JP2019159443A - Information processing apparatus, information processing method and program - Google Patents
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Abstract
Description
本発明は、情報処理装置、情報処理方法、およびプログラムに関する。 The present invention relates to an information processing apparatus, an information processing method, and a program.
従来、特定のサービスに関連する対象者の属性情報に基づいて、該対象者を分類する技術についての研究が進められている（例えば、特許文献１参照）。 Conventionally, research on a technique for classifying a target person based on attribute information of the target person related to a specific service has been advanced (for example, see Patent Document 1).
特定の設備やサービスを利用する複数の対象者間の関連度を簡便な手法で定量的に評価することが求められている。 There is a need to quantitatively evaluate the degree of association between a plurality of subjects who use specific facilities and services by a simple method.
本発明は、このような事情を考慮してなされたものであり、複数の対象者間の関連度を簡便な手法で定量的に評価することが可能な情報処理装置、情報処理方法、およびプログラムを提供することを目的の一つとする。 The present invention has been made in consideration of such circumstances, and an information processing apparatus, an information processing method, and a program capable of quantitatively evaluating the degree of association between a plurality of subjects by a simple technique Is one of the purposes.
本発明の一態様は、複数の対象者が所定の動作を行った事実が時刻に対応付けられた動作情報を収集する収集部と、前記収集部によって収集された前記動作情報に含まれる時刻が所定の範囲に含まれる前記所定の動作を行った前記対象者間の関連度が高くなるように、前記関連度を算出する算出部とを備える、情報処理装置である。 In one aspect of the present invention, a collection unit that collects operation information in which a fact that a plurality of subjects have performed a predetermined operation is associated with time, and a time included in the operation information collected by the collection unit An information processing apparatus comprising: a calculation unit that calculates the degree of association so that the degree of association between the subjects who have performed the predetermined operation included in a predetermined range is high.
本発明の一態様によれば、複数の対象者間の関連度を簡便な手法で定量的に評価することが可能である。 According to one aspect of the present invention, the degree of association between a plurality of subjects can be quantitatively evaluated by a simple technique.
以下、図面を参照して、本発明の情報処理装置、情報処理方法、およびプログラムの実施形態について説明する。 Hereinafter, an information processing apparatus, an information processing method, and a program according to embodiments of the present invention will be described with reference to the drawings.
＜実施形態＞
以下、本発明の実施形態について説明する。実施形態の集団判定システムは、所定の動作を行う対象者を互いに関連付けすることで、対象者の集団判定を行う。「所定の動作」とは、反復性を有する任意の動作を示す。所定の動作とは、例えば、会社に属する社員が食事をとる際に利用する食堂（以下、「社員食堂」）における商品の精算、会社の入り口に設置された認証機能を有するゲートの通過、交通機関における精算機能を有するゲートの通過、アミューズメント施設における入場ゲートの通過などである。また、「集団判定」とは、複数の対象者が所定の動作を行った事実が時刻に対応付けられた動作情報に基づいて、対象者を互いに関連付けして、対象者を組分け（グルーピング）することである。以下においては、所定の動作が、社員食堂における商品の精算であり、対象者が社員である場合を例に挙げて説明する。
<Embodiment>
Hereinafter, embodiments of the present invention will be described. The group determination system of the embodiment performs target group determination by associating target persons performing a predetermined operation with each other. The “predetermined operation” indicates an arbitrary operation having repeatability. The predetermined operations include, for example, payment of products in a cafeteria (hereinafter referred to as “employee cafeteria”) used when employees belonging to the company eat, passage of gates with authentication functions installed at the entrance of the company, traffic This includes the passage of a gate with a checkout function at an institution and the passage of an entrance gate at an amusement facility. In addition, “group determination” refers to the fact that a plurality of target persons have performed a predetermined action based on action information associated with time, and the target persons are associated with each other, and the target persons are grouped (grouped). It is to be. In the following, an example will be described in which the predetermined operation is the settlement of products in the employee cafeteria and the target person is an employee.
＜１−１．システム構成＞
図１は、実施形態に係る集団判定システム１の全体構成を示す図である。集団判定システム１は、例えば、端末装置３（情報処理装置の一例）と、決済サーバ５（情報処理装置の一例）とを備える。端末装置３と決済サーバ５とは、ネットワークＮＷを介して通信する。ネットワークＮＷは、例えば、ＷＡＮ（Wide Area Network）やＬＡＮ（Local Area Network）、インターネット、プロバイダ装置、無線基地局、専用回線などのうち一部または全部を含む。
<1-1. System configuration>
FIG. 1 is a diagram illustrating an overall configuration of a group determination system 1 according to the embodiment. The group determination system 1 includes, for example, a terminal device 3 (an example of an information processing device) and a settlement server 5 (an example of an information processing device). The terminal device 3 and the settlement server 5 communicate with each other via the network NW. The network NW includes, for example, a part or all of a wide area network (WAN), a local area network (LAN), the Internet, a provider device, a wireless base station, a dedicated line, and the like.
端末装置３は、対象者が所定の動作を行う現場に設置され、対象者の行動に基づいて所定の処理を行う。本実施形態において、端末装置３は、社員食堂に設置された、社員の操作に基づいて商品の精算を行う精算機（例えば、セルフ精算レジ）である。端末装置３は、精算情報を所定期間保持する。端末装置３は、例えば、決済サーバ５から精算情報の提供要求を受けた場合には、ネットワークＮＷを介して、精算情報を決済サーバ５に送信する。なお、複数の端末装置３がネットワークＮＷに接続されてよい。 The terminal device 3 is installed at a site where the target person performs a predetermined operation, and performs a predetermined process based on the behavior of the target person. In the present embodiment, the terminal device 3 is a payment machine (for example, a self-checkout cash register) installed in the employee cafeteria that performs payment of products based on the operations of employees. The terminal device 3 holds the settlement information for a predetermined period. For example, when receiving a payment information provision request from the payment server 5, the terminal device 3 transmits the payment information to the payment server 5 via the network NW. A plurality of terminal devices 3 may be connected to the network NW.
決済サーバ５は、ネットワークＮＷを介して、端末装置３から精算情報を収集し、精算金の決済処理を行う。決済処理は、給与システムと連携することで給与から精算金が自動的に減算されるようなシステム、社員が自ら任意の金額を予め入金するプリペイド方式のシステム、クレジットカードのシステム、インターネットバンキングなどを利用して行われてよい。さらに、決済サーバ５は、収集した精算情報に基づいて、社員食堂を利用した社員の集団判定を行う。 The settlement server 5 collects settlement information from the terminal device 3 via the network NW, and performs settlement processing for settlement money. Settlement processing includes a system that automatically subtracts the payment from the salary by cooperating with the salary system, a prepaid system in which the employee pays an arbitrary amount in advance, a credit card system, Internet banking, etc. It may be performed using. Further, the settlement server 5 makes a group determination of employees using the employee cafeteria based on the collected payment information.
