GB2336697A - Alerting user-processing sites as to the availability of information - Google Patents

Abstract

Data files are received by a central processing system (104) and these files analysed to determine whether they contain information which is relevant to user-specified characteristics. On detecting such a condition, an alert signal is supplied to the respective user (115). The incoming data files are analysed with respect to common data characteristics to generate common category associations. The data files are then processed with respect to user-specific data characteristics. The user-specific data characteristics include examples of the common data characteristics and the specific processing procedures make use of the previously defined common category associations.

Description

1 1 j 2336697 ALERTING USER-PROCESSING SITES AS TO THE AVAILABITLITY OF

INFORMATION The present invenflon relates to the alerting of user-processing sites as to the availability of data associated with user-specific characteristics.

Introduction

Search engines are known for identifying particular text files of interest from large, often distributed, databases. These known processes operate by performing free text searching in which a user specifies words which they believe are contained within the target file.

A problem with this known technique is that a simple enquiry can generate thousands of hits many of which are totally irrelevant to the user's needs. Furthermore, many relevant files may be missed because they do not actually contain the specific words chosen.

Procedures for classifying volumes of data so as to facilitate subsequent searching are known but the classification process often involves manual intervention thereby making it time consuming and prone to human error. Procedures are known for processing data files so as to determine whether the file should be associated with a particular information category. The known processes require machine readable association files (or outline files) which are used as a basis for analysing an incoming data file. The processing of a data file in combination with an outline results in a numerical score value being produced, defining an extent to which the data file is relevant to a particular category. Thereafter, a decision may be made as to whether the file should be included in the category by a threshold comparison.

In practical systems, thousands of such outine files would be required in order to provide a useful level of categorisation. The applicant's copending 1 1 /-11 2 British patent application (DGC-Pll-GB) describes a procedure for automating the generation of outline files by making reference to flies that have already been placed in the category and by making reference to files that are not appropriate to the category. In this way, new categories may be identified and appropriate outline flies constructed.

Outline flies work well if the size of incoming data files is similar to the size of the files referred to during the outline file generation process. If an incoming data file is smaller than the, preferred size, score values may be adjusted as described in the applicant's co-pending British patent application (DGC-P12-GB). Alternatively, if an incoming data file is much larger than the preferred size, the file may be divided into a plurality of file sections whereafter the categorisation process is performed for each of the sections, as described in the applicant's co-pending British patent application (DGC P13-G13).

Some categories may be considered as being particularly important to users and users may wish to receive immediate notification upon particular files being detected. Although many categories may be included within a system, these categories may be less than perfectly adequate in terms of defining the highly important issues of interest. Under these circumstances, specific outline files could be generated for a particular application. However, it is appreciated that such outline flies are probably only of interest to particular users and the duration over which these outline flies are required may be relatively short. Thus, it is difficult to justify the generation of outline files, in commercial terms, for specific user applications.

Summary of The Invention

According to a first aspect of the present invention, there is provided a method of alerting a user processing site as to the availability of data associated with user specified characteristics, comprising a first processing 3 step of analysing incoming data with respect to common data characteristics to generate common category associations; a second processing step of analysing said incoming data with respect to userspecific data characteristics to generate user-specific associations; and a third processing step of generating an alerting signal to the effect that user-specific associations have been generated, wherein said userspecific data characteristics include examples of said common data characteristics,. and said second processing step makes use of said common category associations.

In a preferred embodiment, incoming data flies are analysed to make common category associations prior to making user-specific categorisations.

Preferably, the common category associations are written to an association table.

In a preferred embodiment, incoming data files are analysed for alert conditions with respect to a plurality of users. Preferably, each user is invited to select common categories, to define free text, to define a title andlor to define a country of origin.

According to a second aspect of the present invention, there is provided a data processing system configured to analyse incoming data files and to generate alert signals to a user if a data file is detected as being relevant to characteristics defined by a said user, comprising first processing means for analysing incoming data files with respect to common data characteristics to generate common category associations; second processing means configured to analyse said incoming data files with respect to user-specific characteristics to generate user-specific associations; and a third processing means for generating an alerting signal to the effect that user-specific associations have been generated, wherein said second processing means analyses user-specific data characteristics having referenced common category associations defined by said first processing means.

1 4 In a preferred embodiment, a communication link is maintained between the processing system and a user system and relaying means are configured to relay an alert condition upon detection of said condition.

