During the course of using a computer, a user may make mistakes in entering commands or have questions about how to accomplish a particular function or goal. Various levels of on-line help systems have been provided to assist users. A very simple level is one in which the system, in response to the entry of an erroneous command, outputs an error code or a short message. The user's response depends upon the user's knowledge which varies greatly dependent upon the user's training and experience with using computers. An experienced person usually would know the proper response, upon receiving an error message, but even experts often need help. A less experienced person would have to look up the answer in a manual or ask a more knowledgeable person what to do. Some computers are provided with on-line help systems in which full text or shortened descriptions of system commands can be accessed by a user pressing a help key. Such descriptions may or may not be helpful dependent upon the user's expertise and ability through trial-and-error methods to choose the right option. Such descriptions are general in nature and are not tailored to the specifics of the user's activity.
The above identified related application describes an intelligent help system which uses principles of artificial intelligence to suggest to the user, in response to the entry of a question or an erroneous command, one or more suggestions containing commands and actions the user might make, along with an explanation paradigm explaining why such suggestions were made and how they work. The system includes a rules base containing various generic rules to be applied in creating the suggestions and explanations. Such generic rules do the following: correct the spelling of a command, correct the spelling of arguments, correct the path, complete a command, change a command to one with similar meaning, select a command to satisfy the given command's preconditions, select a command whose intent matches the given goal, transform the given goal into a more general one, and break the goal into subgoals. The present invention resides in the manner of applying the above rule of changing a command to one with similar meaning.
Within prior art help systems, the closest prior art of which I am aware, is the common practice of providing precanned text that refers a user to some other area or place for an explanation of something that might be related or similar, e.g., "See command `xxx` in reference manual". Such referral is in the nature of a cross reference and does not provide the user with any suggestion of commands or actions to be taken by the user. Such referral leaves it up to the user to determine the degree of closeness or similarity to the user's goals.
The problem of using data processing techniques to determine closeness has been recognized in areas other than help systems. M. J. Darnell, "Learning Idiomatic Versus Compound Generic Command Names", report number HFC 54, January 1986, IBM Corporation, Human Factors Center, San Jose, Calif., investigated the ease of learning to use idiomatic commands in a computer system. Idiomatic commands use verbs with similar meanings for different operations, each different command being mapped to a different operation. No use is made in an intelligent help system and no discussion is made on determining any degree of closeness. R. E. Kimbrell, "Fuzzy", AI EXPERT (July 1988), 56-63, describes a method for determining, in response to a user's query into a data base management system, what records are "close" as opposed to an "exact" fit. The method involves continuous Boolean functions and counting the number of words, characters or two character snippets of text occurring in a record word or string compared against the query. No discussion is presented on using such a technique in an intelligent help system, nor of determining the degree of semantic closeness as is done in the present invention.
It is also to be noted that there are commercially available spell checking systems which use similarity of appearance, not meaning, to suggest to the user various correctly spelled words that the user might have intended to use instead of an incorrectly spelled word. Such technique involves applying different rules to pick up common spelling errors, e.g., transposition of characters, use of wrong single character, etc., but does not involve attempting to interpret the meaning.
The closest patents of which I am aware will now be discussed. U.S. Pat. No. 4,044,475--K. Fujisawa et al, TRAINING MACHINE FOR KEYBOARDS, describes a training apparatus in which a first word is displayed on a screen, and the user attempts to key in the same characters. As the user does so, a comparison is made of digital representations of the respective characters and the word on the screen is erased when correct characters are entered or the entire word is placed back on the screen when an error occurs. There is no notion of commands, except very loosely if the displayed word just happens to be a command, and certainly no notion of similarity or closeness especially of semantics.
U.S. Pat. No. 4,500,964--A. F. Nickle, DIALOG USER ERROR DIAGNOSIS, SEVERITY, AND HELP TECHNIQUE, describes a system for checking data entries for errors, and providing an error message if an error occurs. The patent does not describe how the error analysis is made and does not suggest nor teach anything about correcting erroneous commands by using a new command that is semantically similar to an erroneous command.
U.S. Pat. No. 4,587,520--B. Astle, CURSOR CONTROLLED PAGE SELECTION IN A VIDEO DISPLAY, describes a system in which a display presents various commands on a screen and the patent is concerned with how close a cursor physically is to the location of each command. The present invention is concerned with how close two commands are semantically, rather than how close a cursor is in proximity to a displayed command.
U.S. Pat. No. 4,648,062--S. E. Johnson et al., METHOD FOR PROVIDING AN ON LINE HELP FACILITY FOR INTERACTIVE INFORMATION HANDLING SYSTEMS, describes a system in which a user is presented with all commands which could be validly issued from the state or context in which a user enters a request for help or an erroneous command. Such system differs from the invention because it issues all valid commands and does not select commands based on semantic similarity. Further, the suggested commands described in such patent are not generated on the fly but are predetermined.
U.S. Pat. No. 4,680,729--J. E. Steinhart, METHOD AND APPARATUS FOR STORING AND UPDATING USER ENTERED COMMAND STRINGS FOR USE WITH OTHERWISE UNASSIGNED KEYS, involves associating commands with user definable softkeys. The system allocates a new key to a command if it finds there is currently no key assigned to the command. Such action is done by comparing the entered command literally with all stored commands to find an exact match. Close matches are not considered and there is no attempt to use semantics as a basis of assigning keys.
U.S. Pat. No. 4,701,130--D. R. Whitney et al., SOFTWARE TRAINING SYSTEM, describes a system for training users to program. A tape has stored thereon a voice channel describing a series of oral instructions along with corresponding target programs. After listening to a voice instruction, the user keys in a program and it is compared to a target program. If the entered program is correct, i.e., the same as the target program, the user is then presented with the next segment of oral instruction. If the entered program is incorrect or not entered within a predetermined period, the correct or target program is displayed. The patent does not discuss closeness nor semantic similarity.