Abstract:
A method, apparatus and computer program element are disclosed for selecting a term for inclusion in a glossary in a document handling or processing system in which a set of functions or rules are applied to the term in order to provide a probability measure for the terms being suitable for inclusion in said glossary.

Description:
FIELD OF INVENTION 
       [0001]    The present invention relates to a method, apparatus and computer program element for selecting terms for a glossary in a document processing system. 
       BACKGROUND OF THE INVENTION 
       [0002]    Glossaries are information repositories that hold information defining particular terms such as acronyms, specialist language or jargon, that are used in a collection of data or documents. In computer based document handling and processing systems, automatic links can be provided, such as hotlinks or hyperlinks, which provide for the automatic display of the glossary definition for a given term. 
         [0003]    In order to build such a glossary in a document processing system, the glossary terms must first be identified and selected from the documents to which the glossary will apply. Once selected, each term must then be defined in the glossary, in other words, and explanation of the acronym, specialist language or jargon must be entered. Each glossary term is then linked to each occurrence of the term within the relevant documents. If the documents or glossary are modified, the links to the terms need to be properly maintained. 
         [0004]    One problem with existing document handling or processing systems is that the identification of relevant glossary terms is a time consuming and laborious process. Furthermore, maintaining a glossary in view of modifications to the document to which it applies is also a time consuming and laborious process. 
       SUMMARY OF THE INVENTION 
       [0005]    An embodiment of the invention provides a method for selecting one or more terms for a glossary in a document processing system, the method comprising the steps of: 
         [0006]    a) receiving a term selected from a document; 
         [0007]    b) applying a set of one or more rules to the term, each rule being arranged to assign a result value to the term; 
         [0008]    c) applying a function to the term, the function being arranged to use one or more of the assigned result values to produce a probability value relating to the likelihood of the term being a candidate for inclusion in a glossary associated with the document; and 
         [0009]    d) presenting the term to a user as a candidate for inclusion in the glossary. 
         [0010]    The method may comprise the further step of comparing the probability value for the term against a threshold probability value and only if the probability value exceeds the threshold then presenting the term to the user as a candidate for inclusion in the glossary. A plurality of the terms with associated probability values may be presented to the user, the terms being presented in a list ordered by the associated probability values. One or more of the rules may produce result values based on the context of the or each term. The rules and function may comprise a Boolean function. 
         [0011]    If the user accepts the term then the term may be added to the glossary. If the term is added to the glossary then the user may be prompted to add a definition for the term in the glossary. If the user rejects more than a predetermined number of consecutive terms in the ordered list then no further terms may be presented to the user. The terms may be selected from the document by a spelling checking system. The terms may be selected from the document in response to user selection of the term. The result value for one or more of the rules may be recorded for a given term and correlated with the user selection or rejection of the given term so as to maintain a probability value for a result value resulting in the corresponding term being included in the glossary. 
         [0012]    Another embodiment of the invention provides apparatus for selecting one or more terms for a glossary in a document processing system, the apparatus being operable to: 
         [0013]    a) receive a term selected from a document; 
         [0014]    b) apply a set of one or more rules to the term, each rule being arranged to assign a result value to the term; 
         [0015]    c) apply a function to the term, the function being arranged to use one or more of the assigned result values to produce a probability value relating to the likelihood of the term being a candidate for inclusion in a glossary associated with the document; and 
         [0016]    d) present the term to a user as a candidate for inclusion in the glossary. 
         [0017]    A further embodiment of the invention provides a computer program element containing computer loadable instructions for enabling a programmable device or group of such devices to carry out a method for selecting one or more terms for a glossary in a document processing system, the method comprising the steps of: 
         [0018]    a) receiving a term selected from a document; 
         [0019]    b) applying a set of one or more rules to the term, each rule being arranged to assign a result value to the term; 
         [0020]    c) applying a function to the term, the function being arranged to use one or more of the assigned result values to produce a probability value relating to the likelihood of the term being a candidate for inclusion in a glossary associated with the document; and 
         [0021]    d) presenting the term to a user as a candidate for inclusion in the glossary. 