Preferably, memory means are configured to store outline association files, wherein the processing means is configured to analyse data files with reference to the outline files.

Brief Description of The Drawings

Figure 1 shows a data distribution environment in which data is received from a plurality of data sources; Figure 2 details a data processing, storage and retrieval system shown in Figure 1, including a central processing system, a user specific processor and a plurality of subsidiary processors; Figure 3 identifies procedures performed by the data procession, storage and retrieval system shown in Figure 1; Figure 4 details the process for generating common characteristics for association with data flies identified in Figure 3; Figure 5 details the process for generating or modifying an outline file identified in Figure 4; Figure 6 shows a terminal display of outline files represented graphically; Figure 7 details an outline file from which the display shown in Figure 6 is generated; Figure 8 shows a diagrammatic representation of the file data shown in Figure 7, Figure 9 details process 302 for the generation of user-specific characteristics; Figure 10 details the process identified in Figure 9 for generating an alert outline file; Figure 11 shows a visual display at a user terminal, inviting a user to provide input information; Figure 12 shows an example of an outline file representing user alert specifications;

Figure 13 represents a structure derived from the file shown in Figure 12; Figure 14 shows an example of a source data file; Figure 15 details a subsidiary process shown in Figure 2; Figure 16 details operations performed by the subsidiary process detailed in Figure 15; Figure 17 shows a plurality of rulebases produced by the process shown in Figure 16 and stored in the memory identified in Figure 15; Figure 18 details procedures performed by the data processing system 104 in response to receiving a new data file; Figure 19 details procedures for the processing of data to determine associated preferred terms shown in Figure 18; Figure 20 details a triggering phase identified in Figure 19; Figure 21 details a scoring phase identified in Figure 19; Figure 22 details a list generation phase identified in Figure 19; Figure 23 details a table constructed by the central processing system shown in Figure 2; Figure 24 details a linked list; Figure 25 details procedures for performing a search in response to a user request; Figure 26 shows an example of a common data associated file.

Detailed Description of The Preferred Embodiments

The invention will now be described by way of example only with reference to the above identified drawings.

6 A data distribution environment is illustrated in Figure 1 in which data, received from a plurality of data sources 101, 102, 103 is supplied to a data processing, storage and retrieval system 104. Data sources 101 and 102 supply data directly to processing system 104 while data source 103 supplies data via a local area network 105, thereby allowing user terminals 106 and 107 to gain direct access to their local data source 103.

The processing system 104 provides access to a plurality of users, such as users 111, 112, 113, 114, 115, 116 and 117. User 111 has direct access to the processing system 104 while users 112, 113 and 114 gain access to the processing system 104 via the Internet 118. Users 115, 116 and 117 exist within a more sophisticated environment in which they have access, via a local area network 119 to their own local database system 120 in addition to a connection, via an interface 121, to the data processing system 104.

All incoming data from data sources 101 to 103 is categorised with a key word in seven separate fields, comprising "market sectoe', "location",

99company name-, -publishe', "publication date" and "scope". Users, such as users 112 to 117 may specify almost any term as the basis for a search and are then prompted by an equivalent word or phrase which constitutes more preferred search parameters. For example, a user may specify a search word such as "confectionery" and the system will prompt the user to consider narrower terms such as "chocolate" along with related terms such as "cakes" or "desserts", or broader terms such as "food". From a simple request, a user is given an option of focusing further or of taking a broader overview of the subject under consideration.

The scope of an article refers to the context in which the document or article was written. For example, the scope field may consider questions as to whether the article concerns "mergers and acquisitions" or "seasonal trends" et cetera. Such terms are useful in gathering related information from a wide variety of industries and markets and may prove invaluable for particular 7 applications.

Processing system 104 is detailed in Figure 2. Data signals from data sources 101 to 103 are supplied to input interfaces 201 via data input lines 202. Similarly, output data signals are supplied to users 111 to 117 via an output interface 203 and output wires 204. Input interface 201 and output interface 203 communicate with a central processing system 205 based on DEC Alpha integrated circuitry. The central processing system 205 also communicates with other processing systems in a distributed processing architecture. Processing system 104 includes eight Intel chip based processing systems 211 to 218, each implementing instructions under the control of conventional operating systems such as Windows NT.

