Enhanced apparatus and methods for retrieving and selecting profiled textural information records from a database of defined category structures

• US 5,537,586 A
• Filed: 05/06/1994
• Issued: 07/16/1996
• Est. Priority Date: 04/30/1992
• Status: Expired due to Term

• Current Assignee: Thomson Reuters Global Resources
• Original Assignee: Individual, Inc. (Moody's Corporation)
• Inventors: Wu, Harry C., Bouvard, Jacques, Amram, Joseph A., Leightheiser, James E., Lidington, John C., Tomeh, Majed G.
• Primary Examiner(s): Black, Thomas G.
• Assistant Examiner(s): HOMERE, JEAN RAYMOND
• Application Number:
  US08/239,421
• Time in Patent Office: 802 Days
• Field of Search: 395/600, 364/DIG. 1, 364/491.19, 364/419.07, 364/491.13
• US Class Current: 1/1
• CPC Class Codes: G06F 16/353 into predefined classes
• CPC Class Codes: Y10S 707/99933 Query processing, i.e. searching

Abstract

A method for extracting a preferred set of textual records from a database includes the following features. Priority values are assigned to each of a plurality of predefined category structures. Textual records are assigned a relevance value with respect to each category structure. If a record'"'"'s relevance value exceeds a predetermined threshold value, that record is associated with the category structure. Each category has a list of associated textual records which are retrieved. Textual records are selected from the set of retrieved textual records and assembled into a set. Information on how the subscriber uses the set is gathered, and new rankings for the category structure are computed.

Claims

1. A method of extracting a preferred set of stored textual records from a database, comprising the steps of:

assigning, to selected ones of a plurality of predefined category structures, a priority value, wherein said selected ones of said plurality of predefined category structures and assigned priority values form a profile associated with a subscriber;

assigning to each stored textual record a relevance value associated with each category structure;

associating each stored textual record with each category structure for which the record'"'"'s relevance value associated with that category structure exceeds a predetermined threshold;

maintaining, for each category structure, a list of associated textual records;

retrieving from the database, for each selected category structure, the textual records associated with that category structure;

selecting, from the set of retrieved textual records, a plurality of preferred textual records in a manner responsive to the priority value assigned to each category structure;

assembling the plurality of preferred textual records to form the preferred set;

collecting usage information from the subscriber for the retrieved textual records forming the preferred set; and

assigning a new priority value for category structures associated with said profile based on the usage information collected for said subscriber associated with the profile, said step of assigning a new priority value comprising;

ranking the category structures in order of subscriber usage of textual records associated with the category structures to determine a usage rank for each category structure; and

comparing the usage rank with the original priority value for each category structure to determine the new priority value for the category structures, said step of comparing comprising;

assigning a first numerical weight to each category structure determined by its original priority value in the associated profile;

assigning a second numerical weight to each category structure determined by the usage of textual records associated with the category structure by the subscriber;

assigning a third numerical weight to each category structure determined by the usage of the textual records associated with the category structure by other subscribers previously determined to be peers; and

assigning the new priority value for each category structure determined by summing the first, second and third numerical weights assigned for each category structure.

2. A method of extracting a preferred set of stored textual records from a database, wherein the stored textual records include full textual records and brief textual records and each brief textual record is associated with a full textual record, comprising the steps of:

assigning to selected ones of a plurality of predefined category structures, a priority value, wherein said selected ones of said plurality of predefined category structures and assigned priority values form a profile associated with a subscriber;

extracting a brief textual record from a full textual record, said extracting step comprising;

determining the source of the full textual record;

selectively extracting portions of the full textual record to provide the brief textual record depending on the source and the length of the full textual record, wherein this selectively extracting step includes extracting the entire full textual record to provide the brief textual record if the length of the full textual record is less than a predetermined value;

assigning to each stored textual record a relevance value associated with each category structure;

associating each stored textual record with each category structure for which the record'"'"'s relevance value associated with that category structure exceeds a predetermined threshold;

maintaining, for each category structure, a list of associated textual record;

retrieving from the database, for each selected category structure, the textual records associated with that category structure;

selecting, from the set of retrieved textual records, a plurality of preferred textual records in a manner responsive to the priority value assigned to each category structure;

assembling the plurality of preferred textual records to form the preferred set;

collecting usage information from the subscriber for the retrieved textual records forming the preferred set, the usage information including subscriber usage of full textual records; and

assigning a new priority value for category structures associated with said profile based on the usage information collected for said subscriber associated with the profile.

