KR20130089959A

KR20130089959A - Grouping system for mobile device user and method thereof

Info

Publication number: KR20130089959A
Application number: KR1020120005593A
Authority: KR
Inventors: 최호진; 정영섭; 김승석
Original assignee: 한국과학기술원
Priority date: 2012-01-18
Filing date: 2012-01-18
Publication date: 2013-08-13

Abstract

The user clustering system of the present invention includes a life log collection unit for collecting life logs of a plurality of mobile terminal users, a lifestyle similarity inference unit for inferring the similarity of the lifestyles of the users from the collected life logs, and the lifestyle similarity And a user clustering unit for clustering the users into a plurality of groups according to the inference result.

Description

Mobile terminal user clustering system and its method {Grouping System for Mobile Device User and Method}

The present invention relates to a clustering system of a mobile terminal user and a method thereof.

Recently, the use of mobile terminals such as smart phones equipped with various measuring devices is increasing. Researches are also being conducted to provide appropriate services to users by analyzing user behavior patterns using sensors inherent in such mobile terminals.

Meanwhile, the risk of lifestyle-related diseases is increasing and researches on the causes of the diseases are progressing. In addition to hereditary causes for the development of lifestyle diseases, research is being actively conducted to find acquired causes such as lifestyle.

Therefore, there is a need for a technique that can infer a user's lifestyle using a simple measuring device such as a mobile terminal and provide various services required by the user or a third party.

Korean Publication No. 10-2011-0125431 (Nov. 21, 2011)

The present invention has been made to meet the needs of the prior art, a system and method for inferring a user's lifestyle from the user's lifelog collected through a mobile terminal to provide the necessary services to the user and third parties It is to provide.

The technical objects to be achieved by the present invention are not limited to the above-mentioned technical problems, and other technical subjects which are not mentioned can be clearly understood by those skilled in the art from the description of the present invention .

In accordance with another aspect of the present invention, a user clustering system includes a life log collector that collects life logs of a plurality of mobile terminal users, a lifestyle similarity inference unit that infers the similarities of the lifestyles of the users from the collected life logs, and the lifestyles And a user clustering unit for grouping the users into a plurality of groups according to the similarity inference result.

In addition, the user clustering system according to the present invention further comprises a ranking unit for ranking the plurality of groups according to a predetermined criterion and a service providing unit for providing a service suitable for each of the plurality of groups or a third party based on the ranking. It may include.

In accordance with another aspect of the present invention, there is provided a user clustering method comprising: collecting lifelogs of a plurality of mobile terminal users; inferring similarity of lifestyles of the users from the collected lifelogs; Clustering them into a plurality of groups.

In addition, the user clustering method according to the present invention may further include the step of ranking the plurality of groups according to a predetermined criterion and providing a service suitable for each of the plurality of groups or a third party based on the ranking. have.

According to an embodiment of the present invention, a user's life log can be collected through a measurement device embedded in a mobile terminal without the need for an additional measurement device. In addition, according to an embodiment of the present invention, it is possible to cluster the user by inferring the similarity of the lifestyle between the users from the user's life log. In addition, according to an embodiment of the present invention, a grouped user group may be ranked to provide a service suitable for each group or a third party.

1 shows an overall configuration diagram including a user clustering system according to an embodiment of the present invention.
2 illustrates a process of inferring the similarity of the lifestyle from the lifelog according to an embodiment of the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, a detailed description of preferred embodiments of the present invention will be given with reference to the accompanying drawings. However, the embodiments of the present invention may be modified into various other forms, and the scope of the present invention is not limited to the embodiments described below. The shape and the size of the elements in the drawings may be exaggerated for clarity of explanation and the same reference numerals are used for the same elements and the same elements are denoted by the same quote symbols as possible even if they are displayed on different drawings Should be. In the following description, well-known functions or constructions are not described in detail to avoid unnecessarily obscuring the subject matter of the present invention.

1 shows an overall configuration diagram including a user clustering system according to an embodiment of the present invention. The user clustering system according to the embodiment of the present invention may be, for example, the server 200 of FIG. 1.

In an embodiment of the present invention, the server 200 may collect a life log of the user of the mobile terminal 100 obtained from the mobile terminal 100.

According to an exemplary embodiment of the present invention, the mobile terminal 100 may be built-in or externally equipped with measurement apparatuses which the user can carry at all times and obtain user's location information. The measuring device may be a module for wireless communication such as global positioning system (GPS) or Wi-Fi. In addition, the mobile terminal 100 may include, for example, a smartphone, a personal digital assistant (PDA), a tablet PC, a notebook, and the like.