＜１−２．社員食堂の構成＞
図２は、実施形態に係る社員食堂Ｃの構成の一例を示す図である。社員食堂Ｃは、例えば、会社内の所定のフロアに設けられた食品提供設備である。社員食堂Ｃには、例えば、食品を提供する店舗Ｓと、食事をとるためのテーブルＴ１からＴ６と、各テーブルの周囲に配置された椅子と、端末装置３として計８つの端末装置３−１から３−８とが設けられている。店舗Ｓは、例えば、麺類、定食類等のメニュー毎（メニュー１から４）にコーナーが分けられている。テーブルＴ１からＴ４は、社員が集団で食事をとることが可能である。例えば、テーブルＴ１の周囲には計５つの椅子が配置されており、最大で５人の社員が集団で食事をとることが可能である。また、テーブルＴ５およびＴ６は、主に、１人で食事をとることを想定して設けられている。
<1-2. Composition of employee cafeteria>
FIG. 2 is a diagram illustrating an example of the configuration of the employee cafeteria C according to the embodiment. The employee cafeteria C is, for example, a food provision facility provided on a predetermined floor in the company. The employee cafeteria C includes, for example, a store S that provides food, tables T1 to T6 for eating, chairs arranged around each table, and a total of eight terminal devices 3-1 as terminal devices 3. To 3-8. In the store S, for example, a corner is divided for each menu (menus 1 to 4) such as noodles and set meals. Tables T1 to T4 allow employees to eat in groups. For example, a total of five chairs are arranged around the table T1, and a maximum of five employees can eat together. The tables T5 and T6 are provided mainly assuming that one person has a meal.
端末装置３−１から３−８は、２つのグループに分けて異なる設置場所に配置されている。第１グループＧ１は、端末装置３−１から３−４を含む。第１グループＧ１に属する端末装置３−１から３−４は、出口Ｅ２付近に配置されている。第２グループＧ２は、端末装置３−５から３−８を含む。第２グループＧ２に属する端末装置３−５から３−８は、出口Ｅ３付近に配置されている。 The terminal devices 3-1 to 3-8 are divided into two groups and arranged at different installation locations. The first group G1 includes terminal devices 3-1 to 3-4. The terminal devices 3-1 to 3-4 belonging to the first group G1 are arranged near the exit E2. The second group G2 includes terminal devices 3-5 to 3-8. Terminal devices 3-5 to 3-8 belonging to the second group G2 are arranged in the vicinity of the exit E3.
社員食堂Ｃを利用する社員は、入口Ｅ１から入場し、店舗Ｓで所望の食品を受け取り、テーブルＴ１からＴ６のいずれかで食事をした後、端末装置３−１から３−８のいずれかで精算処理を行い、出口Ｅ２またはＥ３から退場する。社員食堂Ｃを利用する際、社員は１人で食事を行うか（以下、「ひとり飯」）、或いは、他の社員と一緒に（集団で）食事を行う（以下、「一緒飯」）。図２では、社員Ｐ１からＰ５の５人が、テーブルＴ１で一緒飯を行っており、社員Ｐ６がテーブルＴ５でひとり飯を行っており、社員Ｐ７がテーブルＴ６でひとり飯を行っている例を示している。 Employees who use the employee cafeteria C enter from the entrance E1, receive desired food at the store S, eat at any of the tables T1 to T6, and then use any of the terminal devices 3-1 to 3-8. Checkout is performed and exit from exit E2 or E3. When using the employee cafeteria C, the employee eats alone (hereinafter referred to as “one person”) or with other employees (group) (hereinafter referred to as “joint rice”). In FIG. 2, five employees P1 to P5 are cooking together at table T1, employee P6 is serving alone at table T5, and employee P7 is serving alone at table T6. Show.
図３は、実施形態に係る集団判定の一例を説明する図である。一緒飯を行った集団は、食事を終了した後、連れ立って端末装置３に向かい、同じタイミングで精算処理を行うことが想定される。そこで、本実施形態においては、端末装置３−１から３−８での精算処理の精算時刻に基づいて集団判定を行う。まず、図２に示される例において、一緒飯を行った集団は、第１グループＧ１および第２グループＧ２のいずれか一方に属する端末装置３に連れ立って向かい精算処理を行う。 FIG. 3 is a diagram illustrating an example of group determination according to the embodiment. It is assumed that the group having cooked together, after finishing the meal, is taken to the terminal device 3 and performs the settlement process at the same timing. Therefore, in the present embodiment, group determination is performed based on the settlement time of the settlement process in the terminal devices 3-1 to 3-8. First, in the example shown in FIG. 2, the group that has cooked together is accompanied by the terminal device 3 belonging to one of the first group G1 and the second group G2, and performs a settlement process.
一緒飯を行った集団の精算処理のやり方としては以下の３つのパターンが想定される。第１のパターンは、図３においてＴ１に示されるように、各社員が順に一つの端末装置３−１で精算処理を行うパターンである。第２のパターンは、図３においてＴ２に示されるように、各社員が同一グループに属する複数の端末装置３−２から３−４に分かれて精算処理を行うパターンである。第３のパターンは、第１のパターンと、第２のパターンとを組み合わせたパターンである。 The following three patterns are assumed as the method of the settlement process of the group that cooked together. As shown in T1 in FIG. 3, the first pattern is a pattern in which each employee sequentially performs a settlement process with one terminal device 3-1. As shown in T2 in FIG. 3, the second pattern is a pattern in which each employee divides into a plurality of terminal devices 3-2 to 3-4 belonging to the same group and performs a settlement process. The third pattern is a combination of the first pattern and the second pattern.
＜１−３．端末装置＞
図１に戻り、端末装置３の機能構成について説明する。端末装置３は、例えば、店舗Ｓにより提供される食品を乗せた食器の裏側に設けられたＩＣチップ内蔵のタグの情報を読み取ることで精算処理を行う。端末装置３は、例えば、通信部３１と、認証部３２と、読取部３３と、精算部３４と、表示部３５と、記憶部３６とを備える。通信部３１は、ネットワークＮＷを介して、決済サーバ５と通信する。通信部３１は、例えば、ＮＩＣ等の通信インターフェースを含む。
<1-3. Terminal device>
Returning to FIG. 1, the functional configuration of the terminal device 3 will be described. For example, the terminal device 3 performs checkout processing by reading information on a tag with a built-in IC chip provided on the back side of the tableware on which food provided by the store S is placed. The terminal device 3 includes, for example, a communication unit 31, an authentication unit 32, a reading unit 33, a settlement unit 34, a display unit 35, and a storage unit 36. The communication unit 31 communicates with the settlement server 5 via the network NW. The communication unit 31 includes a communication interface such as a NIC, for example.
