EP1103025A1 - Mise en oeuvre informatique par une interface intelligente et adaptative a l'utilisateur - Google Patents

Mise en oeuvre informatique par une interface intelligente et adaptative a l'utilisateur

Info

Publication number
EP1103025A1
EP1103025A1 EP99936944A EP99936944A EP1103025A1 EP 1103025 A1 EP1103025 A1 EP 1103025A1 EP 99936944 A EP99936944 A EP 99936944A EP 99936944 A EP99936944 A EP 99936944A EP 1103025 A1 EP1103025 A1 EP 1103025A1
Authority
EP
European Patent Office
Prior art keywords
user
task
tasks
information
model
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Withdrawn
Application number
EP99936944A
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German (de)
English (en)
Inventor
Dina Goren-Bar
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Ben Gurion University of the Negev Research and Development Authority Ltd
Original Assignee
Ben Gurion University of the Negev Research and Development Authority Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Ben Gurion University of the Negev Research and Development Authority Ltd filed Critical Ben Gurion University of the Negev Research and Development Authority Ltd
Publication of EP1103025A1 publication Critical patent/EP1103025A1/fr
Withdrawn legal-status Critical Current

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Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/44—Arrangements for executing specific programs
    • G06F9/451—Execution arrangements for user interfaces
    • G06F9/453—Help systems

Definitions

  • the present invention relates to the field of computer operation. More particularly, the invention relates to an improved method for user operation of computers, by using an intelligent adaptive user interface, responsive to the user operations and competence.
  • WO 98/03907 to Horvitz et al. discloses an intelligent assistance facility helping the user during his operation.
  • This facility comprises an event composing and monitoring system, which creates high level events from combinations of user actions by collecting visual and speech information about the user.
  • the system uses the information to compute the probability of alternative user's intentions and goals or informational needs and changes the given assistance based on user competence.
  • this user assistance facility lacks flexibility in user characterization capabilities and the ability to contest with conflicts.
  • the system also does not consider the user's position with respect his tasks.
  • the invention is directed to a method for interactive, user adaptive operation of a computerized system by using an intelligent user interface.
  • Information about the user and the user tasks are collected by monitoring the user operations, and stored. Monitoring includes counting the number of times the user requested for help, the number of user errors, the time intervals between consecutive user operations and seeking after user preferences.
  • information about the user is collected by a questionnaire or an interview.
  • a preliminary dynamic stereotype user model based on predetermined default values and/or on the information about the user is built, as well as a task model for the user.
  • default values are extracted from pre-programmed assumptions, researches and studies of the addressed population of users.
  • a preliminary adaptation level of the interface to the user is provided.
  • the user task is characterized by adaptation to the user, based on the collected information and the user model. Preferably, if after a predetermined period there is no user operation, assistance is offered to the user. Requests are received from the user, and executed by operating an adaptive dialog manager for the specific user, in case they are correct requests (successes). On the other hand, if the requests are incorrect (failures), instructions/help is provided by operating an adaptive dialog manager.
  • information about the user is stored in a user protocol.
  • User macros and/or batch automated files are generated and or updated according to identified sequences of operations from the protocol, which are typical for the user.
  • the preliminary user model, the user tasks and the user characteristics are updated in response to processed information from the user protocol and to successes/failures during operation of the user observed by the dialog manager.
  • the system provides the user help in case when no task is selected for execution and corrective instructions, due to failure analysis.
  • the user characteristics are updated.
  • the preliminary adaptation is modified, and the dialog manager interacts with the user according to the updated user model, user tasks and user characteristics.
  • the user model is constructed by defining hierarchy of user stereotypes and associating characteristics for each user stereotype, wherein a value,, from a predetermined scale, is assigned for each characteristic.
  • the user preliminary model is characterized by selecting a set of stereotype attributes.
  • the preliminary characterization is updated by modifying/adding user characteristics and/or their values based on observation.
  • contradictions between user characteristics are set by obtaining all the user relations to different user stereotypes and characteristics, all the user certain characteristics based on observation, and for each user characteristic with more than one value, selecting only the highest value and its associated stereotype.
