Method and apparatus for a ranking engine
View Patent ↗A computer-implemented method is provided for ranking files from an Internet search. In one embodiment, the method comprises assigning a score to each file based on at least one of the following factors: recency, editorial popularity, clickthru popularity, favorites metadata, or favorites collaborative filtering. The files may be organized based on the assigned scores to provide users with more accurate search results.
1. A computer-implemented method for a ranking engine, the method comprising:
assigning a score to each file based on at least the following factors: recency, editorial popularity, and clickthru popularity, wherein the score is R T and is determined using the following formula:
R
T
=
W
r
R
r
Term
1
+
W
e
R
e
Term
2
+
W
c
R
c
Term
3
where: 0<R i <1
and:
1 =W r +W e +W c
0<R T <1,
wherein clickthru popularity is weighted based on the following formula for R c :
R c =W cpm R cpm +W cph R cph +W cpd R cpd
where:
R
cpm
=
clicks per minutes ranking
=
CPM
Max
(
cpm
)
over
all
items
,
(
0
<
R
cpm
<
1
)
R
cph
=
clicks per hour ranking
=
CPH
Max
(
cph
)
over
all
items
,
(
0
<
R
cph
<
1
)
R
cpd
=
clicks per day ranking
=
CPD
Max
(
cpd
)
over
all
items
,
(
0
<
R
cpd
<
1
)
and
1
=
W
cpm
+
W
cph
+
W
cpd
;
organizing the files based on the assigned scores; and
displaying the files as organized.
2. The method of claim 1 wherein recency is weighted based on the following formula for R r :
R
r
{
1
-
1
t
e
(
d
c
-
d
F
)
,
For
(
d
c
-
d
F
)
<
t
e
0
,
For
(
d
c
-
d
F
)
>
t
e
t e =expiration time (perhaps˜30 days)
d c =current date
d F =date found.
3. The method of claim 1 wherein editorial popularity is weighted between 1 and 0 and is based on at least one of the following: Neilsen ratings, known brand names, website popularity (e.g. Alexa ranking), or the judgment of a professional or corporation with expertise in online media.
4. The method of claim 1 wherein the file is a video file.
5. A computer-implemented method for organizing a collection of files from an Internet search, the method comprising:
assigning a score to each file based on at least the following factors: recency, editorial popularity, clickthru popularity, favorites metadata, and favorites collaborative filtering, wherein the score is R T and is determined using the following formula:
R
T
=
W
r
R
r
Term
1
+
W
e
R
e
Term
2
+
W
c
R
c
Term
3
+
W
md
R
md
Term
4
+
W
cf
R
cf
Term
5
where: 0<R i <1
and:
1 =W r +W e +W c +W cf
0<R T <1,
wherein clickthru popularity is weighted based on the following formula for R c :
R c =W cpm R cpm +W cph R cph +W cpd R cpd
where:
R
cpm
=
clicks per minutes ranking
=
CPM
Max
(
cpm
)
over
all
items
,
(
0
<
R
cpm
<
1
)
R
cph
=
clicks per hour ranking
=
CPH
Max
(
cph
)
over
all
items
,
(
0
<
R
cph
<
1
)
R
cpd
=
clicks per day ranking
=
CPD
Max
(
cpd
)
over
all
items
,
(
0
<
R
cpd
<
1
)
and
1
=
W
cpm
+
W
cph
+
W
cpd
;
organizing the files based on the assigned scores; and displaying the files as organized.
6. The method of claim 5 wherein the file is a media file.
7. The method of claim 5 wherein the file is a video file.
8. The method of claim 5 wherein recency is weighted based on the following formula for R r :
R
r
{
1
-
1
t
e
(
d
c
-
d
F
)
,
For
(
d
c
-
d
F
)
<
t
e
0
,
For
(
d
c
-
d
F
)
>
t
e
t e =expiration time (perhaps˜30 days)
d c =current date
d F =date found.
9. The method of claim 5 wherein editorial popularity is weighted between 1 and 0 and is based on at least one of the following: Neilsen ratings, known brand names, website popularity (e.g. Alexa ranking), or the judgment of a professional or corporation with expertise in online media.
10. The method of claim 5 wherein weighting of favorites metadata is R md =0 if no matches are found or 1 if a keyword field in the metadata of the file matches any favorite titles in a user's favorite titles file, any favorite people in a user's favorite people file, or any keyword in a user's favorite keywords file.
11. The method of claim 5 wherein weighting of collaborative filtering favorites metadata is R cf
R cf, l =W sim ( S max, l )+(1 −W sim ) P l ,
W
sim
=
similarity weighting factor
=
C
max
sim
(
1
-
1
1
+
n
i
)
,
where:
0≦C max sim ≦1.