An operator communicates with the processing system 104 by means of an operator terminal, having a visual display unit 221 and a manually operable keyboard 222. Data files received from sources 101 to 103 are written to bulk storage devices 223 in the form of large magnetic disk arrays. Data files are written to disk arrays 223 after these files have been associated with preferred terms, as illustrated at step 203. These association processes are performed by the subsidiary processors 211 to 218 and the central processing system 205 is mainly concerned with the switching and transferring of data between the interface circuits 201, 203 and the disk arrays 223.

The central processing system 205 communicates with the subsidiary processors 211 to 218 via an Ethemet connection 206 and processing requirements are distributed between processors 211 to 218. Having addressed a subsidiary processor 211 to 218 the transferring of data to an addressed processor is performed. Each individual incoming data file is supplied exclusively to one of the subsidiary processors. The selected subsidiary processor is then responsible for performing the association process, to identify preferred terms relevant to that particular data file. Thereafter, the associated data file is returned to the central processing 8 system 205, over connection 206 and the central processing system 205 is then responsible for writing the associated data file to the disk array 223. In this way, it is possible to scale the degree of processing capacity provided by system 104 in dependence upon the volume of data files to be processed in this way. The central processing system 205 also maintains a table of preferred terms, pointing to particular data files which have been identified as relevant to said preferred terms.

A new incoming data file is supplied to central processing system 205 from input interface 201. The central processing system 205 supplies the new data file to one of the subsidiary processors 211 to 218 over network connection 206. The selected subsidiary processor performs a first processing step of analysing the incoming data file with respect to common data characteristics to generate common category associations. These common category associations, which may be identified by preferred terms, effectively associate the file with particular categories thereby allowing the file to be identified with reference to these categories.

The associated common data characteristics or preferred terms are added to the file which is then returned back to the central processing system 205. Central processing system 205 also maintains a table 228 recording details of particular associated files for each of the common categories. Thus, given a particular common category it is possible to identify all associated files and given a particular file it is possible to identify the particular common categories under which that file has been associated.

In addition to associating the files to common categories, the system shown in Figure 2 is also capable of associating files to user-specific data characteristics. Such characteristics are defined by users, such as users 112 to 117 and the association process is performed by user-specific processor 226. After identifying common data characteristics, as a first process, the central processing system 205 supplies data files to the user-specific processor 226 so as to allow said processor to perform a second processing 9 step. Under the second processing step the incoming data file is analysed with respect to user-specific data characteristics to generate user- specific associations. Such associations, when identified, are brought to the attention of the central processing system 205. The central processing system is then prompted to perform a third processing step consisting of the generation of an alerting signal to the effect that user-specific associations have been generated.

In order to obtain maximum benefit from the first processing step performed by the subsidiary processors 211 to 218 and in order to minimise the burden placed on the user-specific processor 226, user- specific data characteristics may include examples of the common data characteristics. Furthermore, the second processing step makes use of these specified common data characteristics and relies upon processing procedures performed as part of the first processing step by the subsidiary processors 211 to 218. Thus, an association process is performed only once, either in accordance with the common category associations, in response to operations performed by subsidiary processors 211 to 218, or in response to user-specific operations under control of user-specific processor 226.

Procedures performed by the data processing system 104 are summarised in Figure 3. Steps 301 and 302 represent set-up procedures performed prior to receiving incoming data flies. Steps 303 to 307 represent the on-line procedures configured to respond as incoming data files are received. Furthermore, it should be appreciated that other procedures are performed in a multi-tasking environment, possibly in response to incoming data files, although not essential to the present invention.

At step 301 common characteristics are generated for association with data files. These common characteristics are determined by the service provider and will be established in an attempt to anticipate the demands of users.

At step 302 user-specific characteristics are generated for association with data files. These user-specific characteristics will be determined by the specific requirements of a particular user therefore, in a working environment, many user-specific characteristic sets will be created enabling the requirements of many users to be satisfied.

After generating common characteristics and user-specific characteristics, the system enters its on-line mode of operation initiated by step 303. At step 303 a question is asked as to whether a source file has been received and when answered in the negative the system enters a short waft state at 304 before addressing the question again at step 303. When a source file is received the question asked at step 303 is answered in the affirmative and control is directed to step 305.

At step 305 common characteristics are associated with the incoming file and a question is then asked at step 306 as to whether any associations have been made at step 305. If this question is answered in the affirmative, the associations identified at step 305 are written to an association table at step 307 and the file is stored by storage device 223 with the details of the associations.