  • the task model is constructed by collecting and storing information about the user tasks, needs and functions and interacting with the utilities of the inherent operating system in a manner enabling execution of these utilities by the interface.
  • Inherent utilities comprise editing, printing, reading utilities and connecting utilities to other computer networks.
  • the inherent operating system comprises connecting utilities to other networks, such as a computer network, a web-based network, a telephone network, a cellular network, or a cable TV network.
  • the lowest task level is determined and each task is decomposed to a set of sub-tasks necessary to accomplish the task. Each sub-task is also decomposed iteratively, until the lowest task level is reached, and the specific sequence of tasks and/or sub-tasks is then defined. As a result, a set of individual tasks and/or jobs is output into the dialog manager.
  • the user protocol is processed by counting and sorting the number of user failures and correct operations for each task, and seeking after user macros during operation and counting the frequency of each macro.
  • the user model is updated updating the user level of knowledge, the user tasks, the user macros and the user characteristics.
  • the user level of knowledge is updated by seeking after new information about the level of knowledge, updating or using the current level of knowledge, or using default parameters as the current level of knowledge.
  • Each user task is updated by adding a task, in case when no task exists.
  • Each user macro is updated by first seeking after an existing macro. If no macro exists, the frequency of any identified sequence of user operations is counted. For any existing macro, the mean frequency per session and the general frequency of all previous sessions is calculated. A macro is generated from the identified sequence, in case when no existing macro is identified, and the frequency of the sequences is equal to or higher than a predetermined value. The mean frequency per session and the mean frequency of previous sessions is stored for each generated macro.
  • interaction between the user and the dialog manager is carried out by a keyboard with suitable display, soft touch sensors, a microphone and a speaker, a Personal Digital Assistant (PDA), a cellular-phone, or a television (TV) remote -control unit, and suitable display, which may be a monitor, a soft touch display, or an interactive TV set.
  • PDA Personal Digital Assistant
  • TV television
  • the invention is also directed to a computerized system, operated by the described method.
  • the computerized system is not limited to a specific kind, and may be any kind of a PC, a workstation, a mini-computer, a main-frame computer, a client-server system, an INTERNET server, a telemedicine network etc.
  • Fig. 1 is a block diagram of a computerized system operated by an intelligent user interface
  • Fig. 2A is a flowchart of the operations employed by the invention for the adaptation process of the interface to the user;
  • Fig. 2B is a flowchart of the operations employed by the invention for the adaptation process of the interface to the user;
  • Fig. 2C is a flowchart of the operations employed by the invention for the adaptation process of the interface to the user;
  • Fig. 2D is a flowchart of the operations employed by the invention for the adaptation process of the interface to the user;
  • Fig. 2E is a flowchart of the operations employed by the invention for the adaptation process of the interface to the user;
  • Fig. 3A is flow chart of user representation by a preliminary user model
  • Fig. 3B is flow chart of user representation by a preliminary user model
  • Fig. 4A is a flow chart of an intelligent help process according to the invention.
  • Fig. 4B is a flow chart of an intelligent help process according to the invention.
  • Fig. 5 is a flow chart of the process of guiding the user according to the invention.
  • Fig. 6 is a flow chart of user protocol processing according to the invention
  • Fig. 7 is a flowchart of user model updating according to the invention
  • Fig. 8 is a flowchart of user macro updating according to the invention.
  • Fig. 9 is a flowchart of updating of the user's level of knowledge according to the invention.
  • Fig. 10 is a flowchart of updating of the tasks in the user model, according to the invention.
  • Fig. 11 is a flowchart of updating of the attributes in the user model, according to the invention.
  • Fig. 12 is a flowchart of an example of Hierarchical Task Analysis (HTA);
  • Fig. 13 illustrates screen output displaying the main screen functions used for user modeling according to the invention
  • Fig. 14A to 14F illustrate screen outputs displaying each function from the main screen
  • Fig. 15A to 15G illustrate screen outputs displaying steps of task modeling according to the invention
  • Fig. 16A to 16C illustrate screen outputs displaying steps of adaptation of the interface to a specific user according to the invention.
  • Fig. 1 is a block diagram of a computerized system 10 comprising hardware and software, which is operated by the user 11 via an inteUigent user interface 12.
