JP2002511165A - Acquisition and distribution of document information based on feature constraints - Google Patents

Abstract

(57) Abstract: A user-portable system in which the system is connected to a network by multiple workstations, file servers, printers, and other stationary devices, and infrared (IR) links. A plurality of portable devices. Each portable device emulates a personal sachet for the document of the user of the device, ie, the device is programmed to send, receive, and store feature constraints (FC). The FC is distributed among users by transmitting IR data packets, and when a computer, printer, or multi-function device connected to the network receives the FC via the attached IR radio, a search request is extracted from the FC. Then, a document designator (for example, a URL of WWW) that satisfies the FC is obtained via the search engine. For each obtained URL, a corresponding electronic document is obtained from the storage area and then displayed or printed. As the portable device, a hand-held or wristwatch-type computer having a graphic display unit capable of FC transfer by a user is preferable. Suitable stationary devices include scanners, copiers, or printers with built-in IR radios.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to data processing, and more particularly to transfer of document information between computers and acquisition using a computer. More particularly, the present invention relates to obtaining and transferring information about documents using feature constraints. The use of portable computers is expanding. However, it has not yet been possible to save all documents that a user wants to access as electronic files on a portable computer (due to limited storage capacity, etc.). In addition, it takes a long time to transfer a large amount of documents between the portable computer or between the portable computer and a desk-top business or home computer, and the operability of the user is low. On the other hand, the capacity of recording media for storing electronic documents is increasing, and the use of document transfer via the Internet is expanding. This situation has been problematic in European Patent Application 691,619 (hereinafter EP'619), which includes a plurality of workstations, file servers, printers and other stationary networks connected to a network. A system comprising a portable device (including a multifunctional device) and a variety of portable devices (e.g., a handheld or wristwatch-type computer) carried by a user and connected to a network via an infrared (IR) link are disclosed. I have. Each of these mobile devices emulates a user's personal documentary satchel. That is, these portable devices are programmed so as to be able to transmit and receive a document designator (URL of the World Wide Web) and to store the designator. The indicator is associated with an electronic document stored in an electronic storage area at a site on the Web. By transmitting the URL of the document, the document is distributed between the users. The document is transmitted to the printer by transmitting the URL of the document to an IR radio attached to the printer. The problem with such a system is that the links (Web URLs) that the system stores or distributes point to only one document. That is, the instruction of the indicator of each document is limited to a specific document. In addition, how to keep an eye on the ever-changing electronic documents stored on the storage medium, in accordance with changes in document attributes (author list updates, date updates, keyword updates, etc.) The problem is whether to adjust dynamically. For example, in the apparatus described in EP'618, the user performs a search for the subject C using the URL of the document A written by the author B. The latest document A 'written by author B two years after A on the same subject C, unknown to the user, or another document written by the same author who is very relevant (eg, having common keywords) to C Document A "may exist. The user does not have a link to A 'or A", and even if these documents are useful, a separate document search and search to obtain a URL is performed. Unless you perform a browsing operation, you will remain unaware of those documents. It is desired to provide a system that eliminates the lack of dynamic compatibility of the system up to now and allows a user to operate a pointer to a series of dynamically changing documents. The present invention provides a method performed on a data processing device including a processor, a memory, and a user interface, the method comprising: (a) receiving at least one user input information, the method comprising: The user input information defines at least one relationship, each relationship defining an entity for the document and the characteristics of the entity, and (b) compiling a feature constraint, wherein the feature constraint comprises a step (a). ) Including the relationship received in step (d). The present invention also provides a data processing device suitably programmed to perform the method of any of the appended claims, comprising a processor, a memory, and a user interface. The present invention also provides a data processing device, system or device according to claims 19 to 22 in the appended claims. A data processing device provided by the present invention includes a processor, a memory connected to the processor, a user interface connected to the processor and the memory, the user interface capable of generating user input information by an operation, and at least one user input information. Means for receiving, the user input information defining at least one relationship, the relationship defining an entity for the document and characteristics of the entity, and compiling feature constraints including the received relationship. Means to perform. The above-mentioned problems are solved by using a constraint description. That is, instead of using a pointer to a single document or a static set of documents, feature constraints on the document are stored and distributed, and a dynamic set of documents that satisfies the constraints imposed by the feature constraints is specified. Is obtained. The effect