METHOD FOR A NETWORKED KNOWLEDGE BASED DOCUMENT RETRIEVAL AND RANKING UTILIZING EXTRACTED DOCUMENT METADATA AND CONTENT

• US 20080183691A1
• Filed: 01/30/2007
• Published: 07/31/2008
• Est. Priority Date: 01/30/2007
• Status: Abandoned Application

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Kwok, Thomas Y., Nguyen, Thao N.
• Application Number:
  US11/668,560
• Publication Number:
  US 20080183691A1
• Time in Patent Office: Days
• US Class Current: 707/5
• CPC Class Codes: G06F 16/313 Selection or weighting of terms for indexing

Abstract

A method, article, and system for managing document retrieval and ranking, and more particularly to providing a method, article, and system for utilizing not just the explicit metadata of a retrieved document, but also the extracted intrinsic metadata inside the content of the retrieved document, as well as the knowledge of the user-document relationship by relating the document implicit metadata to the user'"'"'s information on the document'"'"'s system database, as important parameters in calculating relevance or ranking score for retrieved documents.

Claims

1. A method for managing document retrieval and ranking from a system, wherein the method comprises:

determining explicit metadata of a retrieved document;

extracting intrinsic metadata from inside content of the retrieved document;

determining stored information related to the retrieved document from a document system database;

obtaining information related to the retrieved document from a series of search engines;

wherein the explicit metadata, intrinsic metadata, stored information, and search engine information comprise document information;

constructing static or dynamic user-document relationship rules based on input from a user or an administrator;

establishing a knowledge of a user-document relationship by relating document information to the user'"'"'s information on the document system database;

generating user-document relationships based on the knowledge of a user-document relationship and the static or dynamic user-document relationship rules;

constructing static or dynamic ranking rules based on input from the user or the administrator;

calculating a relevance or ranking score for each of the retrieved documents based on the explicit metadata, intrinsic metadata, and knowledge of user-document relationship, and the static or dynamic ranking rules;

entering a query by a user into the system with a client user module;

constructing a system query by the system based on said entering;

retrieving information about the user by the system;

reconstructing the system query with the user information by the system;

sending the reconstructed system query from the client user module to an application server by the system;

retrieving a document in response to the reconstructed system query by the application server; and

ranking the retrieved document by the application server.

2. The method of claim 1, wherein the entering of the user query comprises the entering of query types and query terms;

wherein the entering of query types comprises the entering of terms, key words, content search, and quotation search; and

wherein the entering of query terms comprises the entering of details about the query types.

3. The method of claim 1, wherein the method further comprises:

receiving the user query with the user information from the client user module;

retrieving documents with corresponding relevance scores based on the user query with a search module within the application server;

retrieving the explicit metadata by the system from the retrieved documents and their corresponding properties; and

retrieving the implicit metadata by the system from the retrieved document;

retrieving the document information by the system related to the retrieved document from the document system database; and

parsing the user information by the system for comparison to the document information; and

wherein the comparison forms the knowledge of the user-document relationship; and

wherein the knowledge of the user-document relationship is used in numerical analysis to derive the relevance and ranking score.

4. The method of claim 1, wherein the document information comprises:

document name;

key words;

titles;

creation date;

last update;

viewed dates;

ownership;

department;

status;

security settings and access control of the retrieved document.

5. The method of claim 1, wherein the user information comprises both personnel and business related information;

and

wherein the user personnel information comprises;

profile;

user interests;

user preferences; and

user selection histories; and

wherein the user business information comprises;

department affiliation;

user organization and their hierarchies;

user organizational rank;

user document access level;

user'"'"'s customers, partners, and suppliers;

user'"'"'s colleagues and managers, user'"'"'s work and business related information.

6. The method of claim 5 wherein the user business information related to the retrieved document is automatically and dynamically generated from a database on said application server side.

