Method of ordering document clusters given some knowledge of user interests

• US 5,911,140 A
• Filed: 12/14/1995
• Issued: 06/08/1999
• Est. Priority Date: 12/14/1995
• Status: Expired due to Term

• Current Assignee: Oberalis LLC (IP Edge LLC)
• Original Assignee: Xerox Corporation (Xerox Holdings Corp.)
• Inventors: Pedersen, Jan O., Tukey, John W.
• Primary Examiner(s): Black, Thomas G.
• Assistant Examiner(s): ROBINSON, GRETA LEE
• Application Number:
  US08/572,399
• Time in Patent Office: 1,272 Days
• Field of Search: 395/605, 395/604, 395/603, 707/3, 707/4, 707/5, 707/1, 707/7
• US Class Current: 1/1
• CPC Class Codes: G06F 16/355 Class or cluster creation or modification
• CPC Class Codes: Y10S 707/99931 Database or file accessing
• CPC Class Codes: Y10S 707/99933 Query processing, i.e. searching
• CPC Class Codes: Y10S 707/99935 Query augmenting and refining, e.g. inexact access
• CPC Class Codes: Y10S 707/99937 Sorting

Abstract

A method of automatically ordering the presentation of documents clusters generated from a ranked corpus of documents. First, the corpus is ordered into a plurality of clusters. Next, a rank is determined for each cluster based upon the rank of a document within that cluster. Afterward, the clusters are presented to a computer user in the order determined by their rank.

Claims

1. A method of browsing a corpus of documents, each document of the corpus having a rank generated in response to a query of a computer user, the method using a processor executing instructions stored in a memory the method comprising the steps of:

a) ordering the corpus into a plurality of clusters, each cluster including at least one document;

b) determining a rank of each cluster based upon the rank of a one of the documents in the cluster; and

c) presenting the clusters to the computer user in an order based upon cluster rank.

2. The method of claim 1 further comprising the step of:

d) generating a cluster summary for each document cluster, each cluster summary a number of typical partial titles of documents within the cluster, the documents represented being selected based upon document rank.

3. The method of claim 1 wherein step c) includes presenting higher ranking document clusters prior to lower ranking document clusters.

4. The method of claim 1 wherein step c) includes presenting lower ranking document cluster prior to higher ranking document clusters.

5. The method of claim 1 wherein step b) includes generating a rank r(C_i) for each document cluster C_i according to the equation:

space="preserve" listing-type="equation">r(C.sub.i)=minr(d)

where;

d is a document within cluster C_i ; and

r(d) is the rank of document d.

6. The method of claim 2 wherein step c) includes presenting higher ranking document clusters prior to lower ranking document clusters.

7. The method of claim 6 wherein step b) includes generating a rank r(C_i) for each document cluster C_i according to the equation:

space="preserve" listing-type="equation">r(C.sub.i)=maxr(d)

where;

d is a document within cluster C_i

r(d) is the rank of document d.

8. The method of claim 2 wherein step c) includes presenting lower ranking document cluster prior to higher ranking document clusters.

9. The method of claim 8 wherein step b) includes generating a rank r(C_i) for each document cluster C_i according to the equation:

space="preserve" listing-type="equation">r(C.sub.i)=min r(d)

where;

d is a document within cluster C_i

r(d) is the rank of document d.

10. A product of manufacture comprising:

a) a memory; and

b) instructions stored in the memory for a method of browsing a corpus of documents, each document of the corpus having a rank generated in response to a query of a computer user, the method using a processor executing instructions stored in a memory, the method including the steps of;

1) ordering the corpus into a plurality of clusters, each cluster including at least one document;

2) determining a rank of each cluster based upon the rank of a one of the documents in the cluster; and

3) presenting the cluster to the computer user in an order based upon cluster rank.

11. A method of browsing a corpus of documents using a processor and a memory coupled to the processor, the processor implementing the method by executing instructions stored in the memory, the method comprising the steps of:

a) identifying each document of the corpus that satisfies a constraint supplied by a user of the computer;

b) ordering the corpus into a plurality of clusters, each cluster including at least one document;

c) determining a score for each cluster based upon how many documents in the cluster satisfy the constraint; and

d) presenting the clusters to the computer user based upon cluster scores.

12. The method of claim 11 wherein step c) comprises the steps of:

e) determining a number of documents in each cluster that satisfy the constraint;

f) setting each cluster score equal to the number of documents in the cluster that satisfy the constraint.

13. The method of claim 11 wherein step c) comprises the steps of:

a) determining a first number of documents in each cluster that satisfy the constraint;

b) determining a second number of documents in each cluster; and

c) setting the score of each cluster proportional to the first number and inversely proportional to the second number.

14. A product of manufacture comprising:

a) a memory; and

b) instructions stored in the memory, the instructions representing a method of browsing a corpus of documents using a processor coupled to the memory, the method comprising the steps of;

1) identifying each document of the corpus that satisfies a constraint supplied by a user of the computer;

2) ordering the corpus into a plurality of clusters, each cluster including at least one document;

3) determining a score for each cluster based upon how many documents in the cluster satisfy the constraint; and

4) presenting the clusters to the computer user based upon cluster scores.