Systems and methods for spam filtering

1. A computer implemented method, comprising:

scanning, by a computer system, a plurality of sent or received messages of a user to identify addresses of a plurality of persons;

extracting profile data for the persons from the messages, the profile data including one or more of a name of person to whom the user sent a message and a name of a person from whom the user received a message, wherein at least a portion of the profile data is extracted from bodies of the messages;

storing the addresses in a plurality of profiles, each profile being for a respective one of the plurality of persons;

adding the extracted profile data to the profiles, wherein the profile data includes names of the persons and phone numbers for the persons;

querying, using the extracted profile data as search criteria, at least one server to obtain additional information regarding the persons wherein the at least one server includes at least one of: a web search engine, an online directory, a social network server, a business website, a personal website, a media sharing website, a map and direction website, an online retailer, a travel website, a location website, and another type of server;

adding the additional information to the profiles;

updating, by the computer system, the plurality of profiles as new messages of the user are received;

scanning, by the computer system, a set of messages that have been previously classified by a spam filter as spam;

determining, by the computer system, one or more false positive spam messages from the set of messages classified as spam, the determining comprising comparing addresses and names used in the set of messages with addresses and names in the plurality of profiles to select the one or more false positive spam messages out of the set of messages; and

presenting a list to identify the one or more false positive spam messages to the user.

2. The method of claim 1 , wherein the presenting comprises highlighting the one or more false positive spam messages when a list of the set of messages that are classified as spam is presented.

3. The method of claim 1 , further comprising:

moving the one or more false positive spam messages out of the set of messages that are classified as spam.

4. The method of claim 3 , wherein the moving is in response to a single command from a user of the computer.

5. The method of claim 3 , wherein the moving is in response to the computer receiving the one or more messages and determining that the one or more messages are false positive in spam filtering.

6. The method of claim 4 , wherein the presenting comprises highlighting the one or more messages when a list of incoming messages is presented on the computer.

7. The method of claim 1 , wherein each of the sent or received messages is one of: an email, an instant message, and a text message.

8. The method of claim 1 , wherein the computer is a server remote to a user terminal on which the list is displayed.

9. The method of claim 1 , wherein the computer is a user terminal configured to receive incoming messages for the user, send outgoing messages from the user, and display the list.

10. The method of claim 1 , wherein the one or more false positive spam messages are selected out of the set of messages classified as spam, when one or more addresses used in each of the one or more false positive spam messages are in the stored addresses.

11. The method of claim 1 , wherein the scanning of the plurality of messages comprises scanning both sent and received messages to identify the addresses.

12. The method of claim 11 , wherein the received messages and the sent messages are in a first account of the user; the set of messages classified as spam are in a second account of the user; the first account is associated with a first address of the user; and the second account is associated with a second address of the user.

13. The method of claim 1 , wherein the determining of the one or more false positive spam messages comprises communicating via a lightweight directory access protocol to identify the one or more false positive spam messages that at least have addresses listed on a server.

14. A system comprising:

a processor; and

memory coupled to the processor and storing instructions that, when executed by the processor, cause the system to:

scan a plurality of sent or received messages of a user to identify addresses of a plurality of persons;

extract profile data for the persons from the messages, the profile data including one or more of a name of a person to whom the user sent a message an a name of a person from whom the user received a message, wherein at least a portion of the profile data is extracted from bodies of the messages;

store the addresses in a plurality of profiles, each profile being for a respective one of the plurality of persons;

add the extracted profile data to the profiles, wherein the profile data includes names of the persons and phone numbers for the persons;

query, using the extracted profile data as search criteria, at least one server to obtain additional information regarding the persons wherein the at least one server includes at least one of: a web search engine, an online directory, a social network server, a business website, a personal website, a media sharing website, a map and direction website, an online retailer, a travel website, a location website, and another type of server:

add the additional information to the profiles;

update the plurality of profiles as new messages of the user are received;

scan a set of messages that have been previously classified by a spam filter as spam;

determine one or more false positive spam messages from the set of messages classified as spam, the determining comprising comparing addresses and names used in the set of messages with addresses and names in the plurality of profiles to select the one or more false positive spam messages out of the set of messages; and

present a list to identify the one or more false positive spam messages to the user.

15. A non-transitory machine readable storage media storing a set of instructions, that, when executed by a computer system, cause the computer system to:

scan a plurality of sent or received messages of a user to identify addresses of a plurality of persons;

extract profile data for the persons from the messages, the profile data including one or more of a name of person to whom the user sent a message and a name of a person from whom the user received a message, wherein at least a portion of the profile data is extracted from bodies of the messages;

store the addresses in a plurality of profiles, each profile being for a respective one of the plurality of persons;

add the extracted profile data to the profiles, wherein the profile data includes names of the persons and phone numbers for the persons;

query, using the extracted profile data as search criteria, at least one server to obtain additional information regarding the persons wherein the at least one server includes at least one of: a web search engine, an online directory, a social network server, a business website, a personal website, a media sharing website, a map and direction website, an online retailer, a travel website, a location website, and another type of server;

add the additional information to the profiles;

update the plurality of profiles as new messages of the user are received;

scan a set of messages that have been previously classified by a spam filter as spam;

determine one or more false positive spam messages from the set of messages classified as spam, the determining comprising comparing addresses and names used in the set of messages with addresses and names in the plurality of profiles to select the one or more false positive spam messages out of the set of messages; and

present a list to identify the one or more false positive spam messages to the user.

16. The storage media of claim 15 , wherein the memory further stores instructions to cause the computer system to determine a relevancy score for each of the profiles, and wherein the filtering comprises using the relevancy scores of the profiles to filter the spam messages.