JP2009025922A - Information processing unit and information processing method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To enable easy generation of a search condition for searching a plurality of electronic data for particular electronic data. <P>SOLUTION: An information processing unit includes a classification means for classifying a plurality of data stored in a storage device under a predetermined classification condition; a first display means (601) for displaying the classification condition; when the classification condition displayed by the first display means (601) is selected and indicated, a selection means for selecting information related to the data to be classified under the above classification condition indicated from among the plurality of data stored in the storage device; a second display means (602) for displaying information related to the selected data; when a predetermined indication (603) is input, a generation means for generating the search condition to obtain, as a search result, the data of which information is displayed by the second display means (602), based on the above classification condition. <P>COPYRIGHT: (C)2009,JPO&INPIT

Description

  The present invention relates to an information processing technique for generating a search condition for searching for specific electronic data from a plurality of electronic data.

  In recent years, devices capable of generating electronic data, such as personal computers, digital still cameras, and digital video cameras, have become widespread. In addition, the interoperability between multiple devices via the network has also improved, and the development of e-mail and high-speed Internet / intranet as distribution channels for distributing the generated electronic data is also underway. . Furthermore, the capacity of storage devices for storing such electronic data is being increased.

  As a result, an enormous and diverse variety of electronic data has been accumulated in the storage device. Such enlargement and diversification of electronic data make it more difficult for users to organize and manage electronic data.

  In the state where there is little electronic data as in the past, it was not so difficult for users to systematically manage electronic data. However, as the electronic data to be managed increases as in recent years, the electronic data management system Becomes complicated and cumbersome.

  For example, when a user creates a folder and manages electronic data, generally, as the electronic data increases, the folder system becomes complicated and the number of folder hierarchies increases.

  Under such circumstances, each time new electronic data is registered, the user should decide which folder should contain the electronic data, or whether a new folder should be created. I have to make a decision. Furthermore, if the judgment at that time is inconsistent, after registering electronic data in a folder, even if an attempt is made to use the electronic data, there is a problem that it is not known in which folder the electronic data is registered.

  For this reason, recently, as a technique for facilitating access to electronic data, a technique for retrieving electronic data has become familiar. As a result, even if the user does not know in which folder the electronic data is registered, the user can obtain a plurality of electronic data (a set of electronic data) that matches the search conditions simply by giving appropriate search conditions. Can do.

  However, when trying to obtain a set of electronic data by inputting search conditions, the work load for finding the search conditions for obtaining desired electronic data depends on the user's skill and restrictions on the UI of the device. There is a problem that is large.

  Therefore, a technique called “search folder” has been proposed in order to reduce the workload at the time of inputting the search condition as much as possible. In the search folder, when a search condition is set in the folder, the search can be performed with the set search condition each time the folder is opened.

  However, even when using a search folder, the user is not freed from the work of “thinking” and “entering” the search condition, so depending on the user's skill and restrictions on the UI of the device Still, there remains work to find the appropriate search criteria.

On the other hand, as a technique for facilitating input of search conditions, for example, the following Patent Document 1 has been proposed. According to this document, by displaying icons representing information necessary for generating search conditions such as keywords and logical operators (AND, OR) on the screen, it is possible to input search conditions simply by moving the icons. Will be able to.
Japanese Patent Laid-Open No. 11-45271

  However, in the case of the method described in Patent Document 1, it is assumed that the user performs a moving operation while imagining the search condition. For this reason, in order to obtain a desired set of electronic data, the user must imagine the items (search items) set as search conditions and their values (search attributes).

  Furthermore, in the case of the method described in Patent Document 1, when a search is performed by combining these search conditions, the user is required to have a skill that can be considered as to what kind of electronic data set can be obtained. On the other hand, it is easy for users who lack such skills or who are not used to generating search conditions to imagine what kind of electronic data sets can be obtained from the search conditions that they entered. is not.