of the present invention will be clarified by an example. Assuming that the feature constraint only restricts the author's name (eg, Smith) and the date of the document (eg, after 1995), the feature constraint specifies all documents written by Smith after 1995. Thus, if Smith wrote another document in 1998, this document would be automatically linked to the "old" constraint without any further user intervention. Further, the present invention is useful in transferring document indicators between portable devices of multiple users when the user is away from an office workstation (e.g., in a remote meeting). Even if the sender knows that there is a document that he / she wants to send, but does not have the URL of his own device, or cannot send the URL because he cannot remember how to identify the URL on his device. Also, if the author name and creation date (or period) and / or keywords are known, the sender can send the feature constraint to the recipient. When the recipient returns to the office, the document can be retrieved on the desktop workstation using the feature constraints. Embodiments of the invention will now be described by way of example with reference to the accompanying drawings. FIG. 1 is a diagram schematically illustrating a data processing network used to execute one embodiment of the present invention. FIG. 2 illustrates a portable computer used in one embodiment of the present invention. FIG. 3 is a diagram schematically illustrating a range defined by encoded feature constraints. FIG. 4 is a flowchart schematically showing a step of compiling a feature constraint. FIG. 5 is a diagram schematically showing a user interface of the stationary computer at a certain moment when an input is made by a user who issues a query. FIG. 6 is a diagram schematically illustrating a user interface of the portable computer at a certain moment. FIG. 7 is a flowchart illustrating the steps for transmitting a feature constraint from one (portable or stationary) device to another (portable or stationary) device. FIG. 8 is a diagram schematically illustrating a data packet that encodes a feature constraint. FIG. 9 is a flowchart schematically showing a step of searching for a document designator using a feature constraint and displaying or printing a corresponding document. FIG. 10 is a diagram showing a part of a list of hits obtained during the processing of FIG. FIG. 11 is a diagram showing a display state after the hit selected from the list of FIG. 10 is converted into the HTML format. FIG. 12 shows one of the selected hits in more detail. 1. System Hardware Obviously, the present invention can be implemented using any conventional computer network technology, either a local area network (LAN) or, more preferably, a wide area network (WAN). The present invention is implemented using a conventionally used cross-platform communication (such as Netscape) and a web browser capable of exchanging documents via the Internet. This embodiment is schematically shown in FIG. The devices 22, 24, and 26 that form a part of the network 21 are a PC that runs Windows (trademark), a Mac (trademark) that runs MacOS (trademark), or a UNIX that runs MacOS (trademark). Obviously, any minicomputer may be used. For example, the hardware configuration of a PC is described in detail in P. Horowitz and W. Hill, "Art of Electronics", Second Edition, Cambridge University Press, 1989. However, obviously, the present invention can be implemented by another system configuration (see EP'619). (A typical network configuration is described in detail in, for example, European Patent Application No. 772,857 and European Patent Application No. (corresponding to US Patent Application No. 08 / 668,704). When a user makes a request on the device 22, a document stored in the device 26 is searched, and the document is transmitted from the device 26 to the device 22 via the plurality of relay devices 24 via the Internet. As is well known, documents are retrieved using the World Wide Web URL as a unique identifier, as described in EP'619. Also, as described in EP'619, preferably, a plurality of printers or a multi-function device (not shown) (having a scanner function, a printer function, a facsimile function, and the like) is connected to the network 21. Multifunctional devices are described in detail in European Patent Application No. 741,487. As is well known, each device connected to a network includes hardware and software suitable for communicating with a portable computer. The portable computer includes a personal digital assistant (PDA), a handheld PC, or a pocket or wristwatch computer. FIG. 2 shows a preferred embodiment of a portable computer. Apparatus 2 is described in detail in EP'619. However, it is clear that this device can be manufactured in various forms. For example, the shape of the device 2 may be any of the shapes disclosed in European Patent Application No. (Application No. 97 301 669.4, reference D / 95594). Each of the stationary devices on the computer 2 and the network 21 preferably has an infrared communication function. A data packet is communicated between the computer 2 and the stationary device so that a document can be obtained. The data packet is a publicly known industry standard infrared Data Association, That is, it conforms to the physical layer and link layer format (IrLAP) described in the IrDA) specification, version 1.0. 