Abstract:
A method and apparatus for the collaborative knowledge-based creation and extension of an information graph are taught. The method comprises a first step of retrieving items of a given, human-made information graph in a database, a second step of retrieving relations between the given elements, not yet drawn in the information graph or of retrieving characteristics of the given elements, or of retrieving information about the given elements, a third step of attaching these new relations and/or retrieved elements to the given graph on a graphical device and a fourth step of manually adding these proposed items of information to the information graph. The items of information include elements of information and relations between the elements of information. The elements of information are displayed as nodes on the relation map and the relations as lines on the relation map. The apparatus for the display of information on a screen comprises a query processor for processing a query from a user, a query interpreter for interpreting the query from the user, an information acquirer for retrieving items of the information form a database, a graph calculator for calculating a relation map and a drawing processor for creating graphical elements representing at least some of the items of information and for accepting instructions from the user to create at least one further graphical element.

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
       [0001]    None. 
       STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT 
       [0002]    None. 
       BACKGROUND OF THE INVENTION 
       [0003]    1. Field of the Invention 
         [0004]    The present invention relates to apparatus and accompanying methods that help to intensify the interchange and linking of information between humans and machines, for example personal computers or robots. 
         [0005]    2. Brief Description of the Related Art 
         [0006]    A mind map (or mind-map) is a diagram used to represent words and ideas linked to and arranged around a key word or idea. The mind-map is used to generate, visualize, structure and classify thoughts and ideas, and can also be used as an aid in study, organization, problem solving, and decision making. The mind-map is an image-centered diagram that represents semantic or other connections between portions of information. The mind-map encourages a brainstorming approach to any given organizational task as it eliminates the hurdle of initially establishing an intrinsically appropriate or relevant conceptual framework within which to work. 
         [0007]    The mind-map generally involves elements such as images, words, and lines. The elements are arranged intuitively according to the importance of the concepts and they are organized into groupings, branches, or areas. 
         [0008]    The mind-map is created by humans and has been traditionally done by using pen and paper. However, software is now available which provides presents graphical tools for bringing the associations and information of the user into the computer and onto the screen. Companies such as Mindjet, San Francisco, Calif., produce such software. 
         [0009]    A semantic network is often used as a form of knowledge representation. The semantic network is a directed graph consisting of vertices which represent concepts and edges which represent semantic relations between the concepts. The semantic network is used extensively to provide computer representations of the relationships between various concepts. In some senses, one can consider the mind map to be a very free form variant of a semantic network created by a human. 
         [0010]    The Resource Description Framework (RDF) is a family of World Wide Web Consortium (W3C) specifications which is used as a general method of modelling knowledge, through a variety of syntax formats (XML and non-XML). The RDF metadata model is based upon the idea of making statements about resources in the form of a subject-predicate-object expression which is called a “triple” in RDF terminology. For example, one way to represent the fact “The sky has the color blue” in RDF would be to use a triple whose subject is “the sky,” whose predicate is “has the color”, and whose object is “blue.” Predicates in the RDF are traits or aspects about a resource and express a relationship between the subject and the object. 
         [0011]    The RDF&#39;s simple data model and ability to model disparate, abstract concepts has led to increasing use in knowledge management applications. 
         [0012]    The triples of the Resource Description Framework (RDF) of the semantic web are designed to allow a machine based drawing of information graphs. The focus of the triples is to allow the machine to make an automatic drawing of information graphs (i.e. graph generated by computer from data input by user). The triples cannot currently be used to analyse and modify an information-graph that the user has previously created or to add information items to an existing information graph. In short, the approach of the RDF is not as “intelligent co-worker” with analysing, association and drawing capabilities but as a passive tool to draw the information graphs. 
       SUMMARY OF THE INVENTION 
       [0013]    In view of the foregoing, there is therefore a need to enable the bringing or linking of information stored within a machine with information provided by humans. 
         [0014]    There is furthermore a need to allow the addition of information items (nodes or connections or notes or retrieved documents) to an existing information graph. 
         [0015]    These and other objects of the invention are met by a method and apparatus which allows humans and machines a collaborative, interactive and knowledge-based drawing of graphs. In this invention, the machine becomes a knowledge-based co-worker of the user. The machine can offer refinement of the information the user expresses in the graph. In the invention, the machine examines the information graph drawn by the user draws and supplements the information by adding or offering or modifying elements or by assigning notes to existing elements or retrieving assets and information relating to the graph or to parts of the graph or to elements of the graph the user has activated. The machine learns from the information graph by integrating the new elements and the new relations provided by the user into its own knowledge base (relation network). 