  The present invention has been made in view of the above problems, and an object of the present invention is to easily generate a search condition for searching for specific electronic data from a plurality of electronic data.

In order to achieve the above object, an information processing apparatus according to the present invention comprises the following arrangement. That is,
Classification means for classifying a plurality of data stored in the storage device according to a predetermined classification condition;
First display means for displaying the classification condition;
Information related to data classified by the selected classification condition among a plurality of data stored in the storage device when any of the classification conditions displayed by the first display means is selected. A selection means for selecting
Second display means for displaying information relating to the data selected by the selection means;
When a predetermined instruction is input, a search condition for causing the data on which the information is displayed by the second display means to be acquired as a search result is selected as the selected classification condition. And generating means for generating based on the above.

  According to the present invention, it is possible to easily generate a search condition for searching for specific electronic data from a plurality of electronic data.

  Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.

[First Embodiment]
1. Hardware Configuration of Information Processing Device FIG. 1 is a diagram showing a hardware configuration of an information processing device (100) according to the first embodiment of the present invention.

  In the figure, reference numeral 101 denotes an input device for a user to perform an input operation such as a selection instruction. The input device 101 here includes a keyboard, a numeric keypad, a pointing device, a microphone, and the like.

  Reference numeral 102 denotes a ROM that stores a control program and parameters for realizing the information processing method according to the present embodiment.

  Reference numeral 103 denotes a storage device that can store data used when the control program is executed. The storage device here includes a hard disk, a memory card, an optical disk, a magnetic or optical card, an IC card, a memory card, and the like.

  Reference numeral 104 denotes a work RAM when the control program is executed. Reference numeral 105 denotes a CPU that executes the control program. Reference numeral 106 denotes an output device such as a display for outputting the execution result of the program in the CPU 105. A bus 107 connects the units 101 to 106 constituting the information processing apparatus 100 to exchange data.

2. Functional Configuration of Information Processing Device FIG. 2 is a block diagram showing the functional configuration of the information processing device 100. As shown in the figure, in the information processing apparatus 100, a data storage function, a classification / display function, and a search condition generation function are realized by executing the control program.

  The data storage function is a function of storing, in the storage device 103, data used when executing the control program (that is, processing target) and processing results obtained by processing the data.

  The classification / display function classifies data stored in the storage device 103 according to a predetermined classification condition (classification rule), displays the classification rule on the output device 106, and uses the classification rule selected and designated by the user. This function displays a list of data to be classified.

  The classification rule includes, for example, an item (classification item) “XXX” used for classification and a condition attribute (classification attribute) “ "" Means a conditional expression (or conditional statement) in which "" is defined. Data classified according to the classification rule is called a classification result.

  The search condition generation function is a function for generating a search condition to be set in the search folder when the user selects and instructs the classification rule displayed by the classification / display function. The search folder is a folder for searching for data satisfying a predetermined search condition from a plurality of data, and a search condition used for the search is set.

  When the user instructs to select a predetermined classification rule, a search condition is generated so that data classified by the classification rule is output as a search result when the search folder is executed. The generated search condition is set in the.

2.1 Data storage function First, the data storage function is explained. A data storage unit 208 stores data to be processed, search conditions managed by a search condition management unit 207 described later, and the like in the storage device 103.

  Here, the data to be processed includes a data body and metadata. The metadata is auxiliary information of the data body, and includes information such as the creation date / time, type, title, and subject of the data body.

  The metadata generally includes items (metadata items) such as creation date / time, type, title, and subject, and values (metadata values) set for the metadata items. For example, metadata values set in the metadata item “subject” include “eldest daughter”, “second daughter”, “mother”, “father”, and the like.