2. Knowledge Brokers In accordance with one embodiment of the present invention, each of the devices of FIG. 1 uses a broker for local or remote document retrieval for printing or transfer to another device. A broker is a software agent that processes knowledge search requests. As used herein, knowledge refers to all the individual electronic information made publicly accessible. It is assumed that various sources of information that can be distributed are available. There are various sources of information, for example, from one file in a user's directory, to a local database of a site, and even to a wide area information service (WAIS) on the Internet. Upon receiving the request, the broker needs to process this request if it has sufficient knowledge, or to obtain more knowledge. To obtain knowledge, the broker sends sub-requests to other brokers. Thus, the acquisition of knowledge is realized by the cooperation (collaboration) of all brokers. This broker is either a service provider that processes the request or a client of the service that issues the sub-request. The infrastructure required to perform this collaboration and how to store knowledge locally within each broker is not detailed here (for details on preferred models, see Andreoli et al. Based Knowledge Broker Model: Semantics, Execution and Analysis ", J. Symbolic Computation, 1996). Hereinafter, the knowledge processing performed in each broker will be described. In order to perform a collaboration process, each broker must at least understand each other. That is, all requests (and all responses to requests) need to be formalized in a common language, even if the broker translates locally. Therefore, an appropriate language is obtained using logic. The request is represented by a pair of <x, P>, and this notation means "search for the knowledge object x having the attribute represented by the expression P". x is a logical variable, and P is a logical expression related to x. Interestingly, the answer to this request is also expressed in the same format, that is, an <x, Q> pair meaning that "there is a knowledge object x that satisfies the property represented by the expression Q." In this case, P is a logical consequence of Q, and the answer must contain at least as much knowledge as the request. In addition, the knowledge of the target range of the broker, that is, the related scope can be acquired by using the same logical format. That is, a broker having the range <x, R> means that "I cannot acquire a knowledge object x that does not satisfy the attribute represented by the expression R." In many cases, the acquisition range of the broker varies in order to specialize due to an external factor or the influence of the knowledge search process itself, or conversely, to expand the allowance. In other words, logic provides a common language that can express requests, answers and ranges together. The broker performs logical operations on the three elements. The most important logical operation is the satisfiability check, from which all other logical operations can be reconstructed. Matching satisfiability refers to determining whether an object satisfies the property represented by an expression or, conversely, is essentially inconsistent. Unfortunately, as is well known, in completely classical logic, this operation is not algorithmic. That is, it is almost impossible to implement a program that always completes processing. Considering within certain limits, much knowledge representation research has focused on identifying fragments of classical logic whose satisfiability can be determined algorithmically. There is a trade-off between expressiveness and operability. For example, empty fragments are clearly easy to operate, but expressiveness is extremely poor. The most common fragment elucidated so far is called the "feature constraint" (FC). In this case, the satisfiability problem is called "feature constraint solving." As is well known, feature constraints are constructed with either class or feature atomic constraints. Classification is a unary relation and represents the property of one entity. For example, P: person indicates that the entity P is composed of the classification person. Features are binary relations and represent the property of linking two entities. For example, P: employer → E indicates that entity P has an employee, and this employee is entity E. Apart from classification and features, most feature systems also take into account built-in relationships such as equality and disequality. 3. Principle of Feature Constraint A fragment of a complete feature constraint is one that can combine the above-mentioned atomic components using all logical connection symbols (bond, separation, negation, and restriction), and has a high expressiveness, but an operation Sex is bad. A sub-fragment called "Basic Feature Constraint" (BFC), in which negation and separation are simply prohibited, has been studied, and an efficient constraint solving algorithm for this sub-fragment has been proposed. However, this subfragment has the drawback that the negation does not exist at all, which significantly limits the types of operations that the knowledge broker can perform. In a preferred embodiment, the present invention utilizes a powerful operation that relies on the use of negation, referred to as "range partitioning." In practice, the broker will split the range specified by the pair <x, P> based on the criterion expressed in equation F to generate two brokers with ranges P∧F and P∧¬F. And For example, a broker related to bibliographic information has its own range of “books written after 1950” represented by BFCXX: bookX: year → YY> 1950, and “1950” as the remainder. Book or non-book written before the year ". The latter range cannot be expressed by the BFC because it cannot be expressed without negation and separation. Range splitting operations have proven useful in many cases, for example, when implementing a broker capable of storing and reusing information gathered during its lifetime. Embodiments of the present invention utilize fragments of feature constraints called "signed feature constraints" (SFC), on the one hand, and efficient constraint solution methods for SFC, on the other hand. In this SFC, negation can be used in a limited manner, and the type of the above-mentioned divided range can be expressed precisely. 