認証部３２は、社員を識別する情報を読み取るリーダである。例えば、認証部３２は、ＩＣチップ内蔵の社員証に含まれる例えば社員ＩＤなどの社員識別情報を読み取ることで社員の認証を行う。なお、認証部３２は、顔認証、指紋認証、音声認証などの生体認証情報に基づいて社員を識別する情報を読み取るものであってもよい。なお、決済処理が、クレジットカードのシステム、インターネットバンキングなどを利用して行われる場合には、認証部３２は、磁気ストライプを読み取ることが可能なクレジット処理端末機であってよい。また、非接触方式の媒体を用いる場合、認証部３２は、ＣＬＦ（Contactless Front-End）であってよい。 The authentication unit 32 is a reader that reads information for identifying an employee. For example, the authentication unit 32 authenticates an employee by reading employee identification information such as an employee ID included in an employee card with a built-in IC chip. Note that the authentication unit 32 may read information for identifying an employee based on biometric authentication information such as face authentication, fingerprint authentication, and voice authentication. When the payment process is performed using a credit card system, Internet banking, or the like, the authentication unit 32 may be a credit processing terminal capable of reading the magnetic stripe. When a non-contact type medium is used, the authentication unit 32 may be a CLF (Contactless Front-End).
読取部３３は、食器の裏側に設けられたＩＣチップ内蔵のタグの情報を読み取るリーダである。読取部３３は、このタグの情報に含まれるシリアルナンバーなどの固有の識別情報を読み取るセンサを備える。読取部３３は、例えば、トレー上に配置された複数の食器のタグの情報を同時に読み取ることができる。 The reading unit 33 is a reader that reads information from a tag with a built-in IC chip provided on the back side of the tableware. The reading unit 33 includes a sensor that reads unique identification information such as a serial number included in the tag information. For example, the reading unit 33 can simultaneously read information on tags of a plurality of dishes arranged on a tray.
精算部３４は、読取部３３により読み取られたタグの情報に基づいて、精算処理を行う。精算部３４は、例えば、タグの情報に含まれる識別情報と対応する商品の金額を記憶部３６に予め記憶された金額情報Ｒ１から読み出し、精算金額を算出する。次に、精算部３４は、算出した精算金額を含む精算情報Ｄ１（動作情報）として記憶部３６に記憶させる。なお、プリペイドカードなどを用いて精算が行われる場合、精算部３４は、プリペイドカードから精算金額を減算する処理を行う。 The settlement unit 34 performs settlement processing based on the tag information read by the reading unit 33. For example, the settlement unit 34 reads the price of the product corresponding to the identification information included in the tag information from the amount information R1 stored in the storage unit 36 in advance, and calculates the settlement amount. Next, the settlement unit 34 causes the storage unit 36 to store the settlement information D1 (operation information) including the calculated settlement amount. In the case where the settlement is performed using a prepaid card or the like, the settlement unit 34 performs a process of subtracting the settlement amount from the prepaid card.
表示部３５は、例えば、精算部３４により算出された精算金額の表示、精算処理が完了したことの表示などを行う。表示部３５は、例えば、ディスプレイである。記憶部３６は、例えば、精算情報Ｄ１、金額情報Ｒ１などを記憶する。 The display unit 35 displays, for example, the settlement amount calculated by the settlement unit 34 and the completion of the settlement process. The display unit 35 is a display, for example. The storage unit 36 stores, for example, settlement information D1, amount information R1, and the like.
＜１−４．決済サーバ＞
以下、決済サーバ５の機能構成について説明する。決済サーバ５は、ネットワークＮＷを介して、端末装置３から精算情報を収集し、精算金の決済処理を行う。さらに、決済サーバ５は、収集した精算情報に基づいて、社員食堂を利用した社員の集団判定を行う。決済サーバ５は、例えば、通信部５１と、収集部５２と、決済部５３と、集団判定部５４（算出部、判定部、送信部）と、表示制御部５５（画像生成部）と、表示部５６と、記憶部５７とを備える。通信部５１は、ネットワークＮＷを介して、端末装置３と通信する。通信部５１は、例えば、ＮＩＣ等の通信インターフェースを含む。
<1-4. Payment server>
Hereinafter, the functional configuration of the settlement server 5 will be described. The settlement server 5 collects settlement information from the terminal device 3 via the network NW, and performs settlement processing for settlement money. Further, the settlement server 5 makes a group determination of employees using the employee cafeteria based on the collected payment information. The settlement server 5 includes, for example, a communication unit 51, a collection unit 52, a settlement unit 53, a group determination unit 54 (calculation unit, determination unit, transmission unit), a display control unit 55 (image generation unit), a display A unit 56 and a storage unit 57. The communication unit 51 communicates with the terminal device 3 via the network NW. The communication unit 51 includes a communication interface such as a NIC, for example.
収集部５２は、通信部５１を介して、端末装置３から精算情報Ｄ１を収集して、記憶部５７に記憶させる。収集部５２は、例えば、所定の時間間隔、日次などの任意のタイミングで精算情報Ｄ１を収集する。すなわち、収集部５２は、複数の対象者が所定の動作を行った事実が時刻に対応付けられた動作情報を収集する。 The collection unit 52 collects the payment information D1 from the terminal device 3 via the communication unit 51 and stores it in the storage unit 57. The collection unit 52 collects the settlement information D1 at an arbitrary timing such as a predetermined time interval or daily. That is, the collection unit 52 collects operation information in which the fact that a plurality of subjects have performed a predetermined operation is associated with the time.
決済部５３は、記憶部５７に記憶された精算情報Ｄ１に基づいて、社員ごとの精算金を集計し、精算金の決済処理を行う。決済部５３は、決済情報Ｄ２を記憶部５７に記憶させる。決済処理が給与システム（不図示）と連携することで給与から精算金が自動的に減算されるようなシステムの場合、決済部５３は、通信部５１を介して、決済情報Ｄ２を給与システムに送信する。 The settlement unit 53 totals the settlement money for each employee based on the settlement information D1 stored in the storage unit 57, and performs settlement processing for the settlement money. The settlement unit 53 stores the settlement information D2 in the storage unit 57. In the case of a system in which the payment is automatically subtracted from the salary by cooperation with the salary system (not shown), the settlement unit 53 sends the settlement information D2 to the salary system via the communication unit 51. Send.
集団判定部５４は、記憶部５７に記憶された決済情報Ｄ２に基づいて、社員食堂を利用した社員の集団判定を行う。集団判定部５４は、決済情報Ｄ２に含まれる精算時刻に基づいて集団判定を行う。集団判定部５４は、例えば、社員ごとに、一緒飯を行った他社員を判定した判定情報（以下、一緒飯判定情報Ｄ３）を記憶部５７に記憶させる。 The group determination unit 54 performs group determination of employees using the employee cafeteria based on the settlement information D2 stored in the storage unit 57. The group determination unit 54 performs group determination based on the settlement time included in the settlement information D2. The group determination unit 54 stores, for example, determination information (hereinafter, combined rice determination information D <b> 3) that determines other employees who have cooked together for each employee in the storage unit 57.