  • Interface 12 interacts with user 11 by employing a dialog manager 13 which coUects instruction and information from the user 11 and tasks he likes to carry out, and in return offers the user 11 help and/or instructions for further operations required to accomphsh the user tasks.
  • the dialog manager 13 may interact with the user with a keyboard, soft touch sensors, microphones, speakers, an interactive television (TV) and a visual display which may comprise soft touching icons.
  • TV interactive television
  • Information about the user which is coUected in advance and/or continuously during operation, is stored in a user database 14 and is then exploited by interface 12 to buUd a dynamic user model which is continuously updated during operation.
  • information about the user tasks which is also coUected in advance and/or continuously during operation, is stored in a task database 15 and is then exploited by interface 12 to buUd a task model.
  • Interface 12 communicates with the computerized system 10 which executes the desired user tasks by decomposing and executing each task according to the task model. Interaction with the user is carried out by interface 12 with adaptation to the user's competence and tasks in accordance with information (about the user) extracted from the updated user model and from his task model.
  • the user is modeled by stereotype model from the coUected information.
  • a flowchart of the operations employed by the invention for the adaptation process of the interface to the user is presented in Fig. 2A.
  • the first step 20 is identifying the user by software inputs (user name and or a password) or by inputs provided by hardware, such as smart cards, bar-codes, sensors, voice recognition devices etc.
  • the next step 21, is loading a preliminary user model.
  • a flow chart of user representation by a preliminary user model is Ulustrated in Fig. 3A.
  • the interface checks if there is an existing model of the user. If not, the first interaction is a short interview with the user and building a model in step 31.
  • the next step 32 is to load the model into the interface.
  • questions are introduced to the user by the dialog manager 13 of Fig. 1, so as to coUect preliminary information about the user and -his tasks.
  • This information comprises user personal detaUs, occupation, position, experience with the software that executes the user tasks, and experience with si Uar software.
  • several screens of the software comprising most of the software functions are introduced and the user is asked to mark on screen the main tasks selected (by him) for execution. The user is also asked to specify the tasks in which he faced difficulties during operation and of what kinds.
  • Information about missing functions/utilities expressed by the user is coUected, as weU as user preferences, e.g., how the user would like to execute a specific task. If, from any reason, the user refuses to answer to some (or aU the) questions, default values or a default are loaded. These default values are extracted from previous researches and/or studies of the addressed population of potential users.
  • the first step 33 is seeking after the existing level of knowledge about the user, which may result from previous interview and/or previous session.
  • the user is asked to supply required (or missing) information.
  • the user response is checked. If the user refuses to answer or not responding from any reason, a default user model is generated at step 36. In case when the user cooperates, a user model is generated in step 37, according to the provided information.
  • a preliminary stereotype user model is buUt and loaded at the second step 21.
  • a hierarchy of user stereotypes is defined to construct user classifications.
  • the user may be associated with one or more stereotypes in any hierarchy level. For instance, a user may be an athlete and an engineer with blue eyes.
  • Each stereotype is associated with different characteristics where each characteristic having a weighted value from a pre-determined scale. According to the invention, this stereotype user model is able to settle contradictions between different characteristics. If there is no preUminary information about several characteristics, pre-programmed stereotype assumptions are provided based on other (known) stereotypes. For example, if the user is a software engineer, a high level of competence in computer operation is assumed.
  • the characteristic having the lower level in the hierarchy wUl be selected.
  • observation on the user leads to conflicts between the observation and the taken stereotype assumption which are settled by selecting the observed characteristics.
  • Other alternatives are determinin a necessity level for each characteristic or introducing a question to the user.
  • the next step 22 is to load the stored information about the user task and function/position.
  • the interface wiU handle differently users from different positions, even for executing the same task For example, in case when two different users, a software engineer and a secretary have the same task, like composing a letter, the interface wUl interact with them differently, based on the assumption that the level of knowledge of the software engineer is much higher than the level of knowledge of the secretary.
  • the system is ready for the next step 23, in which the first adaptation to the user is implemented.
  • a flowchart of the first adaptation is shown in Fig. 2C.
  • the first user model is buflt.
  • an interface type which matches the specific user model and user tasks is loaded.