The data storage unit 208 stores the metadata in the storage device 103 for each data with the following configuration.
Metadata item 1 = metadata value 1
Metadata item 2 = metadata value 2,
...
Metadata item n = metadata value n
For this reason, for example, in the case of still image data, the configuration is specifically as follows.
-Creation date = 2003/10/10,
・ Event name = sports day,
・ Title = Sports Day 2003
・ Subject = eldest daughter
・ Item type = still image,
・ File type = JPEG,
・ Position information (Eastern longitude) = 35 ° 35'112 "
・ Position information (north latitude) = 139 ° 37'18 ”
However, the configuration of the metadata stored in the storage device 103 is not limited to this, and any configuration may be used as long as the data body, the metadata item, and the metadata value are associated with each other.

2.2 Classification / Display Function Next, the classification / display function will be described.

(1) Classification Unit In FIG. 2, 201 is a classification unit that classifies a set of data stored in the storage device 103 by the data storage unit 208 into one or more groups according to a preset classification rule. .

  The classification unit 201 can classify data for each metadata value for a specific metadata item (that is, classify data according to a classification rule in which the metadata item is a classification item and the metadata value itself is a classification attribute). be able to).

  FIG. 3 is a diagram illustrating an example of a classification rule when the metadata item “subject” is used as a classification item when classifying a set of data stored in the storage device 103 by the data storage unit 208. . As shown in FIG. 3, the metadata included in the data stored in the storage device 103 by the data storage unit 208 includes metadata items whose metadata items are “subject” as “first daughter”, “second daughter”, “ There are four types of metadata values, “Mother” and “Father”.

  Therefore, the four types of metadata values can be used as the classification attributes. As a result, the classification unit 201 classifies the data stored in the storage device 103 by the data storage unit 208 into four groups. Can do.

  The first group is a group of data classified as “subject = first daughter” (data in which “first daughter” is set as the metadata value of the metadata item “subject”). The second group is a group of data classified as “subject = second daughter” (data in which “second daughter” is set as the metadata value of the metadata item “subject”). The third group is a group of data classified as “subject = mother” as a classification rule (data in which “mother” is set as the metadata value of the metadata item “subject”). The fourth group is a group of data (data in which “father” is set as a metadata value of the metadata item “subject”) classified as “subject = father” as a classification rule.

  Note that the classification attribute used as the classification rule in classification by the classification unit 201 is not limited to the metadata value itself as shown in FIG. 3, and for example, a range of metadata values may be used.

  In FIG. 4, when classifying a set of data stored in the storage device 103 by the data storage unit 208, the metadata item “photographed year” is used as the classification item, and the range of the metadata value is set as the classification attribute. It is a figure which shows an example of the classification rule at the time of using.

  In the classification rule of FIG. 4, data stored in the storage device 103 by the data storage unit 208 is divided into a data group whose shooting year is before 2001, a data group whose data is 2002, and a data group whose data is after 2003. Can be classified.

  Furthermore, when using a range of metadata values as a classification attribute in the classification rule of the classification unit 201, an indirect range may be used.

  In FIG. 5, when classifying a set of data stored in the storage device 103 by the data storage unit 208, the metadata item “shooting location” is used as the classification item, and the range of the metadata value is set as the classification attribute. It is a figure which shows another example of the classification rule at the time of using.

  In the example of FIG. 5, the range of metadata values is from “north latitude x1 ° y1′z1” degrees to north latitude X1 ° Y1′Z1 ”degrees, east longitude a1 ° b1′c1” degrees to east longitude A1 ° B1′C1. It is defined as “degree”.

  At this time, for example, by using a range of latitude and longitude representing each prefecture as a range of metadata values, a set of data stored in the storage device 103 by the data storage unit 208 can be obtained for each of the data captured. It can be classified by prefecture. In other words, when the shooting locations of data are classified for each prefecture, the name of each prefecture is not directly used as a classification attribute, but is indirectly expressed using a range of latitude and longitude.

  Furthermore, the classification rules used in the classification by the classification unit 201 are not limited to those using a specific notation such as a metadata item or a metadata value, and may use another notation. Other notations include, for example, methods such as document classification and image classification in which information included in the data body is analyzed and classified using the information.

