Skyhook Wireless, Inc. v. GOOGLE, INC.

Filing 50

AFFIDAVIT in Support re 49 Preliminary Claim Construction Briefs. (Attachments: # 1 Exhibit 1, # 2 Exhibit 2, # 3 Exhibit 3, # 4 Exhibit 4, # 5 Exhibit 5, # 6 Exhibit 6, # 7 Exhibit 7, # 8 Exhibit 8, # 9 Exhibit 9, # 10 Exhibit 10, # 11 Exhibit 11, # 12 Exhibit 12, # 13 Exhibit 13, # 14 Exhibit 14, # 15 Exhibit 15)(Lu, Samuel)

EXHIBIT 15

Exhibit 15
U.S. Patent No. 7,414,988
Term or Phrase for
Construction
"logic to recalculate position
information for Wi-Fi access
points previously stored in the
database to utilize position
information for the newlydiscovered readings of
previously stored Wi-Fi access
points"

Claim

"computer-implemented logic to
add records to the database for
newly-discovered Wi-Fi access
points"

1

"computer-implemented
clustering logic to identify
position information based on
error prone GPS information"

2

2494209

1

Corresponding Structure if Construed as Means-Plus-Function Element
12:24–38
"An additional enhancement to the algorithm would include a weighting value based on
the age of the records such that new records represent a more significant indication of the
present location for a given access point.
Once the parsing process has been completed the central network system . . . begins
processing the new data. . . . 2) existing access points are repositioned based on any new
data recorded by the scanners. The . . . algorithm factors in the number of records and
their associated signal strengths to weight stronger signal readings more than weaker
signals with a quasi weighted average model."
12:29–38
"Once the parsing process has been completed the central network system . . . begins
processing the new data. During this process 1) new access points are added to the
database and their physical location is calculated . . . . The . . . algorithm factors in the
number of records and their associated signal strengths to weight stronger signal readings
more than weaker signals with a quasi weighted average model."
12:1-12:10
"In some cases the GPS receiver may record erroneous or error records for some period
of time, which could negatively affect the final access point location calculation. The
parser and filter process identifies these bad records and either corrects them or removes
them from the system. The filtering process users clustering techniques to weed out

-1-

Term or Phrase for
Construction

Claim

Corresponding Structure if Construed as Means-Plus-Function Element
error prone GPS readings. For example, if 90% of the readings are within 200 meters of
each other but the remaining 10% of the readings are 5 kilometers away then those
outliers are removed by the filter . . . ."

"logic to determine a weighted
centroid position for all position
information reported for an
access point"

3

12:11–13
"In particular, the system first calculates the weighted centroid for the access point using
all reported data."
12:34–38
"The . . . algorithm factors in the number of records and their associated signal strengths
to weight stronger signal readings more than weaker signals with a quasi weighted
average model.

"logic to identify position
information that exceeds a
statistically-based deviation
threshold amount away from the
centroid position"

3

12:11–17

"the clustering logic . . .
excludes such deviating position
information from the database
and from influencing the
calculated positions of the WiFi access points"

3

"In particular, the system first calculates the weighted centroid for the access point using
all reported data. It then determines the standard deviation based on the distribution of
the reported locations. The system uses a definable threshold based on the sigma of this
distribution to filter out access points that are in error."
12:1–12:19

2494209

"In some cases the GPS receiver may record erroneous or error records for some period
of time, which could negatively affect the final access point location calculation. The
parser and filter process identifies these bad records and either corrects them or removes
them from the system. The filtering process users clustering techniques to weed out
error prone GPS readings. For example, if 90% of the readings are within 200 meters of
each other but the remaining 10% of the readings are 5 kilometers away then those
outliers are removed by the filter . . . . In particular, the system first calculates the

-2-

Term or Phrase for
Construction

Claim

Corresponding Structure if Construed as Means-Plus-Function Element
weighted centroid for the access point using all reported data. It then determines the
standard deviation based on the distribution of the reported locations. The system uses a
definable threshold based on the sigma of this distribution to filter out access points that
are in error. Once these error records are marked, the centroid is recalculated with the
remaining location records to determine the final centroid . . . ."

2494209

-3-