  • Each user model emphasizes different attributes such as font size, density of displayed information, preferred mode of interaction (e.g., voice, editing, printing, soft touching etc.) as weU as tasks. For instance, if the user age is over 60, interaction may require large icons, (relatively) few options displayed, easy communication, simple tasks, a soft touch screen etc.
  • the interface In the next step 24, the interface expects the user to interact with the system. If after a predetermined period of time T, there is no reaction from the user the system assumes that the user is facing a difficulty and then in the next step 25 a smart (inteUigent) help is offered to the user.
  • Fig. 2B shows the content of smart help.
  • the system guides the user according to the current user model and level of adaptation which corresponds to the current user model. The level and kind of help is determined according to the preliminary user model.
  • the inteUigent interface starts to coUect more information about the user by monitoring his operations.
  • the reaction time of the user is measured and stored in the database and will be used later to update the user model.
  • FIG. 4A A flow chart of an inteUigent help process is iUustrated in Fig. 4A.
  • the interface checks if there is an existing task which is selected as a goal by the user. If not, the next step 41 is to offer the user to select one. If there is a task which is a user goal, the next step 42 is to load this task.
  • Fig. 4B is a flow chart of task selection.
  • a list of tasks and/or macros is displayed to the user for selection.
  • the system checks if the user has selected a task. If not, the time with no task selection is counted at step 47, for a case when the user needs help. If a task is selected, the selected task, as weU as the time lapsed untU the selection of this task, are stored in the current session log file, at step 45. The time lapses may indicate that some of the user tasks are his main tasks within the session, since they occupy a major portion of his time. Both time counts indications about the user preferences, as weU as competence and/or experience, and used later to update the user model.
  • inteUigent help if the user reacts after few seconds the system classifies him as a user with high level of knowledge. On the other hand, if even after help is offered the user still does not react, the system may offer him more intensive help or even provide him instructions how to proceed.
  • a request for operation is received from the user and stored in a user protocol for the user reactions. This information about requests from the user is also exploited later to update the user model. For example, if the user requested an advanced function of the operated software, this may indicate on high level of knowledge.
  • Fig. 2E is a flow chart of receiving a request from the user.
  • the system checks if any request (from the user) is received. If yes, at step 213, the request is stored in the current session log file. If no, at step 210, the system checks if the user wishes to terminate the current session.
  • the request is set to "go to end” in step 211.
  • the system displays instructions for the user, according to step 212.
  • step 27 the system checks if the request from the user is correct from the aspect of the operated software. If the request is correct, the next step 29 is execution of the request. If the request is incorrect, step 28 is provides corrective instructions to the user, and going back to step 26. According to step 208, shown in Fig. 2D, the request from the user is executed and a success is stored in the current session log file, for further adaptation.
  • a flow chart of guiding the user is Ulustrated in Fig. 5.
  • the interface checks the kind of error resulted from the user request.
  • the next step 51 is to offer a corrective operation (solution) to the user.
  • information about the error type, solution type is stored in the log file of the current session, as weU as the occurrence of the error.
  • the number of successes (correct requests) and faUures (incorrect requests) is stored is the user protocol, as weU as the kind of corrective instructions provided to the user. This information is used to update the user model. After execution of the first request of the user, if after checking the kind of the request at step 201, the request is different than "go to end", the next request from the user is received and steps 26 to 29 of Fig. 2A are repeated iteratively, untU aU requested tasks are executed, where at each iteration more information about the user is coUected.
  • the interface automaticaUy processes the user protocol to extract the required inferences about the user.
  • a flow chart of processing of the user protocol is illustrated in Fig. 6.
  • successes as weU as faUures are sorted and counted .
  • Consecutive user operations are sought at the next step 61 so as to identify potential macros.
  • identified sequences and their corresponding frequencies during the current session are stored in the session log file.
  • Sequences of typical user operations are sought in the next step 202 of Fig. 2A. Identified sequences are sorted and their frequency is counted . A user macro is generated automaticaUy in any case when the frequency of a sequence is higher than a predetermined value.
  • This processed information is used to update the user macros. For example, if the user interacts with a word processor, and the user has some typical preferences like having red header with bold and italic fonts comprising his name and date whUe typing letters, a macro that sets these kind of header is generated and operated automaticaUy every time the user operates the word processor. This macro is updated according to the user operation at the next time he operates the same word processor.