表示制御部５５は、一緒飯判定情報Ｄ３に基づいて、社員同士の結び付きを視覚的に示すグラフィック画像などの集団判定情報Ｄ４を生成し、記憶部５７に記憶させる。また、表示制御部５５は、グラフィック画像を表示部５６に表示させる。 The display control unit 55 generates group determination information D4 such as a graphic image that visually indicates the connection between employees based on the together rice determination information D3 and stores the group determination information D4 in the storage unit 57. In addition, the display control unit 55 causes the display unit 56 to display a graphic image.
表示部５６は、例えば、決済サーバ５の運用担当者により閲覧される。表示部５６は、例えば、決済部５３による決済処理の結果などを表示する。また、表示部５６は、例えば、表示制御部５５により生成されたグラフィック画像を表示する。表示部５６は、例えば、ディスプレイである。記憶部５７は、例えば、精算情報Ｄ１、決済情報Ｄ２、一緒飯判定情報Ｄ３、集団判定情報Ｄ４などを記憶する。 The display unit 56 is viewed by, for example, a person in charge of the settlement server 5. The display unit 56 displays, for example, the result of the settlement process by the settlement unit 53. In addition, the display unit 56 displays a graphic image generated by the display control unit 55, for example. The display unit 56 is, for example, a display. The storage unit 57 stores, for example, settlement information D1, settlement information D2, together rice determination information D3, group determination information D4, and the like.
端末装置３の各機能部および決済サーバ５の各機能部は、ＣＰＵなどのプロセッサが、コンピュータのプログラムメモリなどに記憶されたプログラムを実行することで実現される。なお、これらの機能部は、プロセッサがプログラムを実行するのと同様の機能を有するＬＳＩ（Large Scale Integration）、ＡＳＩＣ（Application Specific Integrated Circuit）、およびＦＰＧＡ（Field-Programmable Gate Array）、ＧＰＵ（Graphics Processing Unit）などのハードウェアにより実現されてもよいし、ソフトウェアとハードウェアが協働することにより実現されてもよい。 Each functional unit of the terminal device 3 and each functional unit of the settlement server 5 are realized by a processor such as a CPU executing a program stored in a program memory or the like of a computer. Note that these functional units include an LSI (Large Scale Integration), an ASIC (Application Specific Integrated Circuit), an FPGA (Field-Programmable Gate Array), a GPU (Graphics Processing) that have the same functions as a processor executing a program. Unit), or may be realized by cooperation of software and hardware.
端末装置３の記憶部３６および決済サーバ５の記憶部５７は、例えば、ＲＡＭ（Random Access Memory）、ＲＯＭ（Read Only Memory）、ＨＤＤ（Hard Disk Drive）フラッシュメモリ、ＳＤカード、レジスタ、またはこれらのうち複数が組み合わされたハイブリッド型記憶装置などにより実現される。また、記憶部３６および記憶部５７の各々の一部または全部は、ＮＡＳ（Network Attached Storage）や外部のストレージサーバなど、端末装置３および決済サーバ５がアクセス可能な外部装置であってもよい。 The storage unit 36 of the terminal device 3 and the storage unit 57 of the settlement server 5 are, for example, a RAM (Random Access Memory), a ROM (Read Only Memory), a HDD (Hard Disk Drive) flash memory, an SD card, a register, or these This is realized by a hybrid storage device in which a plurality of them are combined. Further, a part or all of each of the storage unit 36 and the storage unit 57 may be an external device accessible by the terminal device 3 and the settlement server 5 such as a NAS (Network Attached Storage) or an external storage server.
＜１−５．端末装置による精算処理＞
以下において、端末装置３による精算処理について説明する。図４は、端末装置３による精算処理の流れの一例を示すフローチャートである。
<1-5. Checkout process by terminal device>
Below, the adjustment process by the terminal device 3 is demonstrated. FIG. 4 is a flowchart showing an example of the flow of the settlement process by the terminal device 3.
まず、端末装置３は、食事を終えた社員の操作に基づいて、例えば、ＩＣチップ内蔵の社員証に含まれる社員ＩＤなどの社員識別情報を読み取ることで、社員認証を行う（Ｓ１０１）。 First, the terminal device 3 performs employee authentication by reading employee identification information such as an employee ID included in an employee card with a built-in IC chip based on the operation of the employee who has finished the meal (S101).
次に、端末装置３は、社員の操作に基づいて端末装置３の所定の位置に設置された、例えばトレー上の各食器の裏側に設けられたタグの商品識別情報を読み取る（Ｓ１０３）。 Next, the terminal device 3 reads the product identification information of a tag provided at a predetermined position of the terminal device 3 based on the operation of the employee, for example, provided on the back side of each tableware on the tray (S103).
次に、端末装置３は、金額情報Ｒ１を参照し、読み取った商品識別情報と対応する金額を読み出して精算金額を算出する（Ｓ１０５）。図５は、実施形態に係る金額情報Ｒ１の一例を示す図である。金額情報Ｒ１は、商品識別情報としての商品ＩＤと、該商品ＩＤと対応する金額とを含む。金額情報Ｒ１は、例えば、カレーライスと対応する商品ＩＤ「Ｐ００１」の金額として「２８０円」を含んでいる。 Next, the terminal device 3 refers to the amount information R1, reads the amount corresponding to the read product identification information, and calculates the settlement amount (S105). FIG. 5 is a diagram illustrating an example of the money amount information R1 according to the embodiment. The amount information R1 includes a product ID as product identification information and an amount corresponding to the product ID. The amount information R1 includes, for example, “280 yen” as the amount of the product ID “P001” corresponding to the curry rice.
次に、端末装置３は、算出した精算金額を含む精算情報Ｄ１を記憶部３６に記憶させる（Ｓ１０７）。図６は、実施形態に係る精算情報Ｄ１の一例を示す図である。精算情報Ｄ１は、社員ＩＤと、精算日時と、精算金額と、購入商品１から３とを含む。精算情報Ｄ１は、例えば、社員ＩＤ「Ｕ１０１」である社員が、精算日時「２０１８／０３／０２／１２：５１：１０」に、購入商品１「Ｐ００１」の代金として精算金額「２８０円」の支払いを行った記録が含まれている。なお、精算情報Ｄ１は、４つ以上の商品の精算処理が行われた場合には、４つ目以降の購入商品の情報（購入商品４など）を含んでよい。また、プリペイドカードなどを用いて精算が行われる場合、端末装置３は、プリペイドカードから精算金額を減算する処理を行う。以上により、本フローチャートの処理を終了する。 Next, the terminal device 3 stores the settlement information D1 including the calculated settlement amount in the storage unit 36 (S107). FIG. 6 is a diagram illustrating an example of the settlement information D1 according to the embodiment. The settlement information D1 includes an employee ID, a settlement date, a settlement amount, and purchased products 1 to 3. The settlement information D1 is, for example, that the employee with the employee ID “U101” has the settlement amount “280 yen” as the price of the purchased product 1 “P001” on the settlement date “2018/03/02/12: 51: 10”. Contains records of payments made. Note that the settlement information D1 may include information on the fourth and subsequent purchased products (purchased products 4 and the like) when the settlement processing of four or more products is performed. Further, when the settlement is performed using a prepaid card or the like, the terminal device 3 performs a process of subtracting the settlement amount from the prepaid card. Thus, the process of this flowchart is completed.
