Method for determining a profile of a user of a communication network

• US 20070198937A1
• Filed: 03/10/2005
• Published: 08/23/2007
• Est. Priority Date: 03/10/2004
• Status: Abandoned Application

• Current Assignee: Weborama
• Original Assignee: Weborama
• Inventors: Paris, Sunny
• Application Number:
  US10/592,347
• Publication Number:
  US 20070198937A1
• Time in Patent Office: Days
• US Class Current: 715/745
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

The invention relates to a method and a system for determining a profile of a communications network user, the method includes:

saving profile data regarding known network users in a database, these users forming a reference population, the profile data (P_i) regarding known users including a set of attributes (j) values (P_ij) associated to each user (i),

for each site or part of site (s) of a set of sites of interest accessible via the network, processing a set of probabilities (P_sj) that represent the attribute values of users that connect to the site or part of a site (s), according to the connection history of the users of the reference population to a site or a part of a site, and processing a probability that a user to be identified has a given attribute, according to the probabilities associated to the Internet sites or parts of a site (s) of interest to which the user connects during a specific time period.

The method is characterized in that the processing determines the probability (m_3j) that the user to be identified has a specific attribute (j) as a combination of a decorrelated probability value (m_1j) that takes into account the probabilities associated to the Internet sites or parts of a site (s) and a correlated probability value (m_2j) that takes into account average profile data (g_j) regarding the users that are part of the reference population.

Claims

1. A method for determining a profile of a user to be identified (501) of a communications network (200), the method comprising:

saving profile data regarding known network users in a database (102), these users being part of a reference population (400), the profile data (P_i) regarding known users including a set of attributes (j) values (p_ij) associated to each user (i),

for each site or part of a site (s) of a set of sites of interest (300) accessible via the network (200), processing, a set of probabilities (p_sj) that represent the attribute values of the users that connect to the site or part of site (s), according to connection history of the users of the reference population (400) to the site or the part of site, and

processing, a probability that the user to be identified (501) has a given attribute, according to the probabilities associated to the sites or parts of sites of interest (s) to which the user connected during a given time period,

wherein the processing determines the probability (m_3j) that the user to be identified (501) has a given attribute (j) as a combination of a decorrelated probability value (m_1j) that takes into account the probabilities associated to the sites or parts of sites of interest (s) and a correlated probability value (m_2j) that takes into account average profile data (g_j) regarding the users that are part of the reference population (400).

2. The method according to claim 1, wherein the combination of decorrelated probability values (m_1j) and correlated probability values (m_2j) is a linear combination.

3. The method according to claim 1, wherein the combination of the decorrelated probability value (m_1j) and correlated probability value (m_2j) depends on combination parameters that are empirically determined according to the profile data relative to the known users of the reference population (400).

4. The method according to claim 3, wherein the combination parameters are regularly updated in order to take into account an evolution of the reference population.

5. The method according to claim 1, wherein the processing means determine a decorrelated probability m_1j that a user to be identified (501) has a given attributed j, according to the relation

$m_{1,j}=\prod _{}^{}$

s = 1 x ⁢

( p sj ) ( fn s )

where ƒ

(n_s) is a power function that depends on the number of times n_s that the user to be identified (501) has visited the site of interest s during the given period of time, e is the Euler number and x is the number of sites visited by the user (501).

6. The method according to claim 1, wherein the processing means determine a correlated probability m_2,j that the user to be identified (501) has a given attribute j according to the relation

$m_{2,j}=\prod _{}^{}$

s = 1 x ⁢

( p sj g j ) f ⁡

( n s )

where ƒ

(n_s) is a power function that depends on the number of times n_s that the user to be identified (501) has visited the site of interest s during the given period of time, e is the Euler number, x is the number of sites visited by the user, and g_j is an average value of attribute j for all the known users of the reference population (400).

7. The method according to claim 5, wherein the power function ƒ

(n_s) is equal to ln(e+n_s−

1).

8. The method according to claim 1, wherein the processing determines the probability m_3,j that the user to be identified (501) has a specific given attribute j according to the relation:

m_3,j=α

_jm_1,j+(1−

α

_j)m_2,j

where α

_j is the combination parameter of the decorrelated probability value m_1,j and of the correlated probability value m_2,j determined for attribute j.

9. The method according to claim 1, further comprising converting probabilities (m_3j) that the user to be identified (501) has one or several given attributes (j) into a determined profile (D) of the user (501) including given attributes.

10. The method according to claim 9, wherein performing the converting is dependent on whether the error generated by the converting (e_j) is less than or not less than an acceptable prediction error (ê

_j) for each attribute (j).