  • Fig. 8 is a flowchart of updating process of the user macros.
  • the first step 80 is to seek after an existing macro. If there is an existing macro, the mean frequency of that macro during the current session, as weU as the general frequency for aU past sessions, are calculated at step 82 and stored in the database. If no macro is identified, the frequency of each sequence is measured at step 81. If this frequency is less than three (or any other predetermined value) times per session, no macro is generated. If the this frequency is over than three (or any other predetermined value) times per session, a macro is generated for that sequence at step 83. The mean frequency of the new macro during the current session, as weU as the general frequency for aU past sessions, are calculated and stored in the database.
  • the final step 203 in the flowchart of Fig. 2A is updating the prehminary user model according to the information coUected at the protocol during his operation. This updated user model is employed during the next interaction with the user.
  • Fig. 7 is a flowchart of the updating process of the user model.
  • the user's level of knowledge is updated according to the processed information from the user protocol.
  • the user tasks are updated according to the frequency of each kind of user task. If no task exists, the next task is added.
  • the user's modes of operation stored and processed in the user protocol is updated at the next step 72.
  • the final step 73 is updating the user characteristics in case of a conflict or when a new characteristic is disclosed after processing the user protocol.
  • Fig. 9 is a flowchart of updating of the user's level of knowledge.
  • the interface checks there is a new information about the level of knowledge. If not, the next step is to check if there is any level of knowledge related to the user. If not, a default value is inserted at the next step 92. If there is a new information from step 90, the next step 93 is to update the level of knowledge.
  • Fig. 10 is a flow chart of task updating.
  • the system checks, at step 110, if there are existing tasks. These tasks may be system tasks (saving, printing etc.) which are not included within the user model, or a" utility in a new software (for instance, labels in Microsoft Word). If not, the frequency of each task is calculated, and the task is analyzed in step 103, looking after regular patterns which are important for starting. These patterns may be, for instance, reading E-maU in the beginning or in the end of each session, or background tasks, like looking after specific information in the Internet, on line E-maU or optimization, which continue to run in paraUel with (other) current user tasks.
  • Fig. 11 is a flowchart of updating the user characteristics.
  • the system checks is there any existing attribute in the database of the user model. If no, at step 112, an attribute is added and a corresponding value is assigned to the associated user characteristic. If yes, at the next step 111, the system checks if the new value of the characteristic equals the old value. If yes, there is no conflict. If no, this i an indication of a conflict (contradiction), between user characteristics, and conflict resolution is appUed at step 113, in which the value of the characteristic with the lowing hierarchical level is selected, or values are assigned according to the level of certainty for each characteristic, or values are selected according to observations, or defining necessity level for each characteristic.
  • task modeling is required in addition to user modeling.
  • Task modeling represents operations that should be carried out by the user to achieve his goals.
  • a task modeling system coUects inputs from three information sources: the customer, the user(s) and the designer of the computerized system.
  • the customer e.g., a managing director in an organization
  • inputs e.g., answering a questionnaire
  • the users provide inputs about their goals, preferences and needs required for functioning.
  • the system designer provides inputs which are based on inputs from the customer and the user together with his experience in task analysis and definition.
  • the task modeling system provides the dialog manager two kinds of outputs: individual tasks, each comprising operations and sub-tasks that construct the task, and definition of each user position which is represented by the coUection of aU tasks executed by an individual user.
  • Task analysis or decomposition
  • HTA Hierarchical Task Analysis
  • HTA is an iterative process where each task may be decomposed to sub-tasks and so fourth untU one of a set of pre-determining basic operations is reached.
  • HTA is easy to understand both to the user and to the system designer and may be presented graphicaUy or verbaUy.
  • the specific sequence of tasks and/or sub-tasks is defined, including their attributes. These attributes may comprise the timing of carrying out the task/sub-task, a manual or a computer oriented task/sub-task, or any combination of them, and the control structure of the task/sub -task.
  • the control structure defines if the task is carried out seriaUy, or in paraUel or iteratively, or if the execution of the task is conditioned.