         [0016]    In a preferred embodiment, the invention is a method and apparatus for the collaborative knowledge-based creation and extension of an information graph. The method comprises a first step of retrieving items of a given, human-made information graph in a database, a second step of retrieving relations between the given elements, not yet drawn in the information graph or of retrieving characteristics of the given elements, or of retrieving information about the given elements, a third step of attaching these new relations and/or retrieved elements to the given graph on a graphical device and a fourth step of manually adding these proposed items of information to the information graph. The items of information include elements of information and relations between the elements of information. The elements of information are displayed as nodes on the relation map and the relations as lines on the relation map. 
         [0017]    The apparatus for the display of information on a screen comprises a query processor for processing a query from a user, a query interpreter for interpreting the query from the user, an information acquirer for retrieving items of the information form a database, a graph calculator for calculating a relation map and a drawing processor for creating graphical elements representing at least some of the items of information and for accepting instructions from the user to create at least one further graphical element. 
         [0018]    Still other aspects, features, and advantages of the present invention are readily apparent from the following detailed description, simply by illustrating a preferable embodiments and implementations. The present invention is also capable of other and different embodiments and its several details can be modified in various obvious respects, all without departing from the spirit and scope of the present invention. Accordingly, the drawings and descriptions are to be regarded as illustrative in nature, and not as restrictive. Additional objects and advantages of the invention will be set forth in part in the description which follows and in part will be obvious from the description, or may be learned by practice of the invention. 
     
     
       BRIEF DESCRITION OF THE DRAWINGS 
         [0019]    For a more complete understanding of the present invention and the advantages thereof, reference is now made to the following description and the accompanying drawings, in which: 
           [0020]      FIG. 1  is a block diagram depicting methods in accordance with preferred embodiments of the invention. 
           [0021]      FIG. 2  depicts seven ways of how the methods can modify an information graph. 
           [0022]      FIG. 3  depicts the idea of organizing information graphs in a kind of book (Multilayer Information Graph). 
       
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS 
       [0023]      FIG. 1  illustrates one method of the invention. A user  105  interacts with a computer screen  110  or a similar input device, such as a graphic tablet. The computer screen  110  is attached to a client computer system  115  which is attached in turn to a server computer system  130 . The server computer system  130  could also be incorporated into the client computer system  115 . 
         [0024]    There are two modes of operation of the client computer system  115 : a query process  120  and a drawing process  125 . The drawing process  125  operates by using the client computer system  115  as a graphic tool to draw an information graph representing a semantic network. This is done with the help of common graphic tools  125 . These include, but are not limited to, graphic programmes such as Visio or ConceptDraw and the tools such as MindJet and MindManager mentioned above. The information graph can contain vertices, nodes, edges, text boxes, links, etc. 
         [0025]    The second mode of operation is the query processor  120  in which the user  105  asks the client computer system  115  to perform knowledge-based operations  200  as will be explained in connection with  FIG. 2 . In this second mode of operation, the user  105  does not draw an information graph on the computer screen  110  but inputs a text-based query into the client computer screen  115  by means, for example, of a keyboard. Alternative methods of entry such as selection from drop-down lists are possible. 
         [0026]    After the user  105  has entered the query, it is interpreted by a query interpreter  145 . The query interpreter  145  analyses the kind of task which the user  105  is requesting. The query analyser  145  also sees whether an information graph has been previously generated and determines the actual status of the information graph (described below). Finally the query server  145  needs to acquire requested information. 
         [0027]    The query server  145  uses an information acquirer  150  to acquire the information for the information graph. The information acquirer  150  has to communicate with an information base  155 . The information base  155  may be a database or an association processor and will include a semantic network. The information may be stored in the information base  155  as an RDF triple or in another format, such an extended RDF format. If an information graph exists in the information base  155 , then the current status of the information graph is transformed to a context. The context is generated by analysing the information attached to the nodes of the information graph and the edges between the nodes of the information graph. This is discussed in more details in the Applicant&#39;s co-pending U.S. patent application Ser. No. 11/350,095. The information acquirer  150  takes the context into account when acquiring the information. The information acquirer  150  will return a number of hits. 
         [0028]    An example of this could be, for example, a request to drawn a view of the information graph related to Parkinson&#39;s disease. The information acquirer  150  would access the information base to determine what information is contained on Parkinson&#39;s disease and also whether the information graph had previously been requested (and was therefore stored). The hits relating to Parkinson&#39;s disease will be returned to the information acquirer  150 . 
