Abstract: When a user enters a primary search query into a primary search query input area to perform a first search of the primary search query, disclosed is a method and system for automatically entering the primary search query into a secondary search query input area to perform a second search of the primary search query. When the user enters a secondary search query into the secondary search query input area to perform a first search of the secondary search query, the method and system automatically enters the secondary search query into the primary search query input area to perform a second search of the secondary search query.

Abstract: Disclosed is a method and system for navigating, by a browser executing on the computing device, to a web page; transmitting by a client-side module executing on the computing device to a server computer over a network a request to the server computer for topics associated with the web page; receiving, by the computing device, a set of (one or more) topics associated with the web page from the server computer; displaying by the browser in a first content area the web page; and displaying by the browser in a second content area the received set of topics associated with the web page.

Abstract: When a user enters a primary search query into a primary search query input area to perform a first search of the primary search query, disclosed is a method and system for automatically entering the primary search query into a secondary search query input area to perform a second search of the primary search query. When the user enters a secondary search query into the secondary search query input area to perform a first search of the secondary search query, the method and system automatically enters the secondary search query into the primary search query input area to perform a second search of the secondary search query.

Abstract: When a user enters a primary search query into a primary search query input area to perform a first search of the primary search query, disclosed is a method and system for automatically entering the primary search query into a secondary search query input area to perform a second search of the primary search query. When the user enters a secondary search query into the secondary search query input area to perform a first search of the secondary search query, the method and system automatically enters the secondary search query into the primary search query input area to perform a second search of the secondary search query.

Abstract: Incremental training data is used to supplement a trained model to provide personalized recommendations for a user. The personalized recommendations can be made by taking into account the user's behavior, such as, without limitation, the user's short and long term web page interactions, to identify item recommendations. A trained model is generated from training data indicative of the web page interaction data collected from a plurality of users. Incremental training data indicative of other web page interaction data can be used to supplement the trained model, or in place of the trained model. Incremental training data can be indicative of user behavior collected more recently than the data used to train the model, for example.

Abstract: A system and method are disclosed for optimizing the performance of an advertisement. The advertisement may be targeted based on correlations between advertisements and/or users. The correlations may be used to improve the click-through rate of advertisements. As data is collected and feedback is received, the correlation between ads and users may be updated, so that an advertiser's campaign can optimize its targeting of users.

Abstract: Two items are determined to be similar to each not only based on previous actual user behavior, but also based on the observed relatedness of the characteristics of those two items. A first characteristic and a second characteristic are determined to have some affinity for each other if a high proportion of users who select items having the first characteristics also select items that have the second characteristic, and vice-versa. Two items having characteristics with high affinity for each other are determined to have some similarity to each other, even if very few or no users who selected one of those items ever selected the other of those items. A first item that is determined to be sufficiently similar to second item in this manner may be recommended to a user who has selected the second item as potentially also being of interest to that user.

Abstract: Incremental training data is used to supplement a trained model to provide personalized recommendations for a user. The personalized recommendations can be made by taking into account the user's behavior, such as, without limitation, the user's short and long term web page interactions, to identify item recommendations. A trained model is generated from training data indicative of the web page interaction data collected from a plurality of users. Incremental training data indicative of other web page interaction data can be used to supplement the trained model, or in place of the trained model. Incremental training data can be indicative of user behavior collected more recently than the data used to train the model, for example.

Abstract: Incremental training data is used to supplement a trained model to provide personalized recommendations for a user. The personalized recommendations can be made by taking into account the user's behavior, such as, without limitation, the user's short and long term web page interactions, to identify item recommendations. A trained model is generated from training data indicative of the web page interaction data collected from a plurality of users. Incremental training data indicative of other web page interaction data can be used to supplement the trained model, or in place of the trained model. Incremental training data can be indicative of user behavior collected more recently than the data used to train the model, for example.

Abstract: Disclosed is a method and system for navigating, by a browser executing on the computing device, to a web page; transmitting by a client-side module executing on the computing device to a server computer over a network a request to the server computer for topics associated with the web page; receiving, by the computing device, a set of (one or more) topics associated with the web page from the server computer; displaying by the browser in a first content area the web page; and displaying by the browser in a second content area the received set of topics associated with the web page.

Abstract: When a user enters a primary search query into a primary search query input area to perform a first search of the primary search query, disclosed is a method and system for automatically entering the primary search query into a secondary search query input area to perform a second search of the primary search query. When the user enters a secondary search query into the secondary search query input area to perform a first search of the secondary search query, the method and system automatically enters the secondary search query into the primary search query input area to perform a second search of the secondary search query.

Abstract: Two items are determined to be similar to each not only based on previous actual user behavior, but also based on the observed relatedness of the characteristics of those two items. A first characteristic and a second characteristic are determined to have some affinity for each other if a high proportion of users who select items having the first characteristics also select items that have the second characteristic, and vice-versa. Two items having characteristics with high affinity for each other are determined to have some similarity to each other, even if very few or no users who selected one of those items ever selected the other of those items. A first item that is determined to be sufficiently similar to second item in this manner may be recommended to a user who has selected the second item as potentially also being of interest to that user.

Abstract: Incremental training data is used to supplement a trained model to provide personalized recommendations for a user. The personalized recommendations can be made by taking into account the user's behavior, such as, without limitation, the user's short and long term web page interactions, to identify item recommendations. A trained model is generated from training data indicative of the web page interaction data collected from a plurality of users. Incremental training data indicative of other web page interaction data can be used to supplement the trained model, or in place of the trained model. Incremental training data can be indicative of user behavior collected more recently than the data used to train the model, for example.

Abstract: A system and method are disclosed for optimizing the performance of an advertisement. The advertisement may be targeted based on correlations between advertisements and/or users. The correlations may be used to improve the click-through rate of advertisements. As data is collected and feedback is received, the correlation between ads and users may be updated, so that an advertiser's campaign can optimize its targeting of users.

Abstract: This patent discloses a method to display an online advertisement to a user. The online advertisement may include an object ad profile, at least one user ad profile, and a users personal profile. The method may determine whether to display the online advertisement to the user by comparing at least one of (i) a personal profile of the user and an ad profile of the user to at least one of (ii) the object ad profile, the at least one user ad profile, and the users personal profile.

Abstract: An improved system and method for online advertising driven by predicting user interest is provided. An advertising demand engine may be provided for selecting advertisements to be served to a user for display with requested content. An advertisement may be correlated to an advertisement previously selected by a user or by other users in the user's segment. An advertising correlation engine may be provided for correlating an advertisement to another advertisement using collaborative filtering, an advertising clustering engine may be provided for clustering correlated advertisements using item-based collaborative filtering, and a user correlation engine may be provided for segmenting users by selected advertisements and creating a cluster of advertisements associated with each cluster of users. Correlated advertisements that are selected may be allocated web page placements and then served to a user for display with requested content.