11. The method according to claim 10, wherein when the probability (m_3j) that the user to be identified (501) has a given attribute (i) is greater than a specific threshold ({circumflex over (p)}_j) that depends on the acceptable prediction error (ê

_j) for this attribute, the user to be identified (501) is considered as having the attribute (j).

12. The method according to claim 9, wherein the determined profile (D) is calculated by the processing means taking into account each attribute (i) of a predefined set of attributes according to a predetermined priority (Z), this priority order (Z) being chosen according to the commercial importance of each attribute (j) for a given service provider.

13. The method according to claim 1, wherein the processing determines the probability that a user to be identified (501) has a given attribute (j), this attribute being relative to the gender, age, socio-professional category, income level, geographical location, interest areas or computer type of the user.

14. The method according to claim 1, wherein the sites of interest include pages, some of which being marked with page markers, and wherein downloading of the marker triggering transmission of a request to the processor, this request indicating that a given user downloads a specific page.

15. The method according to claim 1, wherein when the user to be identified (501) connects, via the network (200), to a server (601) that hosts a site (s), the server (601) that hosts the site transmits an identification request of the user to be identified (501) to a profiling server (101) that includes a processor, and the profiling server (101) returns the data relative to the profile of the user to be identified (501) to the server (601) that hosts the site (s).

16. The method according to claim 1, wherein when the user to be identified (501) connects, via the network (200), to a server (601) that hosts a site (s), the server (601) that hosts the site forwards the user to be identified (501) to a profiling server (101) that includes a processor, the profiling server (101) determines the data relative to the profile of the user and resends the user to the server (601) that hosts the site (s), with data relative to the profile of the user to be identified (501).

17. The method according to claim 15, wherein the server (601) that hosts the site (s) adapts the presentation of the site according to the data relative to the profile of the user to be identified (501).

18. The method according to claim 15, wherein the server (601) that hosts the site (s) keeps the data relative to the profile of the user that was returned by the profiling server (101) in memory or stores this data in a cookie that it installs in the navigator of the user to be identified (501).

19. The method according to claim 1, wherein a profiling server (101) generates a report regarding the connections made to a site (s) hosted by a server (601), the report indicating the number of users that have visited the site over a specific period of time and presenting the profile data regarding these users.

20. The method according to claim 19, wherein the report generated by the profiling server (101) includes a prediction error rate associated to the presented profile data.

24. The method according to claim 6, wherein the power function ƒ

(n_s) is equal to ln(e+n_s−

1).

25. The method according to claim 11, wherein the determined profile (D) is calculated by the processing means taking into account each attribute (j) of a predefined set of attributes according to a predetermined priority (Z), this priority order (Z) being chosen according to the commercial importance of each attribute (j) for a given service provider.

26. The method according to claim 16, wherein the server (601) that hosts the site (s) adapts the presentation of the site according to the data relative to the profile of the user to be identified (501).

27. The method according to claim 16, wherein the server (601) that hosts the site (s) keeps the data relative to the profile of the user that was returned by the profiling server (101) in memory or stores this data in a cookie that it installs in the navigator of the user to be identified (501).

21. A system (100) for determining a profile of a user to be identified (501) of a communication network (200), comprising a profiling server (101) connected to the network (200) and which includes a processor, wherein the processor is adapted for determining a probability that a user to be identified (501) has a given attribute, depending on the probabilities associated to said sites of interest to which the user has been connected during a given period of time,

wherein the processor determines the probability (m_3j) that the user has a specific attribute (j) as a combination of a decorrelated probability value (m_1j) that takes into account the probabilities associated to the sites of interest and a correlated probability value (m_2j) that takes into account average profile data (g_j) relative to users that are part of a reference population (400).

22. The system (100) according to claim 21, wherein the server is adapted to be connected to a database (102) that contains profile data (P_i) relative to known users of the network, these users being part of the reference population (400), the profile data (P_i) relative to the known users including a set of attributes (j) values (p_ij) associated to each user (i).

23. The system according to claim 21, wherein the processor is adapted for determining, for each site (s) of a set of sites of interest accessible via the network (200), a set (P_s) of probabilities (p_sj) that represent the attributes values of the users that connect to the site (s), according to the connection history of the users of the reference population (400) to the site (s).

28. The system according to claim 22, wherein the processor is adapted for determining, for each site (s) of a set of sites of interest accessible via the network (200), a set (P_s) of probabilities (p_sj) that represent the attributes values of the users that connect to the site (s), according to the connection history of the users of the reference population (400) to the site (s).