Relevance feedback using query-logs

Gaurav Pandey

Supervisors:Prof. Gerhard Weikum

Julia Luxenburger

Motivation

Results

Search Engine

Query

“One size fits all”

Motivation

Results

Search Engine

User infoQuery

Motivation

Python

Motivation

PythonCGI code Debugging programming

Usage of Query Logs

Clickthrough data

•Past queries

• Documents clicked

Usage of Query Logs

Query

Clicked Documents

History Instance

Query Reformulation

Result Query: “python information CGI code examples program code debugging bug removal programming”

But,

p(python/query)=? p(CGI)/query)=? p(code)/query)=?

…………………………..

Language ModelNormally(without using history), w:term

d: document q:query

Importance of term w in current query

Considers only the current query

But, not history instances

Language ModelNormally(without using history), w:term

d: document q:query

Importance of term w in current query

Now, using history:

Importance of term w in current query + history instances

?

Language Model+History

Importance of the term w at one instance in the history

Importance of term w in history instances

History query: “CGI code”

Documents: “CGI examples”,

“program code”

History query: “CGI code”

Documents: “CGI examples”, “program

code”

Equal Weighting

Works,but can be improved

Discriminative Weighting

Choose different for every history instance.. How?

Overlap

if a history query has common terms with the current query then

λi= 1,

Else if there is no common term

λi=0

Example:

Current query “python information”

History query:”python code” λi= 1

History query:”world cup” λi= 0

Soft overlap

if a history query has common terms with the current query then

λi= a,

Else if there is no common term

λi=b (a>b)

Example:

Current query “python information”

History query:”python code” λi= 8

History query:”world cup” λi= 2

Decrease with time

Use uniformly decreasing values

If there are n history instances,1 =n2 =n-13 =n-2……n-1 =2n =1

Decrease with time

Use geometrically decreasing values

If there are n history instances,1 =n2 =n/23 =n/3……n-1 =n/(n-1)n =1

Experiment Comparison of the 4 techniques Equal weighting Basic model (without history) Use similar techniques for: Probabilistic model Vector space model

Thanks