3.1 Signed Feature Constraints A signed feature constraint consists of a list of positive and negative parts, both of which are basic feature constraints. For example, the following signed feature constraint: P + P: person P: employer → E, E: “Xerox” −P: nationality → N, N: “American” −P: spouse → P ′ P ′: person P ′: employee → E ′ E ′: “Xerox” specifies a Xerox employee who is not American and is not married to another Xerox employee. This is shown schematically in FIG. Circles represent entities (logical variables). The classification relation (unary) is indicated by a classification name in a square frame, and is indicated by a broken arrow. The characteristic relation (binary) is displayed by a characteristic name in a square frame, and is indicated by a solid arrow. Built-in predicates (not present in this example) are indicated by diamonds. The positive portion of the SFC is included in the top column, and is indicated by a double circle to indicate a particular entity (P in this example) range. The negative part of the SFC is included in the lower gray box. The main features of SFC are due to the following properties. That is, the range of the broker is SFC e ₀₁ And if this range is divided by e which is a BFC, the two divided ranges e obtained ⁺ , E ^- Are all SFCs. In practice, e ⁺ Is e ₀ Is obtained by merging the positive part of ^- Is a new negative part containing e alone ₀ By stretching. For example, assuming a bibliographic database-related broker power, including various art-related documents (books, videos, etc.) written by non-Americans, this means that SFC X + X: topic → TT: "Art" -X: author → AA: nationality → NN: “American”. This SFC can be divided by the constraint of “book written after 1950”, and this constraint is expressed by BFCXX: bookX: year → YY> 1950. The obtained range is simply expressed as X + X: book X: topic → TX: year → Y T: “Art” Y> 1950 −X: author → AA: Nationality → NN: “American”. The notation means "art book written after 1950 by a non-American author". XX: topic → TT: “Art” −X: author → AA: nationality → NN: “American” −X: book X: year → Y Y> 1950 Wrote a non-art book related to art after 1950. " 3.2 Solution of Signed Feature Constraints Most constraint systems make some assumptions about the classification and characteristics of features, called system axioms. These axioms are extremely important for satisfiability algorithms because they determine when feature constraints are inconsistent and when they are satisfiable. 3.2.1 Feature Axiom In the embodiment disclosed here, for simplicity, A ^{・ ・} A slightly modified version of the basic axiom system used in t-Kaci H. et al., "A constraint system based on features for logic programming using entailment" (Theoretical Computer Science 122, pp.263-283, 1994). Use. However, the principles of the method can be applied to other axiom systems recognized by those skilled in the art as well. 1. Features are functions. This means that if two pairs of entities constrained by the same feature have the same first term, they also have the same second term. For example, a spouse feature may be a function (in a particular cultural environment). This means that a person cannot have two spouses. In other words, assuming that there is two relations X: spouse → Y and X: spouse → Z with respect to a certain person X, the entities Y and Z match (that is, represent the same person). In addition, some feature systems allow multiple values. 2. Classification is disjoint. That is, an entity does not consist of two different categories. For example, a book is not a person, that is, there can be no entity X such that X: book and X: person on. In other systems, classification is hierarchically considered, and an entity can have multiple classifications as long as an entity has a common element in the hierarchy. 3. There is a special subset of classifications, called "value" classifications, which keeps two different entities from the same class. Traditional basic elements (strings, numbers, etc.) are typical value classes, for example, the string "Xerox" or the number "1950" is a value class. Value classification is not allowed to have features, it is an axiom only for combining classification and features. Other systems allow for more sophisticated combinations of classification and features. 4. There is a special built-in binary predicate that has the traditional congruent axiom (including classification and features) that is equivalent. Axioms describing all other built-in predicates shall not include descriptions of classifications and features. These axioms are shown in formal form in Section A: Axioms in the Appendix at the end of this specification. These axioms are components of theory T. 3.2.2 Constraint Satisfaction First, satisfiability on the built-in predicate is solvable. That is, when there is an expression F using only the built-in predicate (F is also called a built-in constraint), there is an algorithm that determines whether F is a logical consequence of the theory T 1 (represented by ├TF). Constraint satisfaction on the BFC is defined by a set of conditional rewrite rules on the BFC (see section B.1 in the Appendix). This rewrite rule has the following properties. (A) The rule system is convergent and thus defines the "standard form" of BFC. By proving that the system is "Church Rossa" (critical pair convergence) and "Natorian" (term size shrinks strictly with each rewrite), the above can be shown in a classical way. (B) BFCs are satisfiable unless and only if the standard form is not contradicted. One implication is proved by showing that the rewriting step remains satisfiable. The opposite implication is proved by showing a model that satisfies the BFC with a standard form that is not reduced to contradictions. In this way, the steps of the constraint satisfaction algorithm are described by the rewriting rules. Since the rewriting rule system is convergent, this algorithm always terminates processing. Importantly, the definition of this rule relies on the satisfiability test of built-in constraints that are solvable. In other words, this algorithm is modular, and can incorporate all kinds of built-in constraints as long as an appropriate built-in constraint satisfaction algorithm is given. The rules for rewriting the constraint satisfaction algorithm can be easily implemented using a symbolic language such as Lisp or Prolog, or can be optimized by considering the properties of the particular built-in constraints used. The constraint satisfaction algorithm on the SFC (see paragraph B.2 in the Appendix) is briefly described as follows. In some SFCs, the positive component is first standardized by a BFC algorithm. If the results are inconsistent, the entire SFC is unsatisfiable. If not inconsistent, after the (normalized) positive component is inserted into each negative component, the negative component is standardized by the BFC algorithm. If the obtained negative component has an inconsistent standard form, the component is deleted, and if it has a totological standard form, the entire SFC cannot be satisfied. The standard form of the SFC obtained in this way has the following properties: The SFC is satisfiable if and only if the standard form is not contradicted. As in the previous case, the parts that are difficult to imply are proved using model theory. 