         [0022]    A further embodiment of the invention provides software for enabling a programmable device or group of such devices to provide apparatus for selecting one or more terms for a glossary in a document processing system, the apparatus being operable to: 
         [0023]    a) receive a term selected from a document; 
         [0024]    b) apply a set of one or more rules to the term, each rule being arranged to assign a result value to the term; 
         [0025]    c) apply a function to the term, the function being arranged to use one or more of the assigned result values to produce a probability value relating to the likelihood of the term being a candidate for inclusion in a glossary associated with the document; and 
         [0026]    d) present the term to a user as a candidate for inclusion in the glossary. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0027]    Embodiments of the invention will now be described, by way of example only, with reference to the accompanying drawings in which: 
           [0028]      FIG. 1  is a schematic illustration of a document processing system; 
           [0029]      FIG. 2  is a schematic illustration of elements of the system of  FIG. 1 ; and 
           [0030]      FIG. 3  is a flow chart illustrating processing carried out by the elements of  FIG. 2 . 
       
    
    
     DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS 
       [0031]    With reference to  FIG. 1 , a computer system  101  comprises a computer  102  connected to a data storage device  103  in the form of a disk drive. The computer  102  is running an operating system  104  and a document handling or processing application program in the form of a word processing application program  105 . The data storage device  103  is used to store a set of documents  106  which are created, edited and handled by the word processing application program  105 . The word processing application program  105  comprises a glossary agent program  107 , which is arranged to automatically select terms from one or more of the documents  106  for inclusion in a glossary  108  associated with one or more of the documents  106 . 
         [0032]    With reference to  FIG. 2 , the glossary agent  107  is arranged to receive input from a spelling checker  201 , which is part of the document processing application program  105 . The input is in the form of a list of words or phrases from a document being processed, which the spelling checker  201  has rejected either automatically or as a result of user input. These words or phrases are referred to as terms. The glossary agent  107  then processes each input term using a set of rules  202 , each rule being arranged to assign a result value or score to an input term. The glossary agent  107  then uses a function  203  to process the result values assigned by each rule to determine a probability value for the term being a candidate for inclusion in the glossary  108 . The glossary agent  107  then presents a candidate list of processed terms for a user to judge whether or not each term should be included in or excluded from the glossary  108 . Depending on the users input  204 , each processed term is either allocated to the glossary  108  or rejected and discarded. Each term stored in the glossary  108  includes a record of the result values assigned to it by each rule. When a term is stored in the glossary  108 , the user is prompted by the glossary agent  107  to add a definition for the term. 
         [0033]    In the present embodiment, four rules  202  are each arranged to assign one of a set of result values to each processed term. The rules are as follows: 
         [0034]    Rule 1: The term is not in the dictionary but appears more than three times with its particular spelling in the current document. The result value is true or false. 
         [0035]    Rule 2: The term appears capitalised in a non-capitalised context such as outside a title in the current document. The result value is true or false. 
         [0036]    Rule 3: The term appears more often than expected for its word type in the current document. The result value is a probability value where 100 is the expected amount and, for example, a result value of 130 represents 30% more often than expected. 
         [0037]    Rule 4: The term always occurs as part of the same short sequence of words in the current document. The result value is true or false. 
         [0038]    The function  203  is arranged, in the present embodiment, to combine the result values for each of the rules  203  to produce a probability value relating to the likelihood of the term being a candidate for inclusion in the glossary associated with the document. The function  203  is initialised with a base probability, that is, the probability of any given term being a glossary term. In other words, the base probability is the percentage of terms in a typical document of this author, size, or type that are already glossary terms, for example, 7%. In cases where the glossary is empty, the base probability is set to an arbitrary value. 
