Query Expansion Method Using Augmented Terms for Improving Precision Without Degrading Recall

• US 20100070506A1
• Filed: 03/10/2009
• Published: 03/18/2010
• Est. Priority Date: 03/18/2008
• Status: Abandoned Application

• Current Assignee: Korea Advanced Institute of Science and Technology
• Original Assignee: Korea Advanced Institute of Science and Technology
• Inventors: Lee, Jung Hoon, Heo, Jun Seok, Whang, Kyu-Young, Nguyen, Tuan Quang, Kim, Yi Reun
• Application Number:
  US12/401,014
• Publication Number:
  US 20100070506A1
• Time in Patent Office: Days
• US Class Current: 707/740
• CPC Class Codes: G06F 16/3338 Query expansion
• CPC Class Codes: G06F 16/3341 using boolean model

Abstract

A query expansion method that improves the precision without degrading the recall, uses augmented terms. The method steps expand an initial query by adding new terms that are related to each term of the initial query. The query is further expanded by adding augmented terms, which are conjunctions of the terms. A weight is assigned to each term so that the augmented terms have higher weights than the other terms.

Claims

1-7. -7. (canceled)

8. A query expansion method, comprising the steps of:

determining an initial query;

expanding the initial query by selecting a new term that is related to each term in the initial query and adding the new term to the initial query;

further expanding the query by adding an augmented term that is a conjunction of terms to the query; and

assigning a weight to each term in the further expanded query.

9. The query expansion method according to claim 8, wherein the step of assigning a weight to each term in the further expanded query, further comprises:

extracting a set of terms in the expanded query, and classifying the terms of the expanded query into original terms, related terms, and augmented terms;

assigning weights to the original terms, the related terms, and the augmented terms and adding the weights to the query; and

reweighting the augmented terms.

10. The query expansion method according to claim 8, wherein the step of assigning a weight to each term in the further expanded query is performed such that the weights of the augmented terms having an at-co-ordination level (n+1) is always greater than those of augmented terms having an at-co-ordination level n.

11. The query expansion method according to claim 8, wherein the weight of each related term is assigned by calculating the similarity between the original term and the related term.

12. The query expansion method according to claim 11, wherein the similarity is measured by a Mutual Information (MI(x,y)) between the original term (x) and the related term (y), wherein

$\mathrm{MI}$

( x , y ) = log 

number 



of 



( x , y ) 



pairs 



in 



document 



collection total 



number number 



of 



x total 



number * number 



of 



y total 



number

13. The query expansion method according to claim 9, wherein the augmented terms always have weights greater than those of the original terms and the related terms.

14. The query expansion method according to claim 9, wherein the weight of the augmented term is determined by the value of a function of a co-ordination level of the augmented term and the summation of the weights of the original terms and the weights of the related terms in the augmented term.

15. The query expansion method according to claim 14, wherein the function of the co-ordination level of the augmented term is 10^|τ

|, where |τ

| is the co-ordination level of the augmented term.