         [0029]    Should an existing information graph be found in the information base  155 , the existing information graph will be updated. This will occur, for example, in the event that new or additional information has been added to the information base  155  since the creation of the existing information graph. The existing information graph and the hits representing the new information are passed to a graph calculator  160 . The graph calculator  160  produces a set of graphical instructions which are delivered to a drawing process  125  in the client computer system  115 . The drawing process  125  creates graphical elements on the screen  110 . 
         [0030]    In the event that no existing information graph is found in the information base, the information acquirer retrieves the hits and passes the retrieved hits to the graph calculator  160 . The graph calculator  160  calculates an initial information graph which is then sent to the drawing process  125  in the client computer  115  for creating graphical elements on the screen  110 . 
         [0031]      FIG. 2  illustrates the ways in which the machine supports the user  105  in creating the information graph. Suppose that the user  105  had created the information graph  210  as described above or has retrieved an existing information graph from the information base  155 . The relation map  210  includes but is not limited to mind-maps and concept maps. The relation-map  210  has a plurality of elements E 1 -E 13  as shown in the figure. Some of the elements E 1 -E 13  are connected by edges or lines between other ones of the elements E 1 -E 13 . Each of the edges represents at least one relation between the connected ones of the elements E 1 -E 13 . So, for example, element E 1  is connected by an edge to element E 3  which is also connected by an edge to element E 7 . The element E 7  is connected by edges to elements E 3 , E 7  and E 6 . The relation map  210  is stored in a memory in the client computer system  115  and at least part of the relation map is displayed on the screen  110  using a graphics card. If the relation map  210  is so large, then only part of the relation map  210  is displayed on the screen  110  but the rest of the relation map is contained in graphic memory in the client computer and can be moved using known techniques (e.g. scrolling). 
         [0032]    The edges on the relation map  210  are click-sensitive, i.e. clicking any area near one of the edges (or adjacent to one of the edges) selects the clicked one of the edges and will open a window with information  280  on the screen  110 . The information  280  includes but is not limited to information about the relationship between the elements (in this case between E 10  and E 12 ) represented by the selected one of the edges. 
         [0033]    As an example, the user  105  may be interested in the effects of dopamines on Parkinson&#39;s disease and clinical management. The relation map would include elements “Parkinson&#39;s disease”, “clinics” and “dopamine”. The user  105  would draw an edge between the element representing dopamines and the element representing Parkinsonian disease. Similar the user would draw a line between the element representing Parkinsonian disease and the element representing clinics. The user  105  may have heard that the presence of aluminium in the environment affects the susceptibility of a person to Parkinson&#39;s disease. The user  105  does not know the connection and therefore the element representing Aluminium is initially not connected to any of the other ones of the elements (such as element E 13  in  FIG. 2 ). 
         [0034]    The user  105  can define whether the line (connection) be stored permanently within the information base  155 . This can be done automatically by the system noticing the drawn line and storing the information but no further details. The system could also request from the user  105  details of the type of the link and the relationship between the nodes. 
         [0035]    The user  105  having drawn the initial relation map  210  (using the drawing process  125 ) can then ask the server computer  130  to add further elements to the initial relation map  210 . The user  105  can do this by activating, for example, elements E 1 , E 3  and E 6  requesting from the server computer system  130  their relation. This activation is done using the query process  120  in which the elements are selected and a query created which is sent to the query interpreter  145  as disclosed above. The query interpreter  145  accesses the information base  155  to find the hits relating to E 1 , E 3  and E 6 . 
         [0036]    In the case illustrated in  FIG. 2   b , the server computer system  130  identified a further relation between E 1  and E 6  via a new element E 2  (i.e. a new hit in the information base  110 ). The server computer system  130  provides the new hit to the graph generator  160  which adds the new element E 2   230  to the graph and draws the corresponding lines between E 1  and E 6  and E 2  and E 1  on the computer screen. 
         [0037]    The user  105  can ask the graphic card in the client computer system  115  to color all of the elements belonging to a specific category. The user  105  can note that, for example, element E 1  and E 7  belongs to a first category and the element E 2  to a second category. 
         [0038]    The user  105  can ask the graphic card to code the empiric co-occurrence value between hits in the information base  155  by amending the thickness of the line between two of the elements E 1 -E 13  representing this empiric co-occurrence value. This is shown as edge  235  in  FIG. 2   b.    