  • HTA An example of HTA is illustrated in Fig. 12.
  • the task is writing a document using a word processor.
  • the main task 120 is divided to two tasks: open an existing file 101 and begin a new file 122.
  • Task 122 is divided to three secondary tasks: load editing screen 123, edit 124 and save 125.
  • the save task 125 is divided to four sub-tasks: name the file 126, select drive for file' saving 127, auto-save 128 and save the file in the default drive 129.
  • task 121 may also be divided to sub-tasks and then to basic operations. Other (known) methods of task analysis may also be used by the present invention.
  • the dialog manager After modeUng the user by the stereotype user model and the task by task analysis the dialog manager operates an adaptation process to the user model, which is derived from the user model according to his competence and level of knowledge in different relevant subjects. Several adaptation levels like maintenance, moclifying defaults, monitoring the user operations, settling conflicts and updating the user model may exist.
  • the user model is updated by modifying current values of existing characteristics and/or adding new characteristics.
  • an initial adaptation level is determined according to the user model, based on the assumption that a 5 years old chUd does not read and write, is not able to operate a keyboard and may have difficulties with smaU detafls on the display.
  • the screen displays large icons, the background is taken from a cartoon film, instructions/help are given vocaUy and requests from the user are received by soft touching icons on the display. Further adaptation which is responsive to observations on the chUd is activated during operation.
  • a Microsoft Windows environment was selected, comprising three demonstrations of the user modeling, the task modeUng and adaptation to the user model.
  • the user model is implemented using Microsoft Access.
  • Implementation of the user modeling is carried out by the main screen, as shown in Fig. 13.
  • BasicaUy the basic information about the user may be inserted by the system customer and the user model is buUt accordingly, being updated during operation.
  • the first function in the main screen is estabUshment of a specific user, as shown in the screen of Fig. 14A.
  • Basic user detafls like user name, user number, date of estabUshment and comments about the user in accordance with different categories (e.g., education and prior interaction with computers).
  • the second function in the main screen is relating categories to the user, as shown in the screen of Fig. 14B.
  • the user is associated with different stereotypes (e.g., engineers, industrial engineers, industrial engineers speciaUzed in information systems and psychologists).
  • the input from the system customer may be skipped, and interaction with the user may begin (as explained before) even without any detafls about the user. Instead, user selected default values are loaded.
  • the third function in the main screen enables to overwrite attributes for each characteristic representing the user, which are used as absolute values, as shown in the screen of Fig. 14C. Different user categories are defined with associated values.
  • each user category is associated with different characteristics (e.g., associating education period and level of computer education with the category of industrial engineers) by weighted association, as shown in the screen of Fig. 14E. This weighted association is used in case of conflicts between observed data and the user model.
  • the last function in the main screen is generating (or printing) a user report, as shown in the screen of Fig. 14F. This report is used for monitoring the user model in the interface.
  • Microsoft Word 6.0 (word processor) is selected for demonstrating the process of task modeUng.
  • word processor word processor
  • Several modification are implemented in Word for task definition.
  • the default HNORMAL template is modified by adding "users" menu which comprises a "dialog" utiUty, as shown in the screen of Fig. 15A. This modification enables aU previous functions of Word together with additional functions. Since each category of users carries out its typical tasks which are defined in the template, different required styles as weU as special tools for each task are defined and saved as *.dot files.
  • each template is associated with specific help files in several levels, which are normal read only Word (*.doc) files which are opened by special icons from the tool bar or alternatively by from specific menus.
  • a specific screen for selection from several options is displayed, as shown in the screen of Fig. 15B.
  • These options are related to tasks of an un-experienced user, a secretary and students.
  • Other options like a screen with Qtext word processor (QTX) format, general purpose screen and article typing screen are available.
  • Tool bars are adapted to the task according to coUected information. For instance, a tool bar containing only the basic functions for editing and printing is displayed to an un-experienced user, as shown in the screen of Fig. 15C.
  • Other users experienced in QTX who face difficulties with icon size may use a "QTX compatible" screen, shown in the Fig. 15D.
  • Another screen, shown in Fig. 15E is dedicated for preparing an academic article. This screen enables typing in two columns as weU as inserting tables and graphical objects into the text.