  Specifically, as a document classification, a topic such as “topic about a certain product A” is classified, and “a positive opinion about product A is written” or “a negative opinion is written”. Information based on the analysis result is set as a classification attribute. A classification rule composed of these classification items and classification attributes may be used.

(2) Classification Result Selection Input / Output Unit In FIG. 2, 202 is a classification result selection input / output unit. The classification result selection input / output unit 202 displays the classification rules used for classification by the classification unit 201 on the output device 106 in a format in which a selection instruction can be input (functions as a first display unit). In addition, an input of a selection instruction for the classification rule input via the input device 101 is accepted.

  FIG. 6 is a diagram illustrating an example of a display window on the output device 106 on which the classification rule is displayed by the classification result selection input / output unit 202. As shown in FIG. 6, the display window 600 includes a left column 601 and a right column 602, and classification rules are displayed in the left column 601.

  The classification rules displayed in the left column 601 display classification items and classification attributes in a hierarchical structure, and here a tree display is adopted. “■” displayed in the left column 601 is one classification item or classification attribute. When one classification item includes a plurality of classification attributes, a plurality of classification attributes are branched into the one classification item. Connected.

  Further, a single category attribute is connected with a branch of a category item other than the category item including the category attribute.

  Further, the classification result selection input / output unit 202 not only displays the classification rule on the display window 600 but also receives an instruction for selecting the classification rule used for generating the search condition via the display window 600.

  Among the classification attributes displayed in the left column 601, the classification attribute represented by “□” indicates that a classification rule including the classification attribute has been selected. In the case of FIG. 6, since “video” and “second daughter” are selected as classification attributes, two classification rules of “item type = video” and “subject = second daughter” are selected. That is, it indicates that a plurality of selection instructions have been issued.

  In the example of FIG. 6, the classification rules are displayed in a hierarchical structure, but the classification rule display method by the classification result selection input / output unit 202 is not limited to this. For example, a display in which the classification results classified by all the classification rules are expanded, or a display in which only certain fixed classification rules are expanded may be used.

(3) Classification result selection information management unit 209 is a classification result selection information management unit that manages which classification rule is instructed to be selected by the classification result selection input / output unit 202.

(4) Extraction Result Calculation Unit 203 is an extraction result calculation unit. The extraction result calculation unit 203 acquires information on the data (classification result) managed by the classification result selection information management unit 209. When a plurality of classification rules are instructed to be selected in the classification result selection input / output unit 202, the extraction result calculation unit 203 acquires information on data (classification result) classified by each classification rule. The Rukoto.

  The extraction result calculation unit 203 further narrows down the data by calculating a logical product of the information related to the plurality of acquired classification results. Specifically, since the information related to the classification result includes an identifier unique to each data, the data is narrowed down by calculating a logical product using the identifier.

(5) Extraction result output unit 204 is an extraction result output unit. The extraction result output unit 204 displays information on the classification result narrowed down by the extraction result calculation unit 203 on the output device 106 (functions as a second display unit). Thereby, the user can see a list of data classified by the classification rule instructed to be selected as a classification result.

  FIG. 7 is a diagram illustrating a state where the classification result classified according to the classification rule instructed by the user is displayed in the right column 602 of the display window 600. As described above, among the classification attributes displayed in the left column 601, a classification rule including a classification attribute represented by “□” is selected and instructed.

  Specifically, there is a classification rule in which the metadata item is “item type”, the metadata value is “video”, the metadata item is “subject”, and the metadata value is “second daughter”. Selection is instructed. Therefore, data obtained by ANDing the data classified by the classification rule of “item type = video” and the data classified by the classification rule of “subject = second daughter” is displayed in the right column 602 as the classification result. The Rukoto.

