Knowledge gathering system based on user's affinity
A system, method, and processor readable medium for processing data in a knowledge management system gathers information content and transmits a work request for the information content gathered. The information content may be registered with a K-map and assigned a unique document identifier. A work queue processes the work requests. The processed information may then be transmitted to another work queue for further processing. Further processing may include categorization, full-text indexing, metrics extraction or other process. Control messages may be transmitted to one or more users providing a status of the work request. The information may be analyzed and further indexed. A progress statistics report may be generated for each of the processes performed on the document. The progress statistics may be provided in a record. A shared access to a central data structure representing the metrics history and taxonomy may be provided for all work queues via a CORBA service.
1. A computer-implemented method, comprising:
identifying, using a spider component of a server and based on character matching algorithms or text matching algorithms, a match between:
(i) a content of a document stored within one or more data repositories, and
(ii) an affinity of a user;
gathering, by the spider component of the server, using a knowledge map, and from the one or more data repositories, one or more documents with contents that match the affinity of the user;
modifying, by the spider component of the server, the knowledge map by registering the gathered one or more documents with the knowledge map, the knowledge map being used to perform a search based on a search string to determine one or more of a document or an affinity of a user that match the search string;
converting, by the spider component of the server, the gathered one or more documents into meta-documents by extracting the meta-documents from the gathered one or more documents in XML format, the meta-documents may include metrics information from the one or more document;
analyzing, by the spider component of the server, the meta-documents to determine types of the gathered one or more documents; and
notifying, by the spider component of the server, the user that the one or more documents with contents that match the affinity of the user have been gathered.
2. The method of claim 1 , further comprising
organizing, by the spider component of the server, the gathered one or more documents into categories.
3. The method of claim 1 , wherein
the one or more data repositories are non-web based data repositories.
4. The method of claim 1 , wherein
at least one of the one or more data repositories is selected by the user.
5. The method of claim 1 , wherein
the knowledge map includes a map of all information stored in the one or more data repositories.
6. The method of claim 1 , wherein
the knowledge map includes categories of information stored in the one or more data repositories.
7. The method of claim 1 , wherein the knowledge map includes a full-text index of information stored in the one or more data repositories.
8. The method of claim 1 , wherein
the knowledge map includes metrics information for information stored in the one or more data repositories.
9. A computer hardware system, comprising:
at least one hardware processor, wherein the at least one hardware processor is configured to implement a spider component performing acts including:
identifying, based on character matching algorithms or text matching algorithms, a match between:
(i) a content of a document stored within one or more data repositories, and
(ii) an affinity of a user;
gathering, using a knowledge map, and from the one or more data repositories, one or more documents with contents that match the affinity of the user;
modifying, the knowledge map by registering the gathered one or more documents with the knowledge map, the knowledge map being used to perform a search based on a search string to determine one or more of a document or an affinity of a user that match the search string;
converting the gathered one or more documents into meta-documents by extracting the meta-documents from the gathered one or more documents in XML format, the meta-documents may include metrics information from the one or more documents;
analyzing the meta-documents to determine types of gathered one or more documents; and
notifying the user that the one or more documents with contents that match the affinity of the user have been gather.
10. The system of claim 9 , wherein the acts further include
organizing the gathered one or more documents into categories.
11. The system of claim 9 , wherein
the one or more data repositories are non-web based data repositories.
12. The system of claim 9 , wherein
at least one of the one or more data repositories is selected by the user.
13. The system of claim 9 , wherein
the knowledge map includes a map of all information stored in the one or more data repositories.
14. The system of claim 9 , wherein
the knowledge map includes categories of information stored in the one or more data repositories.
15. The system of claim 9 , wherein
the knowledge map includes a full-text index of information stored in the one or more data repositories.
16. The system of claim 9 , wherein
the knowledge map includes metrics information for information stored in the one or more data repositories.