The mobile terminal 100 may acquire location information of the user and accumulate and store the location information in the storage device of the mobile terminal 100. In this case, the mobile terminal 100 may generate and / or store a life log by combining time information corresponding to the location information together. In this case, the visual information may use data used by the mobile terminal 100.

In this case, the location information may be appropriately expressed for the purpose of using the life log. For example, as an embodiment of the present invention, it can be assumed that the life risk is to be obtained through the life log. In this case, the location information may express the location information so that the location information may be related to the lifestyle-related disease. Items related to lifestyle-related illnesses may include tobacco, alcohol, eating habits (such as meat and its frequency, vegetarian and its frequency, and fish consumption and frequency), sleep patterns, medications, and the type and frequency of exercise. have.

Therefore, when recording the location information, in consideration of these items, it may be decided to represent the location information as a resting place, work / study space, restaurants, bars. Therefore, the place visited by all the users 100a, 100b, etc., that is, the location information may be expressed in terms defined in this way.

The life log may be accumulated in units of days, weeks, months, and the like. For example, the daily lifelog shows that the user visits the restaurant every morning, and the weekly lifelog shows the user in the tennis court after a very Monday dinner. Visits can be seen, and the monthly lifelog shows that the user visits the dentist once a month. This is merely an example, and lifelogs may be accumulated annually or in units of predetermined periods of time required.

Alternatively, the life log may be measured by the mobile terminal 100 and then transferred to the server 200 in real time and accumulated in the server 200. The server 200 may include a life log collector that collects life logs of a user from the plurality of mobile terminals 100. In this case, the life log collector may be implemented as an individual module.

The server 200 may include a lifestyle similarity inference unit that infers the similarities of the lifestyles of the users from the collected lifelogs. Of course, the lifestyle similarity inference unit may be implemented as a separate module.

Such inference of lifestyle similarity between users can be made by expressing a lifestyle as a tree for each user's lifelog and measuring similarity between lifestyles based on the lifestyle.

2 illustrates a process of inferring the similarity of the lifestyle from the lifelog according to an embodiment of the present invention. For example, three days of location information of user A may be provided as a life log together with visual information. This is indicated at the upper right of FIG. In this case, the location information is stored together with the visit place of the user and the time information stayed at the visit place.

This lifelog can be expressed as a tree. The three-day lifelog for User A is represented as a tree at the bottom left of FIG. The tree shows daily, weekly, or monthly lifelogs with location information and visit frequency for each time zone.

In Fig. 2, user A stayed in the home at 6:30 am on Monday, and stayed at 8:15 am to 10:15 at the place of study. At this time, the number of visits is one time. At this time, the space between the HOME and the place for the STUDY is expressed as NONE, it can be seen that the user was located in a place irrelevant to lifestyle diseases during the time. As such, a place irrelevant to the purpose of using the lifelog of the embodiment of the present invention may be ignored in the lifelog and lifestyle similarity measurements. On Wednesdays and Fridays, we went out of HOME after 6:30 am and visited RESTAURENT for approximately 20 minutes. That is, on Wednesdays and Fridays, the same pattern is maintained until the RESTAURENT visit, so it is expressed as one branch, but because it is repeated twice, 2 is displayed on the branch. In subsequent time zones, the branches branch from RESTAURENT because they show different patterns on Tuesday and Friday.

As discussed above, time can be seen from the top to the bottom of the tree. In this way, the tree can be completed for the lifelog of a predetermined period according to the time zone.

Such a tree can be created for each user's lifelog, and FIG. 2 illustrates that a tree has been created for three users (User A, B, and C). The similarity measure of the lifestyle may then be replaced by measuring the similarity between each user's tree. To measure the similarity between trees, you can examine the tree's depth, width, type of item, and frequency.

The lifestyle similarity between the users thus obtained may be displayed in a two-dimensional matrix as shown in the lower right of FIG. 2. That is, the similarity between the same users is displayed as 100, the similarity 75 between users A and B, the similarity 54 between users A and C, and the similarity 90 between users B and C.

According to the similarity inference result, users may be clustered into a plurality of groups. That is, clustering may be performed such that users having similar lifestyles form a group. In this case, clustering may be performed according to an absolute evaluation or a relative evaluation. For example, when clustering is performed by an absolute evaluation, grouping may be performed by a group having a similarity of 90 or more, a group having a similarity of 60 to less than 90, and the like based on a specific user. When clustering is performed by relative evaluation, five groups may be formed, for example, by cutting in the order of greatest similarity based on a specific user. The number of such clustering methods and the number of groups may vary depending on the embodiment and / or purpose.