2.3 Search Condition Generation Function Next, the search condition generation function will be described.

(1) Search condition generation instruction receiving unit 205 is a search condition generation instruction receiving unit. The search condition generation instruction receiving unit 205 receives an input (603 in FIG. 6) for instructing generation of a search condition via the input device 101. Note that the instruction in this case is not limited to the search condition generation instruction, but may be any instruction that can recall the generation of the search condition to be set in the search folder. For example, a search folder generation instruction may be used.

(2) Search condition generation unit 206 is a search condition generation unit. In the search condition generation unit 206, when the search condition generation instruction reception unit 205 receives a search condition generation instruction (603 in FIG. 6), the classification result currently selected by the classification result selection information management unit 209 is designated. Get information about classification results classified by rules. Further, a classification rule for obtaining the acquired classification result is acquired. Then, by combining the acquired classification rules, a search condition for searching the data set that has been narrowed down by the extraction result calculation unit 203 is generated.

  In the present embodiment, the extraction result calculation unit 203 narrows down the data by performing a logical product on the information on the classification result classified by the classification rule instructed to be selected. Therefore, the search condition generation unit 206 generates a combination of classification rules instructed for selection as a search condition.

(3) Search condition management unit 207 is a search condition management unit. The search condition management unit 207 manages the search conditions generated by the search condition generation unit 206. In this embodiment, the search condition is managed as a search condition of “search folder”.

3. Process flow in information processing equipment (classification / display processing)
Next, the flow of classification / display processing in the information processing apparatus 100 will be described with reference to the flowchart of FIG.

  First, in step S801, the classification unit 201 performs a classification process on the data stored in the storage device 103 by the data storage unit 208 according to the classification rule, and acquires each classification result.

  In step S802, the classification rule used in the classification process in step S801 is displayed on the output device 106 in a form in which the classification result selection input / output unit 202 can select instructions.

  In step S803, the classification result selection input / output unit 202 monitors a classification rule selection instruction input. If a classification rule selection instruction is received, the process proceeds to step S804. When the selection instruction input is not received, the classification result selection input / output unit 202 continues to monitor the selection instruction input.

  In step S804, the management target in the classification result selection information management unit 209 is updated according to the selection instruction input received in step S803.

  In step S805, the extraction result calculation unit 203 acquires information related to the classification result classified by the selected classification rule updated in step S804 from the classification result selection information management unit 209, and calculates a narrowed data set. In the present embodiment, a narrowed-down data set is calculated by taking the logical product of information related to the classification results classified by the selected classification rule.

  In step S806, the data set calculated in step S805 is displayed on the output device 106.

  The classification / display processing is continued until a search condition generation instruction is input by the user, and the processing ends when a search condition generation instruction is input.

  An embodiment of the processing according to the flowchart of FIG. 8 will be described with reference to FIGS. In the case of FIG. 6, by performing an operation of tracing the tree in the left column 601, the narrowed data as in the right column 602 in FIG. 7 is displayed.

  However, the display form is not limited to this. For example, in 601, the internal data structure is held in such a tree structure, while the display by the output device 106 may take another display form.

  For example, as shown in FIG. 9, when the classification result is held in a tree structure as an internal data structure (902), a display (901) for arranging two classification rules that can be selected on a plane is displayed. You may make it. Also for the right column 602, it is sufficient if a list of narrowed data can be grasped, and for example, thumbnail display may be used.

4). Process flow in information processing device (search condition generation process)
Next, the flow of search condition generation processing in the information processing apparatus 100 will be described using the flowchart of FIG.

  In the flowchart shown in FIG. 10, the processing is executed on the assumption that the output of the data set (602) in step S806 in FIG. 8 has been completed.

  First, in step S1001, the search condition generation instruction receiving unit 205 monitors the input of a search condition generation instruction, and when receiving the generation instruction input, the process proceeds to step S1002. On the other hand, when the generation instruction input is not received, the generation instruction input is continuously monitored.