3. A method of extracting a preferred set of stored textual records from a database, wherein the stored textual records include full textual records and brief textual records and each brief textual record, is associated with a full textual record, comprising the steps of:

assigning, to selected ones of a plurality of predefined category structures, a priority value, wherein said selected ones of said plurality of predefined category structures and assigned priority values form a profile associated with a subscriber;

extracting a brief textual record from a full textural record, said extracting step comprising;

determining the source of the full textual record;

identifying the location of key terms in the full textual record;

selectively extracting portions of the full textual record to provide the brief textual record depending on the source of and the identified key terms in the full textual record, wherein this selectively extracting step includes extracting one or more sentences proximal to, and including, the identified key terms to provide the brief textual record;

assigning to each stored textual record a relevance value associated with each category structure;

associating each stored textual record with each category structure for which the record'"'"'s relevance value associated with that category structure exceeds a predetermined threshold;

maintaining, for each category structure, a list of associated textual records;

retrieving from the database, for each selected category structure, the textual records associated with that category structure;

selecting, from the set of retrieved textual records, a plurality of preferred textual records in a manner responsive to the priority value assigned to each category structure;

assembling the plurality of preferred textual records to form the preferred set;

collecting usage information from the subscriber for the retrieved textual records forming the preferred set, the usage information including subscriber usage of full textual records; and

assigning a new priority value for category structures associated with said profile based on the usage information collected for said subscriber associated with the profile.

4. A method of providing textual records from a database to a subscriber comprising the steps of:

assigning a priority value to selected ones of a plurality of predefined category structures to form a profile associated with a subscriber;

assigning to each stored textual record a relevance value associated with each category structure;

associating each stored textual record with each category structure for which the record'"'"'s relevance value associated with that category structure exceeds a predetermined threshold;

providing a brief textual record associated with each of the stored textual records, wherein the brief textual record comprises an extracted portion of the stored textual record with which it is associated;

retrieving from the database, the brief textual records associated with the stored textual records associated with each category structure, the selection of particular brief textual records retrieved being responsive to the assigned priority values associated with the profile;

assembling the brief textual records retrieved from the database to form the preferred set;

transmitting the preferred set of assembled textual records to the subscriber;

receiving requests from the subscriber for the stored textual records associated with one or more brief textual records of the preferred set; and

retrieving the requested stored textual record from the database and transmitting the retrieved stored textual record to the requesting subscriber, this retrieving step comprising;

providing a stored textual record limit and a brief textual record limit;

retrieving a plurality of stored textual records up to the stored textual record limit by first retrieving a plurality of stored textual records from the associated category structures, and then, if the retrieved stored textual records number less than the stored textual record limit, then retrieving stored textual records from other category structures up to the stored textual record limit; and

retrieving a plurality of brief textual records up to the brief textual record limit.

5. A method of extracting a preferred set of stored textual records from a database, comprising the steps of:

assigning, to selected ones of a plurality of predefined category structures, a priority value, wherein said selected ones of said plurality of predefined category structures and assigned priority values form a profile associated with a subscriber;

assigning to each stored textual record a relevance value associated with each category structure;

associating each stored textual record with each category structure for which the record'"'"'s relevance value associated with that category structure exceeds a predetermined threshold;

maintaining, for each category structure, a list of associated textual records;

retrieving from the database, for each category structure, the textual records associated with that category structure;

selecting, from the set of retrieved textual records, a plurality of preferred textual records in a manner responsive to the priority value assigned to each category structure;

assembling the plurality of preferred textual records to form the preferred set;

collecting usage information from the subscriber for the retrieved textual records forming the preferred set;

defining a group of subscribers sharing a common characteristic;

compiling usage information for the subscribers of the defined group and analyzing the compiled usage information to detect a usage pattern for the group;

defining one or more new category structures in accordance with the detected usage pattern; and

assigning a new priority value for the new category structures associated with each subscriber profile for each subscriber belonging to the defined group, this step of assigning comprising;

assigning a first numerical weight to each new category structure determined by the original priority values for the original category structures in the associated profile;

assigning a second numerical weight to each new category structure determined by the usage of textual records associated with the new category structure by the subscriber;

assigning a third numerical weight to each new category structure determined by the usage of the textual records associated with the new category structure by other subscribers previously determined to be peers; and

assigning the new priority value for each new category structure determined by summing the first, second, and third numerical weights assigned for each new category structure.

6. The method of claim 5, wherein the defining one or more new category structures comprises redistributing the textual records from a pre-existing category structure into two or more new category structures.

7. The method of claim 5, wherein the defining one or more new category structures comprises combining the textual records from at least two pre-existing category structures in a new category structure.

8. The method of claim 5, wherein the defined group comprises all subscribers.

9. The method of claim 5, wherein the defined group comprises subscribers having a common profession.

10. The method of claim 5, wherein the defined group comprises subscribers having similar geographical location.