Electrical computers and digital processing systems: multicomput – Computer network managing – Computer network access regulating
Reexamination Certificate
2001-04-03
2004-01-27
Alam, Hosain T. (Department: 2155)
Electrical computers and digital processing systems: multicomput
Computer network managing
Computer network access regulating
C709S228000, C370S392000
Reexamination Certificate
active
06684250
ABSTRACT:
FIELD OF THE INVENTION
The present invention relates generally to the field of geographic location determination and, more specifically, to a method and apparatus for estimating the geographic location of a network entity, such as a node coupled to the Internet.
BACKGROUND OF THE INVENTION
Geography plays a fundamental role in everyday life and effects, for example, of the products that consumers purchase, shows displayed on TV, and languages spoken. Information concerning the geographic location of a networked entity, such as a network node, may be useful for any number of reasons.
Geographic location may be utilized to infer demographic characteristics of a network user. Accordingly, geographic information may be utilized to direct advertisements or offer other information via a network that has a higher likelihood of being the relevant to a network user at a specific geographic location.
Geographic information may also be utilized by network-based content distribution systems as part of a Digital Rights Management (DRM) program or an authorization process to determine whether particular content may validly be distributed to a certain network location. For example, in terms of a broadcast or distribution agreement, certain content may be blocked from distribution to certain geographic areas or locations.
Content delivered to a specific network entity, at a known geographic location, may also be customized according to the known geographic location. For example, localized news, weather, and events listings may be targeted at a network entity where the geographic location of the networked entity is known. Furthermore content may be presented in a local language and format.
Knowing the location of network entity can also be useful in combating fraud. For example, where a credit card transaction is initiated at a network entity, the location of which is known and far removed from a geographic location associated with a owner of credit card, a credit card fraud check may be initiated to establish the validity of the credit card transaction.
SUMMARY OF THE INVENTION
According to the present invention, there is provided method to estimate a geographic location associated with a network address. At least one data collection operation is performed to obtain information pertaining to a network address. The retrieved information is processed to identify a plurality of geographic locations potentially associated with the network address, and to attach a confidence factor to each of the plurality of geographic locations. An estimated geographic location is selected from the plurality of geographic locations as being a best estimate of a true geographic location of the network address, where the selection of the estimated geographic location is based upon a degree of confidence-factor weighted agreement within the plurality of geographic locations.
At least one data collection operation may be a traceroute operation.
At least one data collection operation may include retrieving any one of a group of registry records, the group of registry records including a Net Whois records, a Domain Name Server (DNS) Whois record, an Autonomous System Network (ASN), and a DNS Location record.
In one exemplary embodiment, the processing of the retrieved information may include performing a plurality of geographic location operations, each of the plurality of geographic location operations implementing a unique process to generate at least one geographic location.
Each of the plurality of geographic location operations may be to associate a confidence factor with the at least one geographic location generated thereby.
In a further exemplary embodiment, the association of the confidence factor with the at least one geographic location by each of the plurality of geographic location operations comprises applying a confidence map that relates at least one parameter derived from the retrieve information to a confidence factor.
The confidence map may relate multiple parameters derived from the retrieved information to a confidence factor.
In a further exemplary embodiment, the association of the confidence factor with the at least one geographic location by each of the plurality of geographic location operations may comprise applying a plurality of confidence maps, associated with the respective geographic location operation, that each relate at least one parameter derived from the retrieved information to a respective confidence factor.
Each of the plurality of confidence maps may, in a further exemplary embodiment, have a confidence weight, the confidence weight indicative of a relative importance attributed to the at least one parameter by the respective geographic location operation.
A plurality of confidence factors generated by the plurality of confidence maps may be combined, for example, into a combined confidence factor. In one embodiment, the combining of the plurality of confidence factors is performed utilizing weights attributed to each of the plurality of confidence factors. The combining of the plurality of confidence factors may be performed by a weighted arithmetic mean, and according to the following formula:
C
C
F
=
∑
i
=
1
n
cf
i
w
i
∑
i
=
1
n
w
i
where cf
i
is the i
th
of n confidence factors generated by the i
th
confidence map with associated weight w
i
.
In one exemplary embodiment, at least one geographic location generated by a first geographic location operation may be designated as a filter geographic location, and filter from the plurality of graphics locations those geographic locations that do not exhibit a predetermined degree of agreement with the filter geographic location. The filter geographic location may, in one exemplary embodiment, be of a first geographic resolution, and inconsistent geographic locations, of the plurality of geographic locations and having a lower geographic resolution than the first geographic resolution, may be filtered on the basis of a failure to fall within the filter geographic location. The filter geographic location may, for example, be a first country, and the inconsistent geographic locations may be filtered on the basis of a failure to be located within the first country. As a further example, filter geographic location may be a first continent, and the inconsistent geographic locations may be filtered on the basis of a failure to be located within the first continent.
In one exemplary embodiment, the selecting of the estimated geographic location may include generating a separate confidence factor for each of a plurality of geographic resolutions associated with the estimated geographic location. Examples of geographic resolutions include continent, country, state, and city geographic resolutions.
The selection of the estimated geographic location may, for example, include comparing each of the plurality of geographic locations potentially associated with the network address against at least some of the further geographic locations of the plurality of geographic locations. In one embodiment, at least one of the geographic location operations may generate a set of geographic locations, and the geographic locations within the set are not compared against other geographic locations within the set.
In a further exemplary embodiment, the selecting of the estimated geographic location may include collapsing at least some of the confidence factors associated with the geographic locations into a confirmation confidence factor. The collapsing may comprise combining the plurality of confidence factors for a geographic location that exhibit a correspondence.
In a specific exemplary embodiment, the plurality of confidence factors to generate the confirmation confidence factor (CCF) may be combined according to the following equation:
C
C
F
=
100
×
[
1
-
∏
i
=
1
n
(
1
-
mcf
i
100
)
]
where mcf
i
is the i
th
of n confidence factors for the geographic locations that exhibit the correspondence.
In yet a further exemplary embodiment, the cor
Anderson Mark
Bansal Ajay
Doctor Brad
Hadjiyiannis George
Herringshaw Christopher
Alam Hosain T.
Blakely , Sokoloff, Taylor & Zafman LLP
Dinh Khanh Quang
Quova, Inc.
LandOfFree
Method and apparatus for estimating a geographic location of... does not yet have a rating. At this time, there are no reviews or comments for this patent.
If you have personal experience with Method and apparatus for estimating a geographic location of..., we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Method and apparatus for estimating a geographic location of... will most certainly appreciate the feedback.
Profile ID: LFUS-PAI-O-3201271