4. User Transaction Using Feature Constraints FIG. 4 is a flowchart schematically showing steps for compiling feature constraints. First, when a user specifies a certain query, for example, "a book or article after 1990 that includes" constraints "in the title and does not include the" Internet ", multiple user input information is received (s41). ). When the input information is received, the relationship (see section 2 above) is determined. FIG. 5 is a diagram illustrating a user interface of the stationary computer at a point in time when an input is performed by a user performing a query. This user interface is described in detail in International Patent Application No. based on UK Patent Application No. 9708172.3 (Reference R / 97005Q / JDR) filed with the present invention. When the user finishes inputting the query element, the feature constraint is compiled from the obtained relation (step s42). The user is prompted to enter a short query name (s43) or, after a default query name has been assigned, the FC is saved in final form. This user input is performed in a well-known manner on a portable computer using a keyboard, touch screen user interface, displayed list and scroll / control buttons, and the like. If the portable computer has a small user interface, the method disclosed in European Patent Application No. 733,964-a method for accessing members of a stored series of data-may be used. As still another method, there is a method in which a user inputs a query using one sheet of paper via a scanner, and obtains FC from the query. That is, when the user enters a check in a box on a preprinted standard sheet (a possible relationship is displayed in a human-readable form on this sheet), and the checked sheet is scanned. The relationship is extracted from the obtained image data, and the FC is compiled using this relationship. This method is described in detail in the aforementioned international patent application (reference R / 97005Q / JDR). FIG. 6 is a schematic diagram of the user interface 60 of the portable computer at a certain moment. Information is provided to the user using the general-purpose technique disclosed in EP'619. As disclosed in EP'619, an icon 61 and a document name 62 corresponding to the saved URL are displayed. In addition, an icon 63 and a short query name 64 corresponding to the saved FC are also displayed. Depending on the situation, the user may also see a long description. For example, when the icon 63 is selected and a button is pressed in response to a double-click on a known user interface, the long description is displayed. In this case, a long description of "a book written by Babbage after 1993, which includes" Lecture "and" Object Orientation "in the title, is displayed. FIG. 7 is a flowchart schematically illustrating a step of transmitting a feature constraint from one (portable or stationary) device to another (portable or stationary) device. As described in EP'619, the computer performs context-dependent processing. That is, the icons of the computers of the respective users in the IR communication area are mutually displayed on the user interface (step s71). After the user requests to send FC to another user in range (s72), if the request is for a new, non-existent FC, the process of FIG. 4 is continued and the new one must be used. For example, FC is obtained from the memory (s73). This FC is then encoded in a suitable format and distributed using any of the communication methods described in EP'619. FIG. 8 schematically shows an example of a data packet in which the FC is encoded in the data area. A preferable communication means is an IR signal, and an IR signal using data transfer according to the IrDA standard is particularly preferable. Returning to FIG. 7, icons of all users in the range are also displayed on the user interface of the receiver (step s75). Upon receipt of the IR data packet, the packet is decoded and the FC is extracted (s77) and, if requested, stored at a designated location in the directory of the recipient's device for later use. FIG. 9 is a flowchart schematically showing steps of acquiring a document designator using the feature constraint and displaying or printing the corresponding document. This operation is performed by a conventional computer or a multi-function device or a printer with a user interface. Initially, FC data is transmitted by, for example, a data packet from a user of the portable device as shown in FIG. 8 or, as is well known, by the user inputting directly to the device using a keyboard, mouse or touch screen. Is received from the user. According to the user's instruction by appropriate input, the FC is solved according to the procedure already described in section 3, and the obtained request in an appropriate format is sent to the search engine (s92). Using this search request, all searchable storage media for documents satisfying the FC are searched (s93), and if necessary, as described in the aforementioned international patent application (reference R / 97005Q), the request is It is subdivided into sub-requests. When a list of hits (of documents satisfying FC) is obtained by the search engine, it is displayed as shown in FIG. 10 (s94). Next, in response to an appropriate user input, operations such as extended display of document details of each hit, conversion of document information into HTML format, or download of a document from a storage medium are performed (s95). FIG. 11 shows a state after the hit selected from the list of FIG. 10 is converted into the HTML format. As shown, additional information such as author name, http_url, information source, and title is displayed for each hit. If desired, the user can view the