  • the screen shown in Fig. 15 F contains several tasks which are typical to a secretary (e.g., financial transfers, typing a memorandum, typing a fax cover sheet and typing a meeting protocol). Selecting a financial transfer option, for instance, leads to a dedicated screen for that task, as shown in Fig. 15G.
  • AU dedicated (selectable) formats are prepared in advance according to previous standards. There is also a possibility that the user creates a form and adds it to the screen for future use.
  • Adaptation to the user is expressed in this example by forming the screen as weU as the format and content of the help program.
  • a screen which defines the level of user is displayed, as shown in Fig. 16A.
  • the user may select the "novice” box or the "advanced” box. If "novice” box is selected, instead of a standard (and compUcated for "novice") Word toolbar, a screen with help toolbar comprising six help boxes (Scope, AppUcable Documents, Engineering Requirements, Qualification Requirements, Preparation for DeUvery and Notes) about different subject is displayed, as shown in Fig. 16B.
  • SRS Software Requirement Specifications
  • the present invention is not restricted to Windows environment, and may be carried out in different environment of different data bases, such as relational, object oriented and others.
  • the invention can be carried out in a great variety of ways, employing more than one technique from those described above, aU without exceeding the scope of the invention.

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  • User Interface Of Digital Computer (AREA)

Abstract

L'invention concerne la mise en oeuvre interactive et adaptative à l'utilisateur d'un système informatisé, cette mise en oeuvre consistant à utiliser une interface utilisateur intelligente. Les informations concernant l'utilisateur et ses tâches sont collectées puis mémorisées, un modèle utilisateur préliminaire dynamique stéréotypé étant construit sur la base de valeurs implicites prédéterminées et/ou des informations concernant l'utilisateur. Un modèle de tâches est également construit pour ledit utilisateur, auquel est par ailleurs fourni un niveau d'adaptation préliminaire de l'interface, la tâche utilisateur étant caractérisée par l'adaptation entre cette tâche utilisateur et l'utilisateur lui-même. Après une période prédéterminée sans mise en oeuvre utilisateur, ledit utilisateur dispose d'une assistance. Les requêtes de cet utilisateur sont reçues et si elles sont correctes, elles sont ensuite exécutées par mise en oeuvre d'un gestionnaire de dialogue adaptatif spécifique dudit utilisateur. Si ces requêtes sont incorrectes, ce gestionnaire de dialogue adaptatif fournit des instructions/une assistance. Un protocole utilisateur représentant les informations sur l'utilisateur, collectées pendant sa mise en oeuvre, est alors généré et/ ou traité. Les macro-instructions et/ou les fichiers de lancement automatique représentant les différentes mises en oeuvre utilisateur par une suite d'opérations typiques de cet utilisateur sont générés et/ou actualisés. Le modèle utilisateur préliminaire, les tâches utilisateur, et les caractéristiques utilisateur sont également mis à jour en réaction aux informations traitées à partir dudit protocole utilisateur et aux succès/échecs survenus pendant la mise en oeuvre utilisateur observée par ledit gestionnaire de dialogue. Dans le cas d'un conflit entre les caractéristiques provenant des informations collectées le modèle utilisateur stéréotypé intervient, et les caractéristiques utilisateur sont mises à jour. Le niveau d'adaptation préliminaire du gestionnaire de dialogue est modifié, et l'interaction avec l'utilisateur effectuée par l'intermédiaire de ce gestionnaire de dialogue en fonction du modèle utilisateur, des tâches utilisateur, et des caractéristiques utilisateur ayant été actualisés.
EP99936944A 1998-08-06 1999-08-05 Mise en oeuvre informatique par une interface intelligente et adaptative a l'utilisateur Withdrawn EP1103025A1 (fr)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
IL12568498A IL125684A0 (en) 1998-08-06 1998-08-06 Method for computer operation by an intelligent user adaptive interface
IL12568498 1998-08-06
PCT/IL1999/000432 WO2000008556A1 (fr) 1998-08-06 1999-08-05 Mise en oeuvre informatique par une interface intelligente et adaptative a l'utilisateur

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AU5190699A (en) 2000-02-28
IL125684A0 (en) 1999-04-11

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