At step 308 a file of user characteristics is selected and at step 309 the user characteristics selected at step 308 are associated to the received file. At step 310 the question is asked whether any associations have been made and if answered in the affirmative an alert signal to this effect is generated at step 311. Alternatively, step 311 is bypassed to direct control to step 312.

At step 312 a question is asked as to whether another set of user characteristics are to be considered and when answered in the affirmative control is returned to step 308. Thus, in this way, all of the user sets are considered and alert signals are generated where appropriate. Eventually, all of the user characteristics will have been considered and control will be directed to step 313.

11 At step 313 a question is asked as to whether characteristics are to be set up and when answered in the affirmative, control is returned to step 301, effectively taking the system off-line and allowing common characteristics to be modified at step 301 or user-specific characteristics to be modified at step 302. However, in a multi-tasking environment, it should be appreciated that a would be possible to perform the off-line and on-line functionality simultaneously. If the queston asked at step 313 is answered in the negative, to the effect that on-line processing is to continue, control is returned to step 303 to await the next incoming file.

Process 301 for specifying preferred terms for association with data files is detailed in Figure 4. At step 401 a preferred term is selected and at step 402 an outline (OR) file is generated or modified. At step 403 a question is asked as to whether another term is to be processed and when answered in the affirmative control is returned to step 401, allowing the next term to be processed at step 402. Eventually, all of the terms will have been processed resulting in appropriate generations or modifications to their related outline files. Consequently, the question asked at step 403 is answered in the negative whereafter at step 404 data structures are initialised by parsing the OTL files generated at step 402.

Step 402 for the generation or modification of outline files is detailed in Figure 5. At step 501 a visual OTL editor is opened resulting in the editor's visual interface being displayed on VDU 321. At step 502 a question is asked as to whether an existing file is to be loaded for modification and if answered in the negative a new OTL file is created at step 503. If the question asked at step 502 is answered in the affirmative, step 503 is bypassed and at step 504 modifications or additions are made to the OTL definition. At step 505 the OTL modifications created at step 504 are tested on a sample of test data and at step 506 a question is asked as to whether another modification is to be made. When answered in the affirmative, control is returned to step 504 resulting in further modifications or additions being made to the OTL /I- i 12 definitions. When answered in the negative at step 506, the new or modified OTL file is saved at step 507.

When performing modifications or additions at step 504, a graphical representation of the OTL file data is presented to an operator via the visual display unit 321. An example of a display of this type is illustrated in Figure 6, representing a graphical illustration of a specific OTL file.

The OTL file stores definitions in an hierarchical tree structure and this structure is represented in the graphical view as shown in Figure 6. A representation of the tree may be contracted or expanded and the possibility of expanding a particular branch is identified by a plus sign on a particular line, as shown at 601. Similarly, when a particular branch has been fully expanded, the line is identified by a minus sign as shown at 602. Definitions within the file consist of rules, words and labels. The labels allow relationships to be defined between various parts of the file and between individual files themselves. The words identify specific words within an input file of interest and the rules define how and what weights are to be attributed to these words. Each rule line includes, at its beginning, a weight value 603 representing the score that will be attributed when a particular rule condition is met. Rules may also have leaves and the rule defines the way in which scores generated from leaves are combined.

OTL file data represented graphically in the form shown in Figure 6 is actually stored in a data file having a format of the type shown in Figure 7.

The actual data file shown in Figure 7 corresponds to the data display in Figure 6 but in Figure 7 all of the data, some of which has been rolled up in Figure 6, is present. The data contained within the file shown in Figure 7 is manipulated interactively by an operator in response to the graphical interface displayed as illustrated in Figure 6. Score values 603 are also identified in the data file shown in Figure 7.

Displayed line 601 in Figure 6 is generated from line 701 of the actual stored data. The syntax of the language used for recording the data, as 1.

13 illustrated in Figure 7, may vary and the example shown is specific to this particular application. However, the underlying functionality of the language may be considered with reference to the diagrammatic representation shown in Figure 8.

Purely to provide a specific example, this particular outline file is concerned with the topic of the oil industry and therefore the purpose of the OTL file is to identify words and phrases within an input file so as to provide an indication as to how relevant that input data is to users having an interest in the oil industry. Thus, the purpose of procedures exploiting these OTL files is to generate evidence showing that a particular data file conveys information which may be of interest to those studying the oil industry.