document corresponding to the hit by a single mouse click on the displayed http_url. Thereafter, printing of the document is performed as necessary (s96). FIG. 12 shows a more detailed display of one selected hit, ie, a series of document attributes. As shown in the figure, a plurality of URLs are displayed corresponding to the plurality of attributes and linking to further pages providing information on these attributes. Obviously, feature implementations in the form of signed feature constraints described in Section 3 can be used in implementing the techniques described herein. Appendix A System axioms There are three sets of axioms: Specific axioms τ and τ ′ of features and types represent arbitrary classes, and f represents arbitrary features. The joint axiom of equality p represents any built-in predicate. The traditional joint axiom is: Built-in predicate axiom This axiom does not describe classifications and features. For example, unequal Axiomized by The dominant constraint is Axiomized by The built-in predicates,>, ≤, ≥, are defined by <and the equal sign. B. Constraint satisfaction 1 In the case of BFC BFC is represented by a <B | Γ> pair. B is a built-in constraint and Γ is an unordered list of classification and feature constraints (read jointly). ⊥ indicates contradiction. There are two sets of rewrite rules. The following rules correspond to the simplification of BFC. The following rules correspond to conflict detection. The following properties support the validity of this algorithm. B. 2. Case of SFC The SFC is represented as an unordered list of BFCs with a sign (+ or-), and one and only component is defined as positive. Let S be SFC. S ^* Is written as Sn, which is given by the following algorithm: If c0 is the BFC standard form of the positive component of S, then if c0 = ⊥ return ⊥, otherwise c0 is <B ₀ ｜ Γ ₀ 〉 Form {〈B _i ｜ Γ _i >} I = 1,. . . , N is the negative component of S. For each i = 1,. ₀ ∧B _i ｜ Γ ₀ , Γ _i 〉 BFC standard format If i = 1, ..., n such that ci = <B | Γ> and ├τB and Γ is empty, return ⊥. Otherwise, I = {i∈1, ..., n} such that ci ≠ ⊥ The following properties support the validity of this algorithm.

[Procedure amendment] [Submission date] June 30, 2000 (2000.6.30) [Correction contents]                                The scope of the claims 1. Data processing device including processor, memory, and user interface Wherein the data processing device comprises one or more devices via a network. Connected to the other data processing devices above, and A method that includes means for storing an electronic document storage area, (A) receiving a series of one or more user input information; (B) obtaining a feature constraint based on a series of user input information; A constraint includes one or more relationships, each of which is an entity for the document and its Process that defines the attributes of the entity (C) solving a feature constraint and determining one or more document indicators from the feature constraint; Document in the storage area in which the one or each document designator satisfies the feature constraint. Corresponding to the method. 2. 2. The method according to claim 1, wherein step (a) is repeated several times before step (b). A method characterized by being returned. 3. 3. The method according to claim 1, wherein the data processing device is a portable computer. Computer, and wherein step (a) includes a touch screen or keyboard. Receiving user input information via a password. 4. 3. The method according to claim 1, wherein the data processing device is a stationary computer. Computer, and wherein step (a) comprises a touch screen, a keyboard And / or receiving user input information via a mouse. how to. 5. The method according to claim 1 or 2,   Step (a) (A1) receiving a series of one or more user input information defining at least one relationship; Trusting,   Step (b) is (B1) a step of compiling feature constraints based on a series of user input information; The compiled feature constraints are defined by a series of one or more user input information A step comprising each relationship. 6. The method of claim 5, wherein   The data processing device includes a multifunctional device including a scanning unit,   Step (a) (A2) A portable recording medium having an image is scanned and at least one of the medium is scanned. Generating an electronic signal corresponding to the two predetermined portions; (A3) determining a relationship corresponding to the signal from the signal. How to sign. 7. 7. The method according to claim 6, wherein the medium is arranged in the predetermined portion. A human-readable indicator and a link corresponding to the predetermined portion related to the arrangement. A human-readable index for each section is provided in each of the predetermined portions. Method. 8. Data processing device including processor, memory, and user interface The method performed in (D) first indicating a graphical object corresponding to the stored feature constraint Receiving the user input information, wherein the feature constraints include one or more relationships. The one or each relationship is an entity relating to the document and the entity A process that defines the attributes; (E) a second constraint indicating that the feature constraint is to be transmitted to another data processing device. Receiving the second user input information; (F) encoding the feature constraint into a data packet; (G) transmitting a data packet. 9. The method according to any one of claims 1 to 8, wherein step (a) comprises: (A1) receiving a series of one or more user input information indicating a feature constraint; Including   The indicated feature constraint is a stored feature constraint, and the stored feature is The constraint is (H) receiving a data packet; (I) a step of decoding a data packet to extract a feature constraint; A feature constraint includes one or more relationships, where one or each relationship is an entity related to the document. A process that defines the attributes of the entity and its entities; (J) storing the feature constraints extracted in step (i). And the method characterized by the above. 