         [0039]    The user can instruct the machine to add relations from E 8  to any other element E 1 -E 7 , E 9 -E 13  on the information graph  210 . The graphic card system draws new edges, for example, to E 5   240  but also to E 3 , E 10 , E 12  and E 13 . Thereby the machine also moves the position of the elements  242  to optimize the graph. Should the machine find a relation other than the relation stated in the graph, the machine can add a relation between elements that had already been connected by the user. This is illustrated by new edge  244 . 
         [0040]    The user can ask the system to mark all of the elements E 1 -E 13  that, for example are part of a structure not drawn in the graph. Then the system marks all these elements as is shown at  250  open the information graph  210 . 
         [0041]    The user  105  also allows annotation of the elements E 1 -E 13  of the graph as is shown at  260 . The annotations can be stored in the information base  155  and retrieved by the information acquirer when searching for hits. The annotations include information from another user about one of the relations, or information that is contradictory. 
         [0042]    The user  105  can ask machine system to add documents (or links) to the information graph  210  as a whole or to parts of the information graph  210 . The machine carries out the document and symbolizes the documents by an icon  270  at elements E 1 , E 3  and E 4 . Double-clicking the icon  270  opens a list with documents related to the three elements E 1 , E 3  and E 4 . 
         [0043]    The user  105  can double-clicks an edge to see the relation specified by the edge and also the information retrieved by the machine (information, coupling-strength etc.). 
         [0044]    The system draws every modification of the graph in a separate and transparent layer, like a transparent foil on top of a paper graph. The user  155  then selects those elements he wants to add to his graph in the transparent layer to create a transparent action-layer. The user can use a multiple of these transparent action-layers. The action-layers can be mapped onto each other to obtain the required result. This is similar to placing multiple transparent foils onto the paper graph to understand the relationships between the multiple transparent foils. 
         [0045]    If the user has more than one information graph  210  it may be interesting to see relations between the more than one information graph  210 . The user  105  can do this by bind the information graphs  210  together in a way such that the information graphs  210  can be handled like leafs in a book. This provides a layer of information graphs  210  called a Multilayer Information Graph as is shown in  FIG. 3 . Each one of the leaves has a tab-note with the name  310 . Should the multilayer information graph be closed the tab-notes  310  allow fast access to the single leafs by clicking on one of them as is shown at  320 . 
         [0046]    Another way to move through the various leaves of the multilayer information graph would be to move the mouse up and down with mouse button down as is shown at  370 . The information graph  210  is rotatable by moving the mouse sideward with mouse button depressed as is shown at  380 . The content of each page can be seen from both sides of the leaf. Each node of the information graph  210  is provided with a label  330  which is presented to the user  105  on the computer screen. This occurs even during rotation of the information graph  210 . 
         [0047]    The user  105  can click on an element of the leaf in combination with a special modifier key and the machine will select lines  350  from the element to related elements on the subsequent leaf. This is shown as the adjacent leaf in  FIG. 3  but could also be another leaf. This process can be “cascaded” using a cascading mechanism: in the first step lines are drawn to the elements on the adjacent leaf and in the second step lines are drawn from the elements in a further leaf. The user  105  will see a vertical network over all of the information graphs  210  presented in different leaves. 
         [0048]    In the illustrated example the user  105  can at once see which elements on the leaf “cells” are connected to the starting element “Parkinson&#39;s Disease” and to which organ they belong (leaf “Organs”). The leaves are presented in a transparent manner and it is possible to look from top, so that all of the information graphs  210  can be seen as an overlay  390 . Each one of the leaves can be blended in and out separately. 
         [0049]    Although the present invention has been described in terms of a preferred embodiment, it is not intended that the invention be limited by this embodiment. Modifications within the spirit of the present invention will be apparent to those skilled in the art. The scope of the present invention is defined in the claims that follow. 
         [0050]    The foregoing description of the preferred embodiment of the invention has been presented for purposes of illustration and description. It is not intended to be exhaustive or to limit the invention to the precise form disclosed, and modifications and variations are possible in light of the above teachings or may be acquired from practice of the invention. The embodiment was chosen and described in order to explain the principles of the invention and its practical application to enable one skilled in the art to utilize the invention in various embodiments as are suited to the particular use contemplated. It is intended that the scope of the invention be defined by the claims appended hereto, and their equivalents. The entirety of each of the aforementioned documents is incorporated by reference herein.