The outlines analyse data files in order to produce numerical evidence as to the relevance of a particular file with relation to a particular topic. The OTL definitions and structures are determined empirically and would be modified and upgraded over a peflod of time. The system does more than merely register the existence of a particular word item by placing the word items within an interacting structure; the nature of which is illustrated in Figure 8. The particular entry, given label "oil-industry-mkt" relates to marketing aspects of the oil industry and as such can contribute to an overall score as to the pertinence of incoming data to this particular topic. The first line 801 shows that this particular contribution may provide a total score of forty percent. This total of forty percent is then subdivided such that at fine 802 the presence of the phase "buying oil from" has a score of fifty percent.

Thus, the total contribution made the presence of this phrase consists of fifty percent of forty percent, that is a total of twenty percent being made to the total contribution. Similarly, as shown at line 803 and below, particular words may be identified which result in contributions of sixty percent of thirty percent of forty percent. Thus, a complete OTL file is structured in this way with particular words and phrases making contributions to an overall score value.

These words and phrases may also be specified in the rules as making 14 single contributions or being allowed to accrue.

Process 302 for the generation of user-specific characteristics is detailed in Figure 9. At step 901 a user is invited to select common categories of the type specified at step 201. At step 902 a user is inviited to define user-specific data characteristics which may be in the form of key words or free text. At step 903 a user is invited to define a specific file title and at step 904 a user is invited to specify a particular country of origin.

At step 905 the user is invilted to define a particular alert format, specifying the way in which the user is alerted when a new data file has been received which satisfies the user's data characteristics. At step 906 the user definitions are processed to generate an alert outline (OTL) file.

The user's alert criteria include components, defined at step 902, which require extensive searching of new material as it is received. Searching of this type places a significant burden upon the information supplying resource. In addition, the characteristics also include reference to the preferred terms which will have been associated automatically upon receiving each data file by means of the subsidiary processors 311 to 318. In accordance with the present preferred embodiment, the user-specific characteristics include examples of common data characteristics, specified at step 901 and reference to these characteristics are included in the user definffions generated at step 906. However, when implementing these definitions, use is made of the previously processed common category associations, thereby significantly reducing the processing overhead placed on the user-specific processor 226.

Process 906 for generating an alert OTL file is detailed in Figure 10. At step 1001 preferred terms are identified and labels are constructed. At step 1002 free text entries are extracted and logical inferred rule structures are constructed. At step 1003 titles are identified and at step 1004 an OTL file is generated representing the user's alert specifications. Thus, these specifications may include references to common data characteristics in x.

combination with references to user-specific data characteristics. User 117 communicates with the data processing station 104 via a terminal including a Visual Display Unit (VDU) 221 and a manually operable keyboard 222.

VDU 221 is shown in Figure 11, having received an initial screen of data from the data processing station 104, inviting the user to provide input information in accordance with the procedures identified in Figure 9. Common categories may be entered within displayed boxes 1101, 1102, 1103, 1104, 1105 and 1106. Box 1101 allows an industry or market sector to be selected, while box 1102 allows a particular country of interest to beselected. Items entered at boxes 1101 and 1102 represent common categories and allow information to be supplied back to the central system 104 in response to prompt 901.

Keywords or free text are entered, as user-specific data characteristics, in box 1103 a specific title, as prompted by step 903, may be entered in box 1105 and an alert format is defined by box 1104. In this example, a user may receive an alert as an e-mail message or, alternatively, a user maintains a continuous connection with the system and the user is continually updated with alerts in a manner similar to known ticker tapes. In addition, a user may identify a particular watch name, for the particular characteristics being defined, allowing a plurality of searching procedures to run simultaneously, at box 1106.

After supplying information into the boxes of the display shown in Figure 11, the information is supplied back to the central system 104, thereby allowing processes 1001 to 1003 to be performed as detailed in Figure 10. This is then followed by the generation of the OTL file at step 1004; a process performed by central processing system 205.

Operation of step 1004 results in the production of an OTL file and an example of such a file is given in Figure 12. OTL file 1201 has been generated in response to the input data illustrated in Figure 11. Common data characteristics, such as the characteristic "medicine" entered at box 16 1101 is recorded in the OTL file as a label, as illustrated at line 1202.

Asterisks beneath this show levels of nesting and effectively represent the importance of a particular phrase or relationship within the structure of the definition. Thus, below the top level label, five levels of nesting are included before a specific word is defined at line 1203. At line 1203 word texts are derived from the free field 1103 which, in this example, result in three lines being included; the first being the word "bacteria" at line 1203, the second being the word "disease" at line 1204 and the third being the word "virus" at line 1205.