＜１−６．決済サーバによる決済処理＞
以下において、決済サーバ５による決済処理について説明する。図７は、実施形態に係る決済サーバ５による決済処理の流れの一例を示すフローチャートである。決済サーバ５は、ネットワークＮＷを介して、端末装置３から精算情報Ｄ１を収集し（Ｓ２０１）、記憶部５７に記憶させる。
<1-6. Payment processing by payment server>
Below, the payment process by the payment server 5 is demonstrated. FIG. 7 is a flowchart illustrating an example of a flow of payment processing by the payment server 5 according to the embodiment. The settlement server 5 collects the settlement information D1 from the terminal device 3 via the network NW (S201) and stores it in the storage unit 57.
次に、決済サーバ５は、収集した精算情報Ｄ１に含まれる精算データを集計し（Ｓ２０３）、決済情報Ｄ２を生成して記憶部５７に記憶させる。図８は、実施形態に係る決済情報Ｄ２の一例を示す図である。図８に示される例は、複数の端末装置３（３−１〜３−８）から日次で収集された精算情報Ｄ１に含まれる精算データを社員ＩＤごとに集計したものである。この決済情報Ｄ２には、精算情報Ｄ１に含まれる項目に加えて、収集元の端末装置を示す「端末装置ＩＤ」が追加されている。例えば、図８に示される決済情報Ｄ２には、社員ＩＤ「Ｕ１０１」の社員が、精算日時「２０１８／０３／０２／１２：５１：１０」に、端末装置ＩＤ「３−１」で精算処理を行った記録が含まれている。 Next, the settlement server 5 totals the settlement data included in the collected settlement information D1 (S203), generates settlement information D2, and stores it in the storage unit 57. FIG. 8 is a diagram illustrating an example of the settlement information D2 according to the embodiment. In the example shown in FIG. 8, the settlement data included in the settlement information D1 collected daily from a plurality of terminal devices 3 (3-1 to 3-8) is tabulated for each employee ID. In addition to the items included in the settlement information D1, a “terminal device ID” indicating a collection source terminal device is added to the settlement information D2. For example, in the settlement information D2 shown in FIG. 8, the employee with the employee ID “U101” performs the settlement process with the terminal device ID “3-1” at the settlement date “2018/03/02/12: 51: 10”. The records made are included.
次に、決済サーバ５は、生成した決済情報Ｄ２に基づいて、社員ごとの精算金の決済処理を行う（Ｓ２０５）。決済処理が給与システム（不図示）と連携することで給与から精算金が自動的に減算されるようなシステムの場合、決済サーバ５は、ネットワークＮＷを介して、決済処理に関する情報を給与システムに送信する。以上により、本フローチャートの処理を終了する。 Next, the settlement server 5 performs settlement processing for the settlement money for each employee based on the generated settlement information D2 (S205). In the case of a system in which the settlement amount is automatically subtracted from the salary by cooperating with the salary system (not shown), the settlement server 5 sends information related to the settlement process to the salary system via the network NW. Send. Thus, the process of this flowchart is completed.
＜１−７．決済サーバによる集団判定処理＞
以下において、決済サーバ５による集団判定処理について説明する。図９は、実施形態に係る決済サーバ５による集団判定処理の流れの一例を示すフローチャートである。まず、決済サーバ５は、記憶部５７に記憶された決済情報Ｄ２の中から、集団判定の処理対象とする一人の社員の決済データを抽出する（Ｓ３０１）。
<1-7. Group determination processing by payment server>
Hereinafter, the group determination process by the settlement server 5 will be described. FIG. 9 is a flowchart illustrating an example of a flow of group determination processing by the settlement server 5 according to the embodiment. First, the payment server 5 extracts the payment data of one employee to be processed for group determination from the payment information D2 stored in the storage unit 57 (S301).
次に、決済サーバ５は、処理対象として抽出した社員の決済データに含まれる「精算日時」を基準として所定時間内に、同一グループに属する端末装置３によって精算処理を行った他社員を抽出する（Ｓ３０３）。図８に示される例において、処理対象として社員ＩＤ「Ｕ１０１」の社員を抽出した場合、精算日時「２０１８／０３／０２／１２：５１：１０」を基準として、例えば、６０秒以内、すなわち、この精算日時の前後３０秒以内に精算処理を行った他社員であって、且つ、社員ＩＤ「Ｕ１０１」の社員が精算を行った端末装置ＩＤ「３−１」と同じグループに属する端末装置３−１から３−４によって精算処理を行った他社員を抽出する。 Next, the settlement server 5 extracts other employees that have been settled by the terminal device 3 belonging to the same group within a predetermined time based on the “settlement date and time” included in the settlement data of the employee extracted as a processing target. (S303). In the example shown in FIG. 8, when an employee with the employee ID “U101” is extracted as a processing target, for example, within 60 seconds with reference to the settlement date “2018/03/02/12: 51: 10”, that is, The terminal device 3 that is another employee who has performed the settlement process within 30 seconds before and after the settlement date and belongs to the same group as the terminal device ID “3-1” for which the employee with the employee ID “U101” has settled -1 to 3-4 are used to extract other employees who have been processed.
図８に示される例において、社員ＩＤ「Ｕ１０２」の社員の精算日時「２０１８／０３／０２／１２：５１：１７」は、社員ＩＤ「Ｕ１０１」の社員の精算日時の後の３０秒以内含まれている。さらに、社員ＩＤ「Ｕ１０２」の社員が精算を行った端末装置ＩＤ「３−１」は、社員ＩＤ「Ｕ１０１」の社員が精算を行った端末装置と同じである。この場合、社員ＩＤ「Ｕ１０２」の社員は、上記の抽出条件を満たす。 In the example shown in FIG. 8, the settlement date “2018/03/02/12: 51: 17” of the employee with the employee ID “U102” is included within 30 seconds after the settlement date of the employee with the employee ID “U101”. It is. Furthermore, the terminal device ID “3-1” for which the employee with the employee ID “U102” has settled is the same as the terminal device with which the employee with the employee ID “U101” has settled. In this case, the employee with the employee ID “U102” satisfies the above extraction condition.
