Abstract: A method, performed by a computer system, of providing usage data for a plurality of hyperlinks in a resource is disclosed. In one aspect, the method includes maintaining hyperlink usage data for each of the hyperlinks within the resource and adjusting a copy of the resource to incorporate the hyperlink usage data associated with each hyperlink, wherein the hyperlink usage data represents the number of times users have selected a hyperlink of the resource. The method also includes sending the adjusted copy of the resource to a networked device to provide a display representing the hyperlink usage data with each associated hyperlink. The hyperlink usage data is incorporated into the copy of the resource so as to be displayed adjacent to the corresponding hyperlinks of the resource.

Abstract: A method for providing usage data for links in a resource is disclosed. The method involves maintaining a link usage data for each of the links within a resource, such as a web page, and adjusting a copy of the resource to incorporate the link usage data associated with each link. A user can access the adjusted copy of the resource from a device connected to a network, such as the Internet, to display the link usage data with each associated link. The link usage data can be collected for a selected period of time by the user.

Abstract: A process is disclosed for associating particular data requests from a user's computing device with particular site visits. The process includes determining whether the data requests are “forced content” requests, such as requests for advertisements. Such forced content requests, even if directed to a different domain from that of a site being visited, preferably are not treated as the end of the site visit or the start of a new site visit. The process may also consider other information regarding the data requests, such as whether they are requests for images, and whether they are directed to hosts associated with an open site visit.

Abstract: A method and system for monitoring users on one or more computer networks, disassociating personally identifiable information from the collected data, and storing it in a database so that the privacy of the users is protected. In one embodiment, the system generates an anonymized identifier and associates that anonymized identifier with collected network data. An embodiment of the system may further anonymize data such as resource location identifiers, by identifying and removing personal information.

Abstract: A process is disclosed for associating particular data requests from a user's computing device with particular site visits. The process includes determining whether the data requests are “forced content” requests, such as requests for advertisements. Such forced content requests, even if directed to a different domain from that of a site being visited, preferably are not treated as the end of the site visit or the start of a new site visit. The process may also consider other information regarding the data requests, such as whether they are requests for images, and whether they are directed to hosts associated with an open site visit.

Abstract: A method and system for monitoring users on one or more computer networks, disassociating personally identifiable information from the collected data, and storing it in a database so that the privacy of the users is protected. In one embodiment, the system generates an anonymized identifier and associates that anonymized identifier with collected network data. An embodiment of the system may further anonymize data such as resource location identifiers, by identifying and removing personal information.

Abstract: A method and system for monitoring users on one or more computer networks, disassociating personally identifiable information from the collected data, and storing it in a database so that the privacy of the users is protected. The system receives a user identifier and uses it to creates an anonymized identifier, defined as a user identifier stripped of all personally identifiable information. The anonymized identifier is then associated with one or more users' computer network transactions. The data is stored by a collection engine and then aggregated to a central database server across a computer network.

Abstract: Data about computer network traffic is collected as user website visit recording sessions. The data captured is analyzed and organized with sufficient level of detail or granularity to determine a single request from a server. Each data request is analyzed to determine if it comes from a server with which an ongoing end user interaction or open site visit is occurring. If not, a new site visit is created as a general proposition. If the data request is part of an open site visit, then the time is compared to the time of the last interaction and if the interval is sufficiently small, the data request is treated as a continuation of the visit. If the interval is large, a new site visit is created.

Abstract: A system for collecting data regarding network behaviors of users is disclosed. In one embodiment, the system combines session records of users with corresponding transaction records reflective of e-commerce transactions. The session records may, for example, be generated by one or more collection engines deployed by one or more Internet Service Providers. The transaction records may, for example, be obtained through interactions with one or more merchant web sites. By combining these two types of information, the system can, for example, identify a set of user actions that led to a particular purchase transaction.

Abstract: A method and system for classifying information available on a computer network such as Web sites accessible on the Internet. The system receives a list of network resource locators and submits each locator to a voting process. The invention includes using single-level or multiple-level voting to increase the classification accuracy. One or more Web coders receive a resource locator and determine a classification for that locator. When the necessary votes have been made, the system classifies the locator according to the voting rules.