Figure 12 represents an example of an OTL file for a specific user's application. It is used to associate particular text files as being relevant and consistent with the search criteria supplied by the user. The file includes reference to common data characteristics in combination with reference to user-specific data characteristics. Each common data characteristic has its own OTL file, of the type illustrated in Figure 7. Thus, when implemented, OTL file 1201 directly performs an association process with respect to the three word-text words shown at lines 1203, 1204 and 1205.

The OTL file also includes examples of the common data characteristics and as such it effectively calls an existing OTL file generated for those specific common characteristics. Thus, in this way, it is not necessary to generate new OTL files for the common characteristics and it is not necessary to perform an additional search based on these characteristics, given that association processes will have already taken place. Thus, OTL file 1201 provides a sophisticated level of funcflonality without being required to generate significant amounts of OTL structuring because it refers to the existing OTL files for the common category associations.

The outline structure defined by file 1201 is illustrated in Figure 13. This structure is substantially similar to the structure of common category associations, as illustrated in Figure 8.

17 Source data files are received at step 303 and an example of a source data file is shown in Figure 14. All incoming data files are converted into a standard format of the type shown for file 1401. The file includes a title identifier at 1402 taking the form 'XXTITLE. This is followed by the actual title of the file followed by a delimiter 7HESTAR7 at 1403. The end of the body text is identified at 1404 by the string "EOR=ENDRECORW.

Upon receiving file 1401, a central processing system 204 supplies this file to a subsidiary processor, such as subsidiary processor 211. The subsidiary processor analyses the file with respect to common data characteristics to generate common category associations. These are added to the file itself and also recorded in table 328 before the data file is then written to storage 223.

Subsidiary processor 211 is detailed in Figure 15. The processor includes an Intel Pentium processing unit 1501 connected to sixty-four megabytes of randomly accessible memory 1502 via a M bus 1503. In addition, a local disk drive 1504 and an interface circuit are connected to bus 1503. Interface circuit 1505 communicates with the TCP/IP network. Random access memory 1502 stores instructions executable by the processing unit 1501, in addition to storing input data files received from the data sources 101 to 103 and intermediate data. Operations performed on processing unit 1501, in response to instructions read from memory 1502 are identified in Figure 16.

At step 1601 temporary memory structures are cleared and at step 1602 an OTL description file is selected. At step 1603 an item in the OTL file is identified and at step 1604 a question is asked as to whether the item selected at step 1603 is a rule definition. If this question is answered in the affirmative, a rule object is defined at step 1605. Alternatively, if the question asked at step 1604 is answered in the negative, to the effect that the item is not a rule definition, a question is asked at step 1606 as to whether the item is a word definition. If this question is answered in the affirmative, a dictionary

18 link is created at step 1604.

At step 1608 a question is asked as to whether the item is a label and when answered in the affirmative a new entry is created in a label list, whereafter at step 1610 a question is asked as to whether another item is present. After executing step 1605 or after executing step 1607, control is directed to step 1610.

When the question asked at step 1610 is answered in the affirmative, to the effect that another item is present, control is returned to step 1603 and the next item is identified in the OTL file. Eventually, all of the items will have been identified resulting in the question asked at step 1610 being answered in the negative. Thereafter, at step 1611 a question is asked as to whether another OTL file is present and when answered in the affirmative control is returned to step 1602 allowing the next OTL description file to be selected.

Thus, this process continues until all of the OTL files have been considered resulting in the question asked at step 1611 being answered in the negative.

For each OTL file considered, by being selected at step 1602, a rule base is generated and a plurality of such rule bases is illustrated in Figure 17.

Thus, a first OTL file processed in accordance with the procedures shown in Figure 10 results in the generation of a first rule base 1701. Similarly, further iterations of the procedures shown in Figure 7 result in the generation of rule bases 1702 to 1709. Typically, for a specific installation, in the order of three thousand rule bases would be generated by execution of the procedures illustrated in Figure 10. Rule bases 1701 to 1709 are stored in memory 1502, which also provides storage space for a dictionary 1721, a label list 1722 and a data buffer 1723. The dictionary stores a list of words which have importance in any of the stored rule bases. Associated with each word in the dictionary, there is at least one pointer and possibly many pointers, to specific entries in specific rule bases 1701 to 1709. Thus, the words identified at 803 in Figure 8 would all be included in dictionary 1721. Entries within the dictionary 1721 are implemented upon execution of step 1607 in Figure 16.