         [0039]    For terms that produce a Boolean result value of “true” for a given rule, the function is arranged to determine what percentage of words or phrases previously given a result of “true” by that rule have been accepted into the glossary. This percentage is then treated as the probability of the term for the given rule being a glossary term. For terms that produce a Boolean result value of “false” for a given rule, the function is arranged to determine what percentage of words or phrases previously given a result of “false” by that rule have been accepted into the glossary. This percentage is then treated as the probability of the term for the given rule being a glossary term. For rules, which produce an ordinal or percentage result value, the system evaluates the probability of previous terms having a similar score, for the given rule, being a glossary term and then treats this resulting probability as the probability for the given term. 
         [0040]    The function  203  is arranged to record the results of each such rule and to log against each result, an indication of whether or not the evaluated terms was subsequently included in the glossary. In this way, the function  203  is able to maintain the probability, for each rule, of a given term being a glossary term. This percentage is the percentage of terms for which a given rule evaluated to true or false and that have then been selected to be in the glossary. The percentage can be treated as a success rate for correlating the rule&#39;s results with the user&#39;s choice to add a word to the glossary. Thus the glossary becomes a super-set of words that that have been successfully predicted by the set of rules. 
         [0041]    Once the probabilities for each term have been determined by the rules  202 , they are combined by the function  203  to produce an average overall probability for the term being a glossary term. The overall probability is then compared to a threshold probability value. All terms with a probability equal to or greater than the threshold are included in the candidate list of terms for the glossary that is presented to the user. The user then selects terms from the candidate list for inclusion in or exclusion from the glossary  108 . By way of example, assume a term T was assigned the following result values by rules 1 to 4: 
         [0042]    T [true, false, 130, true] 
         [0043]    This set of result values would be converted into a set of probability values as follows: 
         [0044]    T [70, 7, 30, 80] 
         [0045]    This set of probability values indicate that, for all terms evaluated by rule 1 with a result value of “true”, 70% have been selected by the user for inclusion in the glossary. Similarly, for all terms evaluated by rule 4, with a result value of “true”, 80% have been selected by the user for inclusion in the glossary. Furthermore, according to rule 3, the term occurs with a frequency twice that for the norm for its word type. The base probability value is 7%, which is assigned to the result value for rule 2. These probability values are averaged to produce an overall probability of 46.75%. Given, in this example, a threshold of 40%, the term T is added to the list of candidate terms for inclusion in the glossary  108 . 
         [0046]    The processing carried out by the glossary agent  107  will now be described in further detail with reference to  FIG. 3 . At step  301 , the glossary agent receives a list of terms from the spelling checker  201  and processing moves to step  302 . From step  302 , each term in the list is processed in turn in accordance with the following four steps  303 ,  304 ,  305 ,  306 . At step  303 , the four rules  202  are applied to the term, assigning a set of result values and the results for each rule are recorded. Processing then moves to step  304  where the function  203  is applied to the set of result values for the term to produce an overall probability of the term being a glossary term. Processing then moves to step  305  where the overall probability value is compared the threshold probability value and if the overall probability value meets or exceeds the threshold, processing moves to step  306  where the term is added to the list of candidate terms for presentation to the user. From step  306 , processing returns to step  302  and continues as described above. If at step  305  the overall probability is below the threshold then processing returns straight to step  302 . If at step  302  all the terms in the list have been processed then processing moves to step  307 . 
         [0047]    At step  307 , the list of candidate terms for the glossary  108  is presented to the user and processing moves to step  308 . At step  308 , processing responds to the acceptance of any term by the user by moving to step  309  where the term is added to the glossary  108 . The acceptance or rejection of a given term is recorded by the function  203  against each of the rules  202  in order to maintain the record of the probability for each rule of a given term being a glossary term. Processing then moves to step  310  where the user is prompted to add a definition for the term. If at step  308 , a term is rejected by the user then processing moves to step  311  where the term is removed from the list of candidate terms and processing returns to step  308  to await further user input. Processing continues until all of the terms in the candidate list have either been accepted into the glossary or rejected. 