一方、社員ＩＤ「Ｕ１０３」の社員が精算処理を行った端末装置ＩＤ「３−７」が属する第２グループＧ２は、社員ＩＤ「Ｕ１０１」の社員が精算処理を行った端末装置ＩＤ「３−１」が属する第１グループＧ１とは異なる。このため、社員ＩＤ「Ｕ１０３」の端末装置ＩＤ「３−７」における精算処理は、上記の抽出条件を満たさない。また、社員ＩＤ「Ｕ１０５」の社員の精算日時「２０１８／０３／０２／１２：５２：５６」は、社員ＩＤ「Ｕ１０１」の社員の精算日時の前後３０秒以内に含まれていない。このため、社員ＩＤ「Ｕ１０５」の精算処理は、上記の抽出条件を満たさない。 On the other hand, the second group G2 to which the terminal device ID “3-7” for which the employee with the employee ID “U103” has performed the settlement processing belongs, has the terminal device ID “3-” for which the employee with the employee ID “U101” has performed the settlement processing. 1 ”to which the first group G1 belongs. For this reason, the payment process in the terminal device ID “3-7” of the employee ID “U103” does not satisfy the above extraction condition. Further, the settlement date “2018/03/02/12: 52: 56” of the employee with the employee ID “U105” is not included within 30 seconds before and after the settlement date of the employee with the employee ID “U101”. For this reason, the payment process for the employee ID “U105” does not satisfy the above extraction condition.
次に、決済サーバ５は、抽出した他社員を、処理対象の社員と一緒飯を行った社員と判定し、その回数（以下、「一緒飯回数」）を一緒飯判定情報Ｄ３として記憶部５７に記憶させる（Ｓ３０５）。一緒飯回数は、関連度の一例である。なお、決済サーバ５は、過去の集団判定処理により、既に一緒飯判定結果情報Ｄ３に一緒飯回数の登録がある場合には、その回数を１つ増大させる。図１０は、実施形態に係る一緒飯判定情報Ｄ３の一例を示す図である。図１０に示される例では、社員ＩＤ「Ｕ１０１」の社員が過去に一緒飯を行った他社員として、社員ＩＤ「Ｕ１０２」の社員が一緒飯回数「８回」として登録されている。 Next, the settlement server 5 determines the extracted other employee as an employee who has cooked together with the employee to be processed, and the number of times (hereinafter referred to as “the number of times to cook together”) as the together rice determination information D3. (S305). The number of meals is an example of the degree of association. Note that the settlement server 5 increments the number of times when the number of times of together rice is already registered in the together rice determination result information D3 by past group determination processing. FIG. 10 is a diagram illustrating an example of the combined rice determination information D3 according to the embodiment. In the example shown in FIG. 10, an employee with employee ID “U102” is registered as “8 times” with the employee ID “U102”.
次に、決済サーバ５は、一緒飯判定情報Ｄ３に含まれる他社員の一緒飯回数が所定回数以上（例えば、５回以上）であるか否かを判定する（Ｓ３０７）。決済サーバ５は、一緒飯回数が所定回数以上であると判定した場合、その他社員が、処理対象の社員と頻繁に一緒飯を行う集団に属すると判定する（Ｓ３０９）。一方、決済サーバ５は、一緒飯回数が所定回数未満であると判定した場合、その他社員が、処理対象の社員と頻繁に一緒飯を行う集団に属さないと判定する（Ｓ３１１）。このような回数の閾値を用いた判定を行うことで、集団判定処理の精度を向上させることができる。決済サーバ５は、判定結果として集団に属することを示す「集団」あるいは集団に属さないことを示す「非集団」を一緒飯判定情報Ｄ３に書き込む。 Next, the settlement server 5 determines whether or not the number of times that the other employees included in the combined rice determination information D3 is equal to or greater than a predetermined number (for example, 5 times or more) (S307). If the settlement server 5 determines that the number of combined meals is equal to or greater than the predetermined number of times, it determines that the other employees belong to a group that frequently cooks together with the employees to be processed (S309). On the other hand, when the settlement server 5 determines that the number of combined meals is less than the predetermined number, it determines that the other employees do not belong to a group that frequently cooks together with the employees to be processed (S311). By performing the determination using such a threshold value, the accuracy of the group determination process can be improved. The settlement server 5 writes “group” indicating that it belongs to the group or “non-group” indicating that it does not belong to the group as the determination result in the together rice determination information D3.
すなわち、決済サーバ５は、収集された動作情報に含まれる時刻が所定の範囲に含まれる所定の動作を行った対象者間の関連度が高くなるように、関連度を算出する。また、決済サーバ５は、対象者間において、動作情報に含まれる時刻が所定の範囲に含まれる頻度が高いほど関連度が高くなるように、関連度を算出する。また、決済サーバ５は、所定の動作は複数の場所で行われ、動作情報において、所定の動作を行った事実が、さらに複数の場所のいずれかに対応付けられており、動作情報に含まれる場所が同じであり、且つ、時刻が所定の範囲に含まれる所定の動作を行った対象者間の関連度が高くなるように、関連度を算出する。 That is, the settlement server 5 calculates the degree of association so that the degree of association between subjects who have performed a predetermined operation whose time included in the collected operation information is included in a predetermined range is high. Further, the settlement server 5 calculates the relevance degree so that the relevance degree increases as the frequency of the time included in the operation information included in the predetermined range increases among the target persons. Further, the settlement server 5 performs a predetermined operation at a plurality of locations, and the fact that the predetermined operation has been performed is further associated with one of the plurality of locations in the operation information, and is included in the operation information. The degree of association is calculated so that the degree of association between subjects who have performed a predetermined operation with the same place and time within a predetermined range is high.
次に、決済サーバ５は、処理対象とする全社員に対する集団判定処理が完了したか否かを判定する（Ｓ３１３）。決済サーバ５は、全社員に対する集団判定処理が完了していないと判定した場合、処置対象の社員を一人抽出し、Ｓ３０１以降の処理を繰り返す。 Next, the settlement server 5 determines whether or not the group determination process for all employees to be processed is completed (S313). If the settlement server 5 determines that the group determination process for all employees has not been completed, the settlement server 5 extracts one employee to be treated, and repeats the processes after S301.
一方、決済サーバ５は、全社員に対する集団判定処理が完了したと判定した場合、一緒飯判定情報Ｄ３に基づいて、集団判定情報Ｄ４として、社員同士の関連度を視覚的に示すグラフィック画像を生成する（Ｓ３１５）。図１１は、実施形態に係るグラフィック画像の一例を示す図である。図１１に示される例では、円である一つ一つが社員を示しており、円と円を結ぶ線が社員同士の関連度を示している。また、円の濃淡は、結び付きを有する他の円の数を示しており、すなわち、数多くの他社員と一緒飯を行った社員ほど濃い円で示されている。また、円と円を結ぶ線の太さが社員同士の関連度の高さを示しており、すなわち、一緒飯を行った回数が多い社員間ほど太い線で結合されている。 On the other hand, when the settlement server 5 determines that the group determination process for all employees has been completed, the settlement server 5 generates a graphic image that visually indicates the degree of association between the employees as the group determination information D4 based on the combined rice determination information D3. (S315). FIG. 11 is a diagram illustrating an example of a graphic image according to the embodiment. In the example illustrated in FIG. 11, each circle is an employee, and a line connecting the circles indicates the degree of association between employees. Further, the shade of the circle indicates the number of other circles that have a connection, that is, the employee who has cooked with many other employees has a darker circle. In addition, the thickness of the line connecting the circles indicates the degree of relevance between the employees, that is, the thicker lines are connected to the employees having more frequent meals.