1 - I- 19 Similarly, execution of step 1609, creating a new entry in the label list, allows a label to relate to rules that are elsewhere in the tree structure.

Processes performed by the data processing system 104 for associating preferred terms with the source files are detailed in Figure 18. At step 1801 central processor 205 obtains access to one of the subsidiary processors 211 to 218. The central processor then expects to receive authorisation so that communication may be effected with one of the subsidiary processors. after a connection has been established, the source file is supplied to the selected subsidiary processor at step 1803 and at step 1804 the data is processed to determine associated preferred terms.

After performing the processing at step 1804, the results are transmitted back to the central processing system at step 1805 and at step 1806 data with associated preferred terms is stored and data pointers associated with the preferred data terms are updated at step 1807.

Step 1804 for the processing of data to determine associated preferred terms is detailed in Figure 19. The overall processing is broken down into three major phases, consisting of a triggering phase at 1901, followed by a scoring phase at 1902 followed finally by a list generation phase at step 1903.

Triggering phase 1901 is detailed in Figure 20. At step 2001 a section of the data, such as its title, market sector or main body of text, is identified and at step 2002 an item of the identified section is selected. At step 2003 a question is asked as to whether the item indicates a new context, which may be considered as a grammatical marker in the form of a full stop, capital, start of a sentence or quotation marks et cetera. When answered in the affirmative new context information is supplied to all rule bases 1701 to 1709 at step 2004 and control is then directed to step 2007.

If the question asked at step 2003 is answered in the negative, step 2004 is bypassed and a look-up address is obtained for rule objects in rule basesfrom the dictionary at step 2005. Thereafter, at step 2006 all addressed objects are triggered and a multiplication of scores is effected by a score weighting factor. Thereafter, at step 2007 a question is asked as to whether another item is present and when answered in the affirmative control is returned to step 2002.

Eventually all of the items for a selected section Will have been considered resulting in the question asked at step 2007 being answered in the negative. Thereafter, at step 2008 a question is asked as to whether another section is to be considered and when answered in the affirmative control is returned to step 2001.

At step 2001 the next section is identified and steps 2002 to 2008 are repeated. Eventually, all of the sections will have been considered and the question asked at step 2008 will be answered in the negative.

Scoring phase 1902 is detailed in Figure 21. At step 2101 a rule base is selected and at step 2102 a score variable is re-set to zero. At step 2103 a branch is identified for score accumulationlaccrue and at step 2104 scores are accumulated or accrued from triggered rules attached to the branch. At step 2105 a question is asked as to whether another branch is to be considered and when answered in the affirmative control is returned to step 2103. A next branch is selected at step 2103 with procedure 2104 being repeated. Eventually all of the branches will have been considered resulting in the question asked at step 2105 being answered in the negative.

At step 2106 an overall score in the range of zero to one hundred is stored for the rule base and at step 2107 a question is asked as to whether another rule base is present. When answered in the affirmative control is returned to step 2101 and steps 2101 to 2107 are repeated. Eventually, all of the rule bases will have been considered and the question asked at step 2107 will be answered in the negative.

The operations illustrated in Figure 21 may be considered with reference to the illustration of the structure in Figure 8. Thus if any of the defined words at 803 are identified within the file a provisional score of one 21 hundred will be allocated. However, the process as shown in Figure 21, must then ascend up the branches so that any scores lower down will be modified in response to scores higher up the structure.

Phase 1903 for the generation of a list of associated preferred terms is detailed in Figure 22. At step 2201 a rule base is identified having a score greater than a predetermined threshold. Thus, for a particular application a threshold may be set at forty-eight percent. At step 2202 additional triggered preferred data characteristics are identified by associating successful rule bases with parent categorisations by rule base links.

At step 2203 lists of successful and inferred rule bases are combined to form overall lists of preferred data characteristics. Step 2203 results in data being generated by a subsidiary processor, such as processor 211, which is then supplied back to the central processing system 205.

Central processing system 205 is responsible for constructing a table of the type shown in Figure 23 in which an entry is present for each preferred term. The specific preferred terms are stored in column 2301 and, for each of these terms, column 2302 defines a specific pointer to a position in memory associated with the central processing system 205. Specific data files are identified by file names and the number of files associated with each preferred term is variable, depending on the nature and the amount of input data being considered. Thus, in order for this data to be accessible quickly while optimising use of the storage capacity within the central processing system 205, an indication of the file names is stored in the form of a linked list as illustrated in Figure 24.