  In this embodiment, the search condition generation instruction is input by operating the search condition setting instruction button (603) displayed on the display via a mouse or the like. However, the search condition generation instruction method is not limited to this, and it may be a selection instruction from a menu called by a mouse operation or an input instruction by a keyboard or voice.

  In step S <b> 1002, the search condition generation unit 206 recognizes the classification rule that is instructed to be selected when the search condition generation instruction is received by referring to the classification result selection information management unit 209.

  In step S1003, the search condition generation unit 206 acquires the classification rules acquired in step S1002.

  In step S1004, the search condition generation unit 206 generates a search condition to be set in the search folder from each classification rule acquired in step S1003. In the present embodiment, a search condition is generated by combining selected classification rules with a logical product. The search condition only needs to be a condition that allows search processing when the search folder is accessed, and does not need to be expressed by a notation like a general conditional expression.

  In step S1005, the search condition management unit 207 manages the search condition generated in step S1004 as a search condition for the search folder.

  As is apparent from the above description, in the information processing apparatus according to the present embodiment, when generating a search condition, first, means for classifying data using a predetermined classification rule is provided. And it was set as the structure which displays the said classification rule (a classification item and a classification attribute) used for the classification of the data by the said means to a user. Further, the user can select and display the displayed classification rule, and the search condition can be generated.

  As a result, the user can generate search conditions while looking at the displayed classification rules (classification items and classification attributes), and the user can imagine the items and their values that are set as search conditions as in the past. The convenience of the user has been improved.

  Further, the information processing apparatus according to the present embodiment is configured to display data classified according to the classification rule when the user instructs to select the classification rule.

  As a result, the user can imagine what kind of data set can be obtained according to the generated search condition.

  As a result, it is possible to easily generate a search condition for searching for specific data from a plurality of data.

[Second Embodiment]
In the first embodiment, the classification result selection input / output unit 202 selects and instructs one classification attribute for each classification item. However, the present invention is not limited to this. That is, the classification result selection input / output unit 202 may be configured to receive input of a plurality of classification attribute selection instructions for each classification item. In this case, the extraction result calculation unit 203 performs a logical sum for data classified by the respective classification rules obtained by different classification attributes of the same classification item.

  FIG. 11 shows a display example when the classification rule is selected and designated in this way. According to this example, first, a data set classified according to the classification rule of “item type = moving image” and “subject = second daughter” or “subject = elder daughter” is acquired. Further, a data set classified according to the classification rule of “item type = still image” and “subject = second daughter” or “subject = elder daughter” is acquired. A data set obtained by ORing these data sets is displayed.

  Note that, as shown in FIG. 11, it may be possible to distinguish whether or not the classification attribute instructed to be selected is checked.

[Third Embodiment]
In each of the above embodiments, the classification result selection input / output unit 202 is configured to receive only a selection instruction. However, the present invention is not limited to this, so that a non-selection instruction can be received (that is, a selection instruction is issued). It may be configured to be releasable.

  In addition, when the classification rules have a hierarchical configuration, when the higher-level selection instruction state is canceled, the classification rules below the released classification rule are configured to be in a non-selection instruction state. Also good.

  It is assumed that the non-selection instruction method is configured to be performed via a mouse or the like, similar to the selection instruction method. Alternatively, a button for accepting a “return” instruction that cancels the process in the reverse order of the selection instruction may be provided, and the operation may be performed via the button.

[Fourth Embodiment]
In each of the above embodiments, the classification unit 201 performs the classification process on the data to be processed, and implements the data narrowing down by taking the logical product of the data sets obtained from the respective classification rules. However, the data narrowing method is not limited to this, and any method may be used as long as an equivalent data set can be obtained.

  For example, it is assumed that the classification result “a” is obtained as a result of classifying data whose metadata value of the item “item type” is “moving image” according to the classification rule A (first classification condition). Further, it is assumed that the classification result B is obtained as a result of classifying data whose metadata value of the subject “subject” is “elder daughter” by the classification rule B (second classification condition).