12. The method of claim 11 wherein R cf is a weighted sum of the maximum user similarity for an item l and the popularity of item l among K-Nearest Neighbors such that 0≦R cf ≦1.
13. A computer system comprising: a processor; ranking engine having programming code for displaying results of a search query based on scores, wherein the scores for files found in the search are based on at least the following factors: recency, editorial popularity, and clickthru popularity, wherein each of the scores is R T and is determined using the following formula:
R
T
=
W
r
R
r
Term
1
+
W
e
R
e
Term
2
+
W
c
R
c
Term
3
where: 0<R i <1
and:
1 =W r +W e +W c
0<R T <1
wherein clickthru popularity is weighted based on the following formula for R c :
R c =W cpm R cpm +W cph R cph +W cpd R cpd
where:
R
cpm
=
clicks per minutes ranking
=
CPM
Max
(
cpm
)
over
all
items
,
(
0
<
R
cpm
<
1
)
R
cph
=
clicks per hour ranking
=
CPH
Max
(
cph
)
over
all
items
,
(
0
<
R
cph
<
1
)
R
cpd
=
clicks per day ranking
=
CPD
Max
(
cpd
)
over
all
items
,
(
0
<
R
cpd
<
1
)
and
1
=
W
cpm
+
W
cph
+
W
cpd
.
14. The system of claim 13 wherein the files are media files.
15. The system of claim 13 wherein the files are video files.
16. The system of claim 13 wherein recency is weighted based on the following formula for R r :
R
r
{
1
-
1
t
e
(
d
c
-
d
F
)
,
For
(
d
c
-
d
F
)
<
t
e
0
,
For
(
d
c
-
d
F
)
>
t
e
t e =expiration time (perhaps˜30 days)
d c =current date
d F =date found.
17. The system of claim 13 wherein editorial popularity is weighted between 1 and 0 and is based on at least one of the following: Neilsen ratings, known brand names, website popularity (e.g. Alexa ranking), or the judgment of a professional or corporation with expertise in online media.
18. A computer system comprising: a processor; ranking engine having programming code for displaying results of a search query based on scores, wherein the scores for files found in the search are based on at least the following factors: recency, editorial popularity, clickthru popularity, favorites metadata, and favorites collaborative filtering, wherein each of the scores is R T and is determined using the following formula:
R
T
=
W
r
R
r
Term
1
+
W
e
R
e
Term
2
+
W
c
R
c
Term
3
+
W
md
R
md
Term
4
+
W
cf
R
cf
Term
5
where: 0<R i <1
and:
1 =W r +W e +W c W md +W cf
0<R T <1,
wherein clickthru popularity is weighted based on the following formula for R c :
R c =W cpm R cpm +W cph R cph +W cpd R cpd
where:
R
cpm
=
clicks per minutes ranking
=
CPM
Max
(
cpm
)
over
all
items
,
(
0
<
R
cpm
<
1
)
R
cph
=
clicks per hour ranking
=
CPH
Max
(
cph
)
over
all
items
,
(
0
<
R
cph
<
1
)
R
cpd
=
clicks per day ranking
=
CPD
Max
(
cpd
)
over
all
items
,
(
0
<
R
cpd
<
1
)
and
1
=
W
cpm
+
W
cph
+
W
cpd
.
19. The system of claim 18 wherein the files are media files.
20. The system of claim 18 wherein the files are video files.
21. The system of claim 18 wherein recency is weighted based on the following formula for R r :
R
r
{
1
-
1
t
e
(
d
c
-
d
F
)
,
For
(
d
c
-
d
F
)
<
t
e
0
,
For
(
d
c
-
d
F
)
>
t
e
t e =expiration time (perhaps˜30 days)
d c =current date
d F =date found.
22. The system of claim 18 wherein editorial popularity is weighted between 1 and 0 and is based on at least one of the following: Neilsen ratings, known brand names, website popularity (e.g. Alexa ranking), or the judgment of a professional or corporation with expertise in online media.
23. The system of claim 18 wherein weighting of favorites metadata is R md =0 if no matches are found or 1 if a keyword field in the metadata of the file matches any favorite titles in a user's favorite titles file, any favorite people in a user's favorite people file, or any keyword in a user's favorite keywords file.
24. The system of claim 18 wherein weighting of collaborative filtering favorites metadata is R cf
R cf, l =W sim ( S max, l )+(1 −W sim ) P l ,
where:
W
sim
=
similarity weighting factor
=
C
max
sim
(
1
-
1
1
+
n
i
)
,
where:
0≦C max sim ≦1.
25. The system of claim 24 wherein R cf is a weighted sum of the maximum user similarity for an item l and the popularity of item l among K-Nearest Neighbors such that 0≦R cf 1.