Abstract: A system for collecting data regarding network behaviors of users is disclosed. In one embodiment, the system combines session records of users with corresponding transaction records reflective of e-commerce transactions. The session records may, for example, be generated by one or more collection engines deployed by one or more Internet Service Providers. The transaction records may, for example, be obtained through interactions with one or more merchant web sites. By combining these two types of information, the system can, for example, identify a set of user actions that led to a particular purchase transaction.

Abstract: Data about computer network traffic is collected as user website visit recording sessions. The data captured is analyzed and organized with sufficient level of detail or granularity to determine a single request from a server. Each data request is analyzed to determine if it comes from a server with which an ongoing end user interaction or open site visit is occurring. If not, a new site visit is created as a general proposition. If the data request is part of an open site visit, then the time is compared to the time of the last interaction and if the interval is sufficiently small, the data request is treated as a continuation of the visit. If the interval is large, a new site visit is created.

Abstract: A method and system for monitoring users on one or more computer networks, disassociating personally identifiable information from the collected data, and storing it in a database so that the privacy of the users is protected. The system receives a user identifier and uses it to creates an anonymized identifier, defined as a user identifier stripped of all personally identifiable information. The anonymized identifier is then associated with one or more users' computer network transactions. The data is stored by a collection engine and then aggregated to a central database server across a computer network.

Abstract: Data about computer network traffic is collected as user website visit recording sessions. The data captured is analyzed and organized with sufficient level of detail or granularity to determine a single request from a server. Each data request is analyzed to determine if it comes from a server with which an ongoing end user interaction or open site visit is occurring. If not, a new site visit is created as a general proposition. If the data request is part of an open site visit, then the time is compared to the time of the last interaction and if the interval is sufficiently small, the data request is treated as a continuation of the visit. If the interval is large, a new site visit is created.

Abstract: A method and system for monitoring users on one or more computer networks, disassociating personally identifiable information from the collected data, and storing it in a database so that the privacy of the users is protected. The system includes monitoring transactions at both a client and at a server, collecting network transaction data, and aggregating the data collected at the client and at the server. The system receives a user identifier and uses it to create an anonymized identifier. The anonymized identifier is then associated with one or more users' computer network transactions. The data is stored by a collection engine and then aggregated to a central database server across a computer network.

Abstract: A method and system for monitoring users on one or more computer networks, disassociating personally identifiable information from the collected data, and storing it in a database so that the privacy of the users is protected. The system includes monitoring transactions at both a client and at a server, collecting network transaction data, and aggregating the data collected at the client and at the server. The system receives a user identifier and uses it to create an anonymized identifier. The anonymized identifier is then associated with one or more users' computer network transactions. The data is stored by a collection engine and then aggregated to a central database server across a computer network.

Abstract: A method and system for monitoring users on one or more computer networks, disassociating personally identifiable information from the collected data, and storing it in a database so that the privacy of the users is protected. The system includes monitoring transactions at both a client and at a server, collecting network transaction data, and aggregating the data collected at the client and at the server. The system receives a user identifier and uses it to create an anonymized identifier. The anonymized identifier is then associated with one or more users' computer network transactions. The data is stored by a collection engine and then aggregated to a central database server across a computer network.

Abstract: A method and system for monitoring users on one or more computer networks, disassociating personally identifiable information from the collected data, and storing it in a database so that the privacy of the users is protected. The system includes monitoring transactions at both a client and at a server, collecting network transaction data, and aggregating the data collected at the client and at the server. The system receives a user identifier and uses it to create an anonymized identifier. The anonymized identifier is then associated with one or more users' computer network transactions. The data is stored by a collection engine and then aggregated to a central database server across a computer network.

Abstract: Data about computer network traffic is collected as user website visit recording sessions. The data captured is analyzed and organized with sufficient level of detail or granularity to determine a single request from a server. Each data request is analyzed to determine if it comes from a server with which an ongoing end user interaction or open site visit is occurring. If not, a new site visit is created as a general proposition. If the data request is part of an open site visit, then the time is compared to the time of the last interaction and if the interval is sufficiently small, the data request is treated as a continuation of the visit. If the interval is large, a new site visit is created.