10. The method according to any one of claims 1 to 8, wherein step (a) comprises: (A1) receiving a series of one or more user input information indicating a feature constraint; A method comprising: 11. The method of claim 1, wherein (K) displaying the one or each document designator determined in step (c). A method characterized by the following: 12. The method of claim 11, wherein (L) in response to second user input information pointing to one of the displayed document indicators, A document corresponding to the document designator is obtained from the storage area, and the Displaying a book or a portion of a document. 13. The method according to claim 11 or 12, (M) A document corresponding to the document indicator is printed according to the third user input information. The method comprising: 14． 14. The method according to any of claims 1 to 13, wherein the feature constraint is low. At least one positive component and one negative component are included, each of the positive and negative components having one or more functions. A method comprising engaging. 15. 15. The method according to any of the preceding claims, wherein one of said relationships. Is a classification relation, and the classification relation indicates a classification included in the corresponding entity. The method characterized in that: 16. 16. The method according to any of the preceding claims, wherein one of said relationships. Is a characteristic relationship, and the characteristic relationship is that the corresponding entity has one attribute. And the value of the attribute is a second entity. 17． 17. The method according to any of the preceding claims, wherein the entity is A method characterized in that the attribute possessed is a value or a range of values. 18. A data processing device for performing a method according to any of the preceding claims. Processor, memory, and user interface A device comprising a base. 19. In the data processing device,   A processor,   Memory connected to the processor,   A user interface connected to the processor and the memory, the user interface comprising: User interface that can generate user input information by the operation of ,   An electronic document storage area;   Means for receiving a series of one or more user input information;   Means for obtaining a feature constraint based on a series of user input information; Contains one or more relationships, where each relationship is an entity for the document and its Means for defining the attributes of the   A means for solving a feature constraint and determining one or more document indicators from the feature constraint The one or each document designator corresponds to a document in the storage area satisfying the feature constraint. A data processing apparatus. 20. In a system that accesses and distributes electronic documents,   A storage area for an electronic document, said document having a corresponding document designator A storage area,   A plurality of objects, at least one of which is An object that is a band type or a mobile type, and each object includes:   A processor,   Memory connected to the processor,   Connected to the processor and memory, generates user input information by user operation User interface made available,   Means for receiving a series of one or more user input information;   Means for communicating with the one or each object and a user interface;   Acquire, store, and / or transmit feature constraints based on a set of user input information Means, wherein the feature constraints include one or more relations, each of which is related to a document. Means that specify the attributes of the entity and its entities;   A means for solving a feature constraint and determining one or more document indicators from the feature constraint Then, the one or each document designator specifies a document in the storage area satisfying the feature constraint. Corresponding means. 21. A portable device for accessing and delivering electronic documents   A processor,   Memory connected to the processor,   Connected to the processor and memory, generates user input information by user operation User interface made available,   A means of communication with a stationary or mobile electronic device and a user interface. Thus, at least one of the stationary and mobile electronic devices is capable of storing an electronic document. Means for preserving the domain, wherein each document has a corresponding document designator. ,   Means for receiving a series of one or more user input information;   Acquire, store, and / or transmit feature constraints based on a set of user input information Means, wherein the feature constraint comprises one or more relationships, each relationship being associated with a document. Means for defining an entity and its attributes;   A means for solving a feature constraint and determining one or more document indicators from the feature constraint Then, the one or each document designator specifies a document in the storage area satisfying the feature constraint. Portable device comprising: a corresponding means. 22. An apparatus for scanning, copying and / or printing a document,   A processor,   Memory connected to the processor,   Means for accessing a storage area of an electronic document, wherein each electronic document has a corresponding document Means having an indicator;   By means of a user interface and communicating with one or more multiple objects And at least one of these objects is portable or mobile. Means,   Means for receiving a series of one or more user input information;   Capturing, storing, and / or transmitting feature constraints based on a set of user input information The feature constraint includes one or more relationships, each of which relates to a document. Means that specify the entity to perform and the characteristics of that entity;   A means for solving a feature constraint and determining one or more document indicators from the feature constraint The one or each document designator corresponds to a document in the storage area satisfying the feature constraint. Responsive means.

────────────────────────────────────────────────── ─── [Continuation of summary] It includes a printer.