The preferred term MIL-INDUSTRY" has been associated to a pointer OF8912, as shown in Figure 23. Address OF8912 is the first in column 2401 of the linked list. Column 2402 identifies a particular file name and column 2403 identifies the next pointer in the list. Thus, entry OF8912 points to a particular file with the file name MIL-INDUSTRY-NETHERLAND-W with a further pointer to memory location OF8A20. At memory location e 1---.

22 OF8A20 a new file name is provided, illustrated at column 2402 and again a new pointer is present at column 2403. Eventually, all relevant files will have been considered and the end of the list is identified by address 000000 at the pointer location in column 2403.

Procedures for performing a search in response to a user request are detailed in Figure 25. At step 2501 a user logs onto the system and at step 2502 a search method is identified. At step 2503 search criteria are defined and at step 2504 search criteria are processed to determine preferred terms.

At step 2505 a list of preferred terms are supplied to the central processing system 205.

At step 2506 a question is asked as to whether the host has responded and when answered in the affirmative titles of associated data files are displayed at step 2507. At step 2508 a question is asked as to whether the user wishes to view identified data and when answered in the affirmative the data is viewed; after being downloaded over the communication channel, at step 2509. At step 2510 a question is asked as to whether another search is to be performed and when answered in the affirmative control is returned to step 2502.

Common data associated files are supplied to storage device 223 and an example of such a file is shown in Figure 26. File 2601 is a processed version of file 1401 and includes all the information present in file 1401. In addition, reference to common categories have been added to the top of the file, as shown at 2602 before title line 1403.

Claims (20)

Claims

1. A method of alerting a user-processing site to a condition as to the availability of information associated with user-specified characteristics, comprising a first processing step of analysing incoming data files with respect to common data characteristics to generate common category associations; a second processing step of analysing said incoming data files with respect to user-specific data characteristics to generate user-specific associations; and, a third processing step of generating an alerting signal to the effect that user-specific associations have been generated, wherein said user-specific data characteristics include examples of said common data characteristics, and said second processing step makes use of said common category associations.

2. A method according to claim 1, wherein incoming data files are analysed to make common category associations prior to making userspecific data categorisations.

3. A method according to claim 2, wherein said common category associations are written to an association table.

4. A method according to claim 1, wherein incoming data files are analysed for alert conditions with respect to a plurality of users.

5. A method according to claim 1, wherein each user is invited to select common categories.

6. A method according to claim 1, wherein each user is invited to define free text.

1 24

7. A method according to claim 1, wherein each user is invited to define a tide.

8. A method according to claim 1, wherein each user is invited to define a country of origin.

9. A method according to claim 1, wherein an alert condition is relayed to a user by a maintained communications link.

10. A method according to claim 1, wherein data files are analysed with reference to outline association files so as to generate score values.

11. A data processing system configured to analyse incoming data flies and to generate alert signals to a user if a data file is detected as being relevant to characteristics defined by said user, comprising first processing means for analysing incoming data files with respect to common data characteristics to generate common category associations; second processing means configured to analyse said incoming data flies with respect to user-specific characteristics to generate user specific associations; and a third processing means for generating an alerting signal to the effect that user-specific associations have been generated, wherein said second processing means analyses user-specific data characteristics having reference to common category associations defined by said first processing means.

12. Apparatus according to claim 11, wherein said first processing means analyses an incoming data file with respect to common data characteristics before said second processing means analyses said incoming data with respect to user-specific characteristics.

13. Apparatus according to claim 12, wherein said first processing means is configured to write said common category associations to an association table configured in memory.

14. Apparatus according to claim 11, wherein said second processing means is configured to analyse incoming data files with respect to alert conditions defined for a plurality of users.

15. Apparatus according to claim 11, including user selection means configured to invite each user to select common categories.

16. Apparatus according to claim 11, including user selection means configured to invite each user to define free text.

17. Apparatus according to claim 11, including user selection means configured to invite each user to define a title.

18. Apparatus according to claim 11, including user selection means inviting each user to define a country of origin.

19. Apparatus according to claim 11, including a maintained communications link between the processing system and a user's system, including relaying means configured to relay an alert condition upon detection of said condition.

20. Apparatus according to claim 11, including memory means configured to store outline association flies, wherein said processing means are configured to analyse data files with reference to said outline files.