  In each of the above-described embodiments, by performing a logical product of the respective data sets obtained from the classification result a and the classification result b, the classification is performed according to the classification rule that “the item type is a moving image and the subject is the eldest daughter”. The data set to be obtained is obtained.

  However, the method for obtaining such a data set is not limited to this. For example, a data set obtained from the classification result “a” of the classification rule A, that is, a data set classified according to the classification rule “item type is moving image” may be used as the input of the classification rule B. Thereby, as a data set obtained from the classification result b of the classification rule B, it is possible to obtain a data set classified according to the classification rule that “the item type is a moving image and the subject is the eldest daughter”.

  In this way, the data collection obtained as a result of classification according to a certain classification rule and the logical operation result between these data sets are targeted for processing by another classification rule, so that the data can be narrowed down. It doesn't matter.

[Fifth Embodiment]
In each of the above embodiments, a case has been described in which the search condition generation instruction receiving unit 205 receives a generation instruction from a user and starts generating search conditions triggered by the generation instruction. However, the present invention is limited to this. It is not a thing.

  The search condition generation instruction receiving unit may not be provided, and the search condition generation unit 206 may perform search condition generation processing according to an arbitrary determination condition. For example, a search condition generation process may be performed when a set time has elapsed, or a search condition generation process may be performed when a data set is narrowed down below a certain number. In addition, a classification rule serving as a trigger may be determined in advance, and search condition generation processing may be performed when the classification rule is instructed to be selected.

[Sixth Embodiment]
In each of the above embodiments, it has been described that the processing target data classified by the classification rule used when generating the search condition is the same as the search target data searched by the generated search condition. However, the present invention is not particularly limited to this.

  For example, a search condition for obtaining a desired data set from a data set held by a user is generated, and the search condition is searched by another data set (for example, data on the Web) or by another data management system. You may comprise so that it can utilize for.

  In this case, the search condition generated by the search condition generation unit 206 is generated by absorbing differences in the schema of metadata or ensuring compatibility of search processing.

[Seventh Embodiment]
In the first embodiment, the extraction result calculation unit 203 narrows down the data by calculating the logical product of the information related to the classification results obtained from the different classification rules. It is not limited. For example, the logical sum of the obtained data sets may be calculated. Alternatively, it may be configured such that whether to calculate a logical product or a logical sum for each obtained data set can be switched by providing a switching button or the like.

[Other Embodiments]
Note that the present invention can be applied to a system (for example, a copier, a facsimile machine, etc.) consisting of a single device even when applied to a system composed of a plurality of devices (for example, a host computer, interface device, reader, printer, etc.). You may apply.

  Needless to say, the object of the present invention can also be achieved by supplying a system or apparatus with a storage medium storing software program codes for realizing the functions of the above-described embodiments. In this case, the above functions are realized by the computer (or CPU or MPU) of the system or apparatus reading and executing the program code stored in the storage medium. In this case, the storage medium storing the program code constitutes the present invention.

  As a storage medium for supplying the program code, for example, a floppy (registered trademark) disk, hard disk, optical disk, magneto-optical disk, CD-ROM, CD-R, magnetic tape, nonvolatile memory card, ROM, or the like is used. be able to.

  Further, the present invention is not limited to the case where the functions of the above-described embodiments are realized by executing the program code read by the computer. For example, an OS (operating system) running on a computer performs part or all of actual processing based on an instruction of the program code, and the functions of the above-described embodiments may be realized by the processing. Needless to say, it is included.

  Further, when the program code read from the storage medium is written in a memory provided in a function expansion board inserted into the computer or a function expansion unit connected to the computer, the functions of the above-described embodiments are realized. Is also included. That is, after the program code is written in the memory, the CPU or the like provided in the function expansion board or function expansion unit performs part or all of the actual processing based on the instruction of the program code, and is realized by the processing. This is also included.