         [0048]    As will be understood by those skilled in the art, the rules may be selected from a larger group of such rules. The starting point for many rules may be the set of words in a given document. This could be a complete or partially complete document. The result value type can be varied between rules as long as the function is arranged to interpret the result values accordingly. In other words, rules provide a score and the function is arranged to identify the correlation with the existing glossary terms and any increase/decrease in the likelihood of a term being a glossary term given a certain result value. Examples of rules in this group are set out below: 
         [0049]    1) Filtering rules arranged to eliminate all words that are not nouns, adjectives or verbs. In the above embodiment, this rule is employed in the spelling checker. 
         [0050]    2) Detecting rules arranged to detect all words that are not in the dictionary, such as spelling mistakes or new terms. Again, in the above embodiment, this rule is employed in the spelling checker. 
         [0051]    3) Significance rules for determining the frequency of words in a given document to give an idea of their importance to the document. A word used a large number of times might warrant definition in the context of this document. Similarly, words only used once might also be selected as they might be indicating a key concept. 
         [0052]    4) Style rules arranged to identify patterns in an authors writing style. For example, patterns in the way terms are used in documents by an author can be detected and refined as the author builds their document portfolio. These patterns are then used to identify word sequences in new documents as they are created and hence identify potential new glossary terms. 
         [0053]    The record of result values and user inclusion or exclusion for each rule is kept to avoid a recalculation each time a rule is applied. A false result value can be as important as a true result value, as is whether a term was accepted or rejected. In some embodiments, the following percentages are maintained for each rule:
       1) The rule evaluated to true and the term was accepted into the glossary;   2) The rule evaluated to false and the term was accepted into the glossary;   3) The rule evaluated to true and term was rejected; and   4) The rule evaluated to false and term was rejected.       
 
         [0058]    The usefulness of the rule is dependent on how contradictory the values for these percentages are. For example, if a given rule scored a high percentage for “false and accepted” and a high percentage for “true and rejected” then this would be a significantly reliable rule. Similarly, if a rule scored highly for “true and accepted” and “false and accepted” then the rule would be less useful. This usefulness assessment enables the system to learn or improve over time. 
         [0059]    In a further embodiment, the candidate terms presented to the user are ranked by their respective overall probability values. In another embodiment, the probability threshold is omitted and all terms are ranked and presented to the user in the candidate list. The terms may be sorted in descending order of overall probability value. A cut-off point may be configured so that after a user rejects three consecutive terms in the list, no further lower ranking terms are presented. 
         [0060]    In another embodiment, the glossary agent is arranged to detect user input in relation to a term, which suggests that the term should be entered and defined in the glossary. For example, if a reader of a document double clicks on a particular term more than three times, the glossary agent may be arranged to flag the term to the author of the document for inclusion in a relevant glossary. In a further embodiment, the glossary agent may be arranged to present potential glossary terms to the user as they are typed. 
         [0061]    In another embodiment, candidate terms rejected by the user are stored in a rejected terms store and a “false” probability for each rule is determined from the rejected terms instead of using the base probability value. In a further embodiment, when a predetermined number of terms have been added to the glossary, the glossary agent is arranged to recalculate the overall probability value for each term in the glossary. The recalculation may include terms from the rejected term store, which may be then included in the glossary. 
         [0062]    It will be understood by those skilled in the art that the apparatus that embodies a part or all of the present invention may be a general purpose device having software arranged to provide a part or all of an embodiment of the invention. The device could be single device or a group of devices and the software could be a single program or a set of programs. Furthermore, any or all of the software used to implement the invention can be communicated via any suitable transmission or storage means so that the software can be loaded onto one or more devices. 
         [0063]    While the present invention has been illustrated by the description of the embodiments thereof, and while the embodiments have been described in considerable detail, it is not the intention of the applicant to restrict or in any way limit the scope of the appended claims to such detail. Additional advantages and modifications will readily appear to those skilled in the art. Therefore, the invention in its broader aspects is not limited to the specific details representative apparatus and method, and illustrative examples shown and described. Accordingly, departures may be made from such details without departure from the spirit or scope of applicant&#39;s general inventive concept.