例えば、円Ｆ２（社員Ｆ２）は、円Ｆ１（社員Ｆ１）よりも濃い円で示されている。これは、社員Ｆ２は、社員Ｆ１よりも一緒飯を行った他社員の数が多いことを示している。また、例えば、円Ｆ３（社員Ｆ３）と円Ｆ４（社員Ｆ４）とを結ぶ線Ｌ２は、円Ｆ１と円Ｆ２とを結ぶ線Ｌ１よりも太く示されている。これは、社員Ｆ３と社員Ｆ４とが一緒飯を行った回数は、社員Ｆ１と社員Ｆ２とが一緒飯を行った回数よりも多いことを示している。このようなグラフィック画像により、社員同士の関連度を視覚的に表現することができる。なお、グラフィック画像において社員は円で示される以外に、四角形、三角形など任意の図形で示されてもよい。 For example, the circle F2 (employee F2) is shown as a darker circle than the circle F1 (employee F1). This indicates that the employee F2 has a larger number of other employees who cooked together than the employee F1. Further, for example, a line L2 connecting the circle F3 (employee F3) and the circle F4 (employee F4) is shown thicker than the line L1 connecting the circle F1 and the circle F2. This indicates that the number of times that the employee F3 and the employee F4 cooked together is larger than the number of times that the employee F1 and the employee F2 cooked together. Such a graphic image can visually represent the degree of association between employees. In the graphic image, the employee may be indicated by an arbitrary figure such as a rectangle or a triangle in addition to the circle.
このようなグラフィック画像を生成することで、ある社員がどのような他社員と関連があり、すなわち、どのような集団に属しているのかを判断することができる。ある社員は、一つのみの集団に属していてもよいし、複数の集団に属していてもよい。 By generating such a graphic image, it is possible to determine what other employee is associated with, that is, what group the employee belongs to. A certain employee may belong to only one group, or may belong to a plurality of groups.
以上説明した第１実施形態の集団判定システム１によれば、社員間（対象者間）の関連度を簡便な手法で定量的に評価することが可能である。 According to the group determination system 1 of the first embodiment described above, the degree of association between employees (between subjects) can be quantitatively evaluated by a simple method.
なお、上記の実施形態においては、決済サーバ５が、精算情報Ｄ１を集計して、一緒飯判定情報Ｄ３、グラフィック画像などの集団判定情報Ｄ４を生成する例を説明した。しかしながら、端末装置３に精算情報Ｄ１の集計機能を持たせ、集計結果を端末装置３間で共有することで、一緒飯判定情報Ｄ３、グラフィック画像などの集団判定情報Ｄ４を端末装置３側で生成するようにしてもよい。 In the above-described embodiment, the example in which the settlement server 5 aggregates the settlement information D1 and generates the group determination information D4 such as the together rice determination information D3 and the graphic image has been described. However, the terminal device 3 has a function for counting the settlement information D1, and by sharing the tabulation result between the terminal devices 3, the group device determination information D4 such as the rice determination information D3 and the graphic image is generated on the terminal device 3 side. You may make it do.
なお、決済サーバ５は、一緒飯判定情報Ｄ３、集団判定情報Ｄ４（グラフィック画像など）を、社員の健康診断結果を管理する健康診断管理サーバ（不図示）に送信するようにしてもよい。一般的に、一人飯を行う社員は、麺類、カレーライスなどの短時間で食べ終えることが可能な商品を繰り返し選択し、また、野菜などのサイドメニューを選択する頻度が低いことが想定される。一方、一緒飯を行う社員は、他社員が選択した商品を参考にして、様々な商品を選択し、また、野菜などのサイドメニューなども選択することが想定される。このため、一緒飯判定情報Ｄ３および集団判定情報Ｄ４と、健康診断の結果とを結び付けることで、例えば、一人飯を行うことで食生活に偏りが生じて健康を損なう兆候が見られる社員には、健康によい食品を推薦することや、一緒飯を推奨することができる。 The settlement server 5 may transmit the combined rice determination information D3 and the group determination information D4 (graphic image or the like) to a health diagnosis management server (not shown) that manages the employee's health check result. In general, it is assumed that employees who eat rice repeatedly select products that can be eaten in a short time, such as noodles and curry rice, and select side menus such as vegetables. . On the other hand, it is assumed that employees who cook together choose various products with reference to products selected by other employees, and also select side menus such as vegetables. For this reason, by linking together rice determination information D3 and group determination information D4 with the results of a health checkup, for example, for employees who have a sign of eating habits that are biased in eating habits due to serving alone Can recommend healthy foods and recommend rice together.
なお、決済サーバ５は、生成した一緒飯判定情報Ｄ３、集団判定情報Ｄ４などを、会社組織における管理者により利用される端末装置（不図示）に送信するようにしてもよい。一緒飯を行う社員は、様々な部署の社員と食事をする機会があり、仕事面にも良い影響が生じることが期待される。例えば、管理者は、一緒飯判定情報Ｄ３および集団判定情報Ｄ４を参照することで、自身の部下が様々な部署の社員と食事をするように働きかけることができる。 The settlement server 5 may transmit the generated together rice determination information D3, group determination information D4, and the like to a terminal device (not shown) used by an administrator in the company organization. Employees who eat together have the opportunity to eat with employees from various departments, which is expected to have a positive impact on work. For example, the administrator can encourage his / her subordinates to eat with employees in various departments by referring to the together rice determination information D3 and the group determination information D4.
また、決済サーバ５は、生成した一緒飯判定情報Ｄ３、集団判定情報Ｄ４などを、各社員により利用される端末装置（不図示）に送信するようにしてもよい。社員は、一緒飯判定情報Ｄ３および集団判定情報Ｄ４を参照することで、自分を中心とした他社員との関係を把握することができる。 The settlement server 5 may transmit the generated together rice determination information D3, group determination information D4, and the like to a terminal device (not shown) used by each employee. The employee can grasp the relationship with other employees centered on himself / herself by referring to the together rice determination information D3 and the group determination information D4.
