Adaptive hierarchy structure ranking algorithm

• US 20070162448A1
• Filed: 01/10/2006
• Published: 07/12/2007
• Est. Priority Date: 01/10/2006
• Status: Abandoned Application

• Current Assignee: Ashish Jain, Srikanth Soogoor
• Original Assignee: Ashish Jain, Srikanth Soogoor
• Inventors: Soogoor, Srikanth, Jain, Ashish
• Application Number:
  US11/328,342
• Publication Number:
  US 20070162448A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/322 Trees
• CPC Class Codes: G06F 16/334 Query execution G06F16/335 takes precedence
• CPC Class Codes: G06F 16/3344 using natural language analysis

Abstract

The present invention is a method for ranking a plurality of documents during a search query utilizing a hierarchical keyword ranking scheme. The present invention utilizes an algorithm which determines a level value for each searched page in the plurality of documents. The algorithm then ranks each page from the plurality of documents by extracting keywords from each document and determining a page keyword rank for each searched page. Next, a hierarchical keyword rank is determined based upon the level value and the page keyword rank for each page. This hierarchical keyword rank is used to rank order the searched documents in order of importance.

Claims

1. A computer implemented method for ranking a plurality of documents and web pages for search, the method comprising the steps of:

determining a level value for each searched page in the plurality of documents and web pages by utilizing distributed crawling;

ranking each page from the plurality of documents and web pages by extracting keywords from each document and determining a page keyword rank for each page; and

determining a hierarchical keyword rank based upon the level value and the page keyword rank for each page.

2. The computer implemented method for ranking a plurality of documents of claim 1 wherein the step of determining a level value for each page includes the steps of:

extracting a child URL from a tag within the searched page;

assigning a level value to the searched page;

classifying the searched page as a parent of the child URL; and

saving the searched page content.

3. The computer implemented method for ranking a plurality of documents of claim 2 wherein the step of assigning a level value to the searched page includes the steps of:

determining if the searched page is a duplicate page; and

if the page is not a duplicate page, assigning a level value to the searched page and saving the searched page in an array for duplicate pages.

4. The computer implemented method for ranking a plurality of documents of claim 1 wherein the step of ranking each page from the plurality of documents by extracting keywords from each document and determining a page keyword rank for each page includes the steps of:

utilizing a formula of;

Σ

freq_tag×

Rank_tag to determine keyword rank wherein freq_tag is a preset frequency for each tag and Rank_tag is a rank per occurrence for each tag; and

saving the keyword rank as Log₁₀(keyword rank×

10).

5. The computer implemented method for ranking a plurality of documents of claim 1 wherein the step of determining a hierarchical keyword rank based upon the level value and the page keyword rank for each page includes the step of combining the searched page keyword rank with the keyword rank of any child pages associated with the searched page to form the hierarchical keyword rank.

6. A computer implemented method for ranking a plurality of documents during a search query, the method comprising the steps of:

determining a level value for each searched page in the plurality of documents, wherein the step of determining a level value includes the steps of;

extracting a child URL from a tag within the searched page;

assigning a level value to the searched page;

classifying the searched page as a parent of the child URL; and

saving the searched page content;

ranking each page from the plurality of documents by extracting keywords from each document and determining a page keyword rank for each page; and

determining a hierarchical keyword rank based upon the level value and the page keyword rank for each page, the hierarchical keyword rank being based upon the searched page keyword rank with the keyword rank of any child pages associated with the searched page.

7. The computer implemented method for ranking a plurality of documents of claim 6 wherein the step of ranking each page from the plurality of documents by extracting keywords from each document and determining a page keyword rank for each page includes the steps of:

utilizing a formula of;

Σ

freq_tag×

Rank_tag to determine keyword rank wherein freq_tag is a preset frequency for each tag and Rank_tag is a rank per occurrence for each tag; and

saving the keyword rank as Log₁₀(keyword rank×

10).

8. The computer implemented method for ranking a plurality of documents of claim 6 wherein the step of assigning a level value to the searched page includes the steps of:

determining if the searched page is a duplicate page; and

if the page is not a duplicate page, assigning a level value to the searched page and saving the searched page in an array for duplicate pages.