It is a figure which shows the hardware constitutions of the information processing apparatus (100) concerning the 1st Embodiment of this invention. 2 is a block diagram illustrating a functional configuration of the information processing apparatus 100. FIG. It is a figure which shows an example of a classification rule. It is a figure which shows an example of a classification rule. It is a figure which shows another example of a classification rule. It is a figure which shows an example of the display window on the output device 106 on which the classification rule was displayed. It is a figure which shows a mode that the classification result classified according to the classification rule instruct | indicated by the user was displayed. 5 is a flowchart showing a flow of classification / display processing in the information processing apparatus 100. It is a figure which shows an example of the display window on the output device 106 on which the classification rule was displayed. 5 is a flowchart showing a flow of search folder generation processing in the information processing apparatus 100. It is a figure which shows an example of the display window on the output device 106 on which the classification rule was displayed.

Explanation of symbols

101 Input device 102 ROM
103 Storage device 104 RAM
105 CPU
106 output device 107 bus 201 classification unit 202 classification result selection input / output unit 203 extraction result calculation unit 204 extraction result output unit 205 search condition generation instruction reception unit 206 search condition generation unit 207 search condition management unit 208 data storage unit 209 classification result selection Information management department

Claims (12)

Classification means for classifying a plurality of data stored in the storage device according to a predetermined classification condition;
First display means for displaying the classification condition;
Information related to data classified by the selected classification condition among a plurality of data stored in the storage device when any of the classification conditions displayed by the first display means is selected. A selection means for selecting
Second display means for displaying information relating to the data selected by the selection means;
When a predetermined instruction is input, a search condition for causing the data on which the information is displayed by the second display means to be acquired as a search result is selected as the selected classification condition. An information processing apparatus comprising: generating means for generating based on the information. The selection means includes
2. The information regarding data classified into any of the classification conditions instructed to select is selected when a plurality of classification conditions displayed by the first display means are instructed. Information processing device. The selection means includes
2. The information related to data classified into one of the classification conditions instructed to select is selected when a plurality of classification conditions displayed by the first display means are instructed. Information processing device. The selection means includes
When a plurality of classification conditions displayed by the first display means are instructed, information relating to data classified by the first classification condition is extracted, and the second information is extracted from the information relating to the extracted data. 2. The information processing apparatus according to claim 1, wherein information relating to data classified according to the classification condition instructed to select is selected by extracting information relating to data classified according to the classification condition.   The information processing apparatus according to claim 1, further comprising: an instruction receiving unit that receives a selection instruction from a user for the generating unit to generate the search condition.   The information processing apparatus according to claim 1, wherein the selection instruction for the classification condition displayed by the first display unit can be canceled.   The information processing apparatus according to claim 1, wherein the classification condition is defined using a metadata item included in the data and a metadata value corresponding to the item.   The information processing apparatus according to claim 1, wherein the classification condition is defined using a metadata item included in the data and a range that a metadata value corresponding to the item can take.   The information processing apparatus according to claim 1, wherein the classification condition is an attribute of the data obtained by analyzing the data.   The information processing apparatus according to claim 1, further comprising a selection instruction unit that selects and instructs the classification condition displayed by the first display unit. A classification step of classifying a plurality of data stored in the storage device according to a predetermined classification condition;
A first display step for displaying the classification condition;
Information related to data classified by the selected classification condition among a plurality of data stored in the storage device when any of the classification conditions displayed in the first display step is selected. A selection process for selecting
A second display step for displaying information on the data selected in the selection step;
When a predetermined instruction is input, a search condition for causing the data on which the information is displayed in the second display step to be acquired as a search result is selected as the selected classification condition. An information processing method comprising: a generation step of generating based on the information. A program for causing a computer to execute the information processing method according to claim 11.

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