Claims (1)

[Claims] 1. Data processing device including processor, memory, and user interface The method performed by (A) receiving at least one user input information, wherein the user input information is received; The force information defines at least one relationship, wherein the or each relationship relates to a document. A process that defines an entity and the characteristics of that entity; (B) compiling feature constraints, wherein the feature constraints are received in step (a); A step comprising a trusted relationship. 2. 2. The method according to claim 1, wherein step (a) is repeated several times before step (b). A method characterized by being returned. 3. 3. The method according to claim 1, wherein the data processing device is a portable computer. Computer, and wherein step (a) includes a touch screen or keyboard. Receiving user input information via a password. 4. 3. The method according to claim 1, wherein the data processing device is a stationary computer. Computer, and wherein step (a) comprises a touch screen, a keyboard And / or receiving user input information via a mouse. how to. 5. 5. The method according to claim 4, wherein the stationary computer is a scanning means. Including multi-function devices, including   Step (a) (A1) A portable medium having an image is scanned and at least one location in the medium is scanned. Generating an electronic signal corresponding to the fixed part, (A2) determining a relationship corresponding to the signal from the signal. How to sign. 6. 5. The method according to claim 4, wherein the medium is arranged in the predetermined portion. A human-readable indicator and a link corresponding to the predetermined portion related to the arrangement. A human-readable index of the person in charge at each of the predetermined portions. Way. 7. Data processing device including processor, memory, and user interface The method performed in (D) first indicating a graphical object corresponding to the stored feature constraint Receiving the user input information, wherein the feature constraints include one or more relationships. The one or each relationship is an entity relating to the document and the entity A process that defines the characteristics; (E) a second constraint indicating that the feature constraint is to be transmitted to another data processing device. Receiving the second user input information; (F) encoding the feature constraint into a data packet; (G) transmitting a data packet. 8. Data processing device including processor, memory, and user interface The method performed by (H) receiving a data packet; (I) decoding a data packet to extract a feature constraint, A constraint includes one or more relationships, where the or each relationship is related to the document. A process that defines the attributes of an entity and its entities, (J) storing the feature constraint extracted in step (i). Way. 9. Data processing device including processor, memory, and user interface Wherein the data processing device comprises one or more devices via a network. Connected to the other data processing devices above, and A method that includes means for storing a storage area of an electronic document, (K) receiving at least one user input signal indicating a feature constraint. Thus, the feature constraint includes one or more relationships, wherein one or each relationship relates to a document. Processes that define the entity and the characteristics of that entity, (L) solving the feature constraint and determining one or more document indicators from the feature constraint; The one or each document designator is the storage location that satisfies the feature constraint. Corresponding to a document in the region. 10. 10. The method according to claim 9, wherein step (k) comprises the method according to claim 8. A method comprising: 11. The method of claim 9, wherein (M) displaying any one of the document indicators determined in step (l). A method comprising: 12. The method of claim 11, further comprising: (N) in response to a second user input signal indicating one of the displayed document indicators, A document corresponding to the document designator is obtained from the storage area, and the Displaying a book or a portion of a document. 13. The method according to claim 11 or 12, further comprising: (O) A document corresponding to the document indicator is printed in response to a third user input signal. The method comprising: 14． 14. The method according to any of claims 1 to 13, wherein the feature constraint is low. At least one positive component and one negative component, wherein each of the positive component and the negative component is one A method comprising the above relationships. 15. 15. The method according to any of the preceding claims, wherein one of said relationships. Is a classification relation, and the classification relation indicates the classification included in the corresponding entity. A method comprising: 16. 16. The method according to any of the preceding claims, wherein one of said relationships. Is a characteristic relationship, and the characteristic relationship is that the corresponding entity has one attribute. And the value of the attribute is a second entity. 17． 17. The method according to any of the preceding claims, wherein the entity is A method characterized in that the attribute possessed is a value or a range of values. 18. A data processing device for performing a method according to any of the preceding claims. Processor, memory, and user interface A device comprising a base. 19. In the data processing device,   A processor,   Memory connected to the processor,   A user interface connected to the processor and the memory, the user interface comprising: A user interface adapted to generate a user input signal by the operation of as well as   Means for receiving at least one user input information, wherein said user input information is The report defines at least one relationship, where the or each relationship is related to the document. Stipulates the attributes of the entity and its entities. Compiles the feature constraints, which include the received relationships. An apparatus, comprising: a means. 20. In a system that accesses and distributes electronic documents, the storage A storage area in which each document has a corresponding document designator; Object, at least one of said objects being portable or Is a mobile object, each object being the one or each other object and Object including communication means with the Means for transmitting, storing, and / or transmitting, wherein the characteristic constraints relate to one or more relationships. And the one or each relationship is an entity relating to the document and the entity Means for defining attributes. 21. For portable devices that access and deliver electronic documents, Means for communicating with a moving body electronic device and a user interface, wherein Includes means for storing a storage area for electronic documents, each document having a corresponding storage area. Receiving, storing, and / or receiving a communication means having a document designator and a feature constraint. Or means for transmitting, wherein the feature constraint includes one or more relationships, and the one or more Where each relationship specifies an entity for the document and the attributes of that entity A portable device comprising: 22. Applicable to devices that scan, copy and / or print documents Means for accessing a storage area of an electronic document having a document designator Means for communicating with a plurality of objects and a user interface, wherein Means wherein at least one of the objects is portable or mobile, and Means for receiving, storing, and / or transmitting a feature constraint, wherein the feature constraint is one Including the above relationships, the or each relationship can be an entity related to the document and its A means for defining the attributes of the titties.