なお、上記の実施形態においては、社員食堂において食後に精算処理を行う例について説明したが、食前に精算処理を行う場合にも同様な仕組みを適用することができる。 In the above-described embodiment, an example in which the checkout process is performed after meals in the employee cafeteria has been described. However, a similar mechanism can be applied when the checkout process is performed before meals.
以上説明したように、実施形態の決済サーバ５は、複数の対象者が所定の動作を行った事実が時刻に対応付けられた動作情報を収集する収集部５２と、前記収集部５２によって収集された前記動作情報に含まれる時刻が所定の範囲に含まれる前記所定の動作を行った前記対象者間の関連度が高くなるように、前記関連度を算出する集団判定部５４とを備える。これによって、複数の対象者間の関連度を簡便な手法で定量的に評価することが可能である。 As described above, the settlement server 5 according to the embodiment is collected by the collection unit 52 that collects operation information in which the fact that a plurality of subjects have performed a predetermined operation is associated with time, and the collection unit 52 collects the operation information. And a group determination unit 54 that calculates the relevance level so that the relevance level between the subjects who have performed the predetermined motion whose time included in the motion information is included in a predetermined range is increased. Thereby, it is possible to quantitatively evaluate the degree of association between a plurality of subjects by a simple method.
以上、本発明を実施するための形態について実施形態を用いて説明したが、本発明はこうした実施形態に何など限定されるものではなく、本発明の要旨を逸脱しない範囲内において種々の変形及び置換を加えることができる。 As mentioned above, although the form for implementing this invention was demonstrated using embodiment, this invention is not limited to such embodiment at all, In the range which does not deviate from the summary of this invention, various deformation | transformation and Substitutions can be added.
１…集団判定システム
３、３−１、３−２、３−３、３−４、３−５、３−６、３−７、３−８…端末装置
３１…通信部
３２…認証部
３３…読取部
３４…精算部
３５…表示部
３６…記憶部
５…決済サーバ
５１…通信部
５２…収集部
５３…決済部
５４…集団判定部
５５…表示制御部
５６…表示部
５７…記憶部
DESCRIPTION OF SYMBOLS 1 ... Group determination system 3, 3-1, 3-2, 3-3, 3-4, 3-5, 3-6, 3-7, 3-8 ... Terminal device 31 ... Communication part 32 ... Authentication part 33 ... Reading unit 34 ... Settlement unit 35 ... Display unit 36 ... Storage unit 5 ... Payment server 51 ... Communication unit 52 ... Collecting unit 53 ... Payment unit 54 ... Group determination unit 55 ... Display control unit 56 ... Display unit 57 ... Storage unit
Claims (10)
前記収集部によって収集された前記動作情報に含まれる時刻が所定の範囲に含まれる前記所定の動作を行った前記対象者間の関連度が高くなるように、前記関連度を算出する算出部と
を備える、情報処理装置。 A collection unit that collects operation information associated with a time when a plurality of subjects perform a predetermined operation; and
A calculating unit that calculates the relevance level so that the relevance level between the subjects who have performed the predetermined motion whose time included in the motion information collected by the collecting unit is included in a predetermined range; An information processing apparatus comprising:
請求項１に記載の情報処理装置。 The calculation unit calculates the relevance degree so that the relevance degree is higher as the frequency that the time included in the motion information is included in a predetermined range is higher among the target persons.
The information processing apparatus according to claim 1.
前記動作情報において、前記所定の動作を行った事実が、さらに前記複数の場所のいずれかに対応付けられており、
前記算出部は、前記動作情報に含まれる前記場所が同じであり、且つ、前記時刻が所定の範囲に含まれる前記所定の動作を行った対象者間の前記関連度が高くなるように、前記関連度を算出する、
請求項１または２に記載の情報処理装置。 The predetermined operation is performed in a plurality of locations,
In the operation information, the fact that the predetermined operation has been performed is further associated with one of the plurality of locations,
The calculation unit is configured so that the relevance level between subjects who have performed the predetermined operation in which the location included in the operation information is the same and the time is included in a predetermined range is high. Calculate relevance,
The information processing apparatus according to claim 1 or 2.
請求項１から３のいずれか一項に記載の情報処理装置。 The target person is indicated by a figure, and the degree of association between the target persons calculated by the calculation unit is indicated by a line connecting the figures, and the figure is darker as the number of the other connected figures increases. The line further includes an image generation unit that generates an image that is thicker as the relevance between the subjects is higher.
The information processing apparatus according to any one of claims 1 to 3.
前記所定の動作は、前記会社に設けられた社員食堂における商品の精算であり、
前記算出部は、前記商品の精算時刻に基づいて、前記複数の社員間の関連度を算出する、
請求項１から４のいずれか一項に記載の情報処理装置。 The plurality of target persons are a plurality of employees belonging to a company,
The predetermined operation is a checkout of products in an employee cafeteria provided in the company,
The calculation unit calculates the degree of association between the plurality of employees based on the settlement time of the product.
The information processing apparatus according to any one of claims 1 to 4.
請求項５に記載の情報処理装置。 The calculation unit calculates the relevance degree so that the relevance degree between employees whose terminal devices where the settlement is performed is the same and the settlement time is included in a predetermined range is high. ,
The information processing apparatus according to claim 5.
請求項５または６に記載の情報処理装置。 The installation location of the terminal device that performed the payment is the same, and further includes a determination unit that determines that the employee whose payment time is included in a predetermined range is an employee belonging to the same group,
The information processing apparatus according to claim 5 or 6.
請求項１から７のいずれか一項に記載の情報処理装置。 A transmission unit that transmits the relevance calculated by the calculation unit to the outside;
The information processing apparatus according to any one of claims 1 to 7.
複数の対象者が所定の動作を行った事実が時刻に対応付けられた動作情報を収集し、
収集された前記動作情報に含まれる時刻が所定の範囲に含まれる前記所定の動作を行った前記対象者間の関連度が高くなるように、前記関連度を算出する、情報処理方法。 Computer
Collecting action information associated with the time when the fact that multiple subjects performed a given action,
An information processing method for calculating the relevance level so that the relevance level between the subjects who have performed the predetermined motion whose time included in the collected motion information is within a predetermined range is high.
複数の対象者が所定の動作を行った事実が時刻に対応付けられた動作情報を収集させ、
収集された前記動作情報に含まれる時刻が所定の範囲に含まれる前記所定の動作を行った前記対象者間の関連度が高くなるように、前記関連度を算出させる、プログラム。 On the computer,
The fact that a plurality of subjects performed a predetermined action causes action information associated with the time to be collected,
The program which calculates the said relevance degree so that the relevance degree between the said subjects who performed the said predetermined | prescribed operation | movement in which the time contained in the collected said operation | movement information is contained in a predetermined | prescribed range becomes high.
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| JPWO2022138918A1 (en) * | 2020-12-25 | 2022-06-30 | ||
| JP7311058B2 (en) | 2020-12-25 | 2023-07-19 | 日本電気株式会社 | Payment system, method and recording medium |
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