7. The method of claim 1, wherein the method is employed in a networked based system.

8. The method of claim 1, wherein the method is employed a in a standalone system.

9. The method of claim 1 wherein the client user module has graphical user interfaces (GUIs) and provides for communication with the server application for the user to customize and store user information related to a document on a client side of the system.

10. The method of claim 1 wherein user business information related to said document can also be automatically and dynamically generated from a database on the application server side.

11. The method of claim 1 wherein an administrator module has GUIs and provides for communication with the server application for an administrator to define and input default user-document relationship parameters and their weighting factors in calculating a total ranking score.

12. The method of claim 1 wherein the client user module has GUIs and provides for communication with the server application for the user to redefine, customize and input default user-document relationship parameters and their weighting factors in calculating a total ranking score.

13. The method of claim 1 wherein the client user module has GUIs and provides for communication with the server application for the user to dynamically modify the user-document relationship parameters and their weighting factors in calculating a total ranking score.

14. The method of claim 1 wherein a ranking module builds and calculates the total ranking scores on a set of relevant documents from search based on knowledge derived from the user-document relationship parameters and their weighting factors.

15. The method of claim 1 wherein a ranking module builds and calculates the total refined ranking scores on a returned set of relevant documents from a search based on knowledge derived from the user-document relationship parameters and their weighting factors.

16. An article comprising one or more machine-readable storage media containing instructions that when executed enable a processor to access a document retrieval and ranking program in a system that comprises computer servers, mainframe computers, desktop computers, and mobile computing devices;

and

wherein the document retrieval and ranking program facilitates document searches; and

wherein the document retrieval and ranking program provides for managing document retrieval and ranking from the system by utilizing not just explicit metadata of a retrieved document, but also extracted intrinsic metadata inside content of the retrieved document, static and dynamic ranking rules constructed from a user'"'"'s information or inputs from the user or an administrator, and knowledge and rules dynamically built on a user and the retrieved document based on the extracted data, and forms a dynamically constructed user-document relationship based on knowledge and rules on the user and the retrieved document by relating document implicit metadata to a user'"'"'s information on a document system database, as important parameters in calculating relevance or ranking score for the retrieved documents.

17. The article of claim 16, wherein the article comprises:

an algorithm to filter, build and calculate total ranking scores on a returned set of relevant documents from a search based on knowledge derived from user-document relationship parameters and their weighting factors.

18. The article of claim 16, wherein the article comprises:

an algorithm to filter, build and calculate total ranking scores on a set of relevant documents based on knowledge derived from user-document relationship parameters and their weighting factors.

19. A system for managing document retrieval and ranking by utilizing not just explicit metadata of a retrieved document, but also extracted intrinsic metadata inside content of the retrieved document, and knowledge and ranking rules dynamically built on a user and the retrieved document based on the extracted data, and forms a dynamically constructed user-document relationship based on the static relationship rules retrieved from the system or dynamic relationship rules inputted by the administrator, and the knowledge on the user and the retrieved document by relating document implicit metadata to a user'"'"'s information on the systems or databases of the user, retrieved documents and search engines, as important parameters in calculating relevance or ranking score for the retrieved documents, wherein the system comprises computing devices and at least one network;

and

wherein the computing devices implement the document database; and

wherein the computing devices further comprise;

computer servers;

mainframe computers;

desktop computers; and

mobile computing devices; and

wherein the computing devices execute electronic software that manages the document retrieval and ranking; and

wherein the electronic software is resident on a storage medium; and

wherein the computing devices have the ability to be coupled to the network; and

wherein the network further comprises;

a local area network (LAN);

a wide area network (WAN);

a global network;

an Internet;

an intranet;

wireless networks; and

cellular networks.

20. The system of claim 19, wherein the computing devices further comprises:

a client user module;

a generic search engine;

a generic document parser;

a generic data extraction engine;

a dynamically derived user-document knowledge and rules built engine;

a dynamically derived user-document relationship construction engine;

a ranking module;

an application server; and

an administrator module.