian Network and support vector machine (SVM) . The method of claim 9,
A comparison step of comparing new application metadata with the application metadata; Further comprising:
The searching step is a user experience based mobile app search method, characterized in that for automatically recommending the app (application) based on the comparison result.

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