The server 200 may include a ranking unit configured to rank the plurality of groups grouped according to lifestyle similarities between users according to a predetermined criterion. Of course, such a ranking unit may be implemented as a separate module.

That is, each group of users having similar lifestyles may be scored based on a predetermined criterion to determine the ranking. For example, according to one embodiment of the present invention can be scored for each group according to the degree related to lifestyle diseases.

In other words, each group may be scored in consideration of tobacco, drinking, eating habits (frequency of meat, frequency of vegetarian food, frequency of eating fish, etc.), sleep patterns, drug use, type and frequency of exercise. In this case, a representative tree may be generated by combining a tree of N upper users in each group, and scores may be scored for the generated representative tree. The scores thus scored may determine the ranking of the group. The higher the risk of lifestyle disease, the higher the ranking, and the lower the risk of lifestyle disease, the lower the ranking, and vice versa.

The server 200 may include a service provider that provides a service suitable for each group or a third party based on the ranking. Of course, such a service provider may be implemented as a separate module.

For example, the service may provide lifestyle disease risk to users in each group. This may suggest that the user take appropriate action. Groups with a high risk of lifestyle disease can warn users of this and suggest that they reduce meat consumption and exercise. Conversely, a group with a low risk of lifestyle disease may be informed of this and encouraged to maintain a desirable lifestyle. Therefore, each user can effectively improve the lifestyle while considering the risk of lifestyle diseases. It is also possible to improve lifestyles by creating a healthy lifestyle competition between users.

In addition, the ranked clustering status and status may be provided to a third party. Such third parties may include organizations, corporations, governments, and the like, as shown in FIG. Therefore, organizations, companies, governments, etc. can easily grasp the living conditions of the mobile terminal user based on the above information, it can be reflected in the medical policy or marketing.

As described above, since the user directly obtains the life log of the user using a mobile terminal such as a smartphone that is always carried without the participation of other measuring devices and third parties, the risk of privacy information leakage may be reduced. In addition, the obtained data is provided to organizations, companies, governments, and the like so that these organizations can easily grasp the living conditions of users and use them in appropriate policies, thereby improving the lifestyles of users as well as the entire society. It can also help reduce the incidence of lifestyle-related diseases, and can greatly help decision-making in corporations, governments, and organizations.

In the above, embodiments of the present invention have been described in connection with lifestyle diseases, but these are only examples and may be used for other purposes than lifestyle diseases.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is evident that many alternatives, modifications and variations will be apparent to those skilled in the art. will be. Therefore, it should be understood that the above-described embodiments are to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than the foregoing description, It is intended that all changes and modifications derived from the equivalent concept be included within the scope of the present invention.

100: mobile terminal
200: server 300: third party

Claims

A life log collector configured to collect life logs of a plurality of mobile terminal users;
A lifestyle similarity inference unit that infers the similarity of the lifestyles of the users from the collected lifelogs; And
Including a user clustering unit for grouping the users into a plurality of groups according to the lifestyle similarity inference result,
User Clustering System.

The method of claim 1,
And a ranking determiner configured to rank the plurality of groups according to a predetermined criterion.

The method of claim 2,
And a service provider which provides a service suitable for each of the plurality of groups or a third party based on the ranking.

The method according to claim 2 or 3,
The predetermined criterion is a degree of association with lifestyle diseases.

4. The method according to any one of claims 1 to 3,
The life log is a user clustering system, characterized in that it comprises time-based position data measured by a measuring instrument embedded in the mobile terminal.

Collecting lifelogs of a plurality of mobile terminal users;
Inferring similarity of the lifestyles of the users from the collected lifelogs; And
Clustering the users into a plurality of groups according to the lifestyle similarity inference result;
User clustering method.

The method according to claim 6,
And ranking the plurality of groups according to a predetermined criterion.

The method of claim 7, wherein
And providing a service suitable for each of the plurality of groups or a third party based on the ranking.

9. The method according to claim 7 or 8,
The predetermined criterion is a degree associated with lifestyle diseases.

9. The method according to any one of claims 6 to 8,
The life log is a user clustering method, characterized in that it comprises time-based position data measured by a measuring instrument embedded in the mobile terminal.