1130 results about "Click-through rate" patented technology

Systems and methods for determining the value of bids placed by content providers for placement positions on a page, e.g., a web page, rendered according to a given context, for instance, the search results listing for a particular query initiated on a search engine web site, are provided. Additionally, systems and methods are provided for determining placement of content items, e.g., advertisements and/or images, on a rendered page relative to other content items on the page based upon bid value.

If some aspect of serving or scoring an ad is subject to a performance (e.g., click-through rate, etc.) threshold, such a threshold may be adjusted using a confidence factor of the ad targeting used. For example, ads served pursuant to a more relaxed notion of match might have to meet a higher performance threshold (e.g., than the threshold applied to ads served pursuant to a stricter notion of match). Alternatively, or in addition, ads served pursuant to a stricter notion of match might be subject to a lower performance threshold (e.g., than the threshold applied to ads served pursuant to a more relaxed notion of match. Thus, in general, a performance threshold could increase as match confidence decreases, and/or a performance threshold could decrease as match confidence increases.

A system obtains a first parameter (QP₁) associated with a quality of an advertisement among multiple advertisements, where the first quality parameter (QP₁) does not include a click through rate (CTR). The system functionally combines the first quality parameter (QP₁) with at least one other parameter and uses the functional combination to filter, rank or promote the advertisement among the multiple advertisements.

Relevant content is prepared and selected for delivery to a member of a network based, in part, on prior online activities of the other members of the network, and the closeness of the member's relationship with the other members of the network. The relevant content may be an online ad, and is selected from a number of candidate online ads based on click-through rates of groups that are predefined with respect to the member and with respect to certain attributes. An online ad's revenue-generating potential may be considered in the selection process.

Advertisements over a network, such as the Internet, by extracting an index file of suppliers of search result sets for a plurality of keywords and/or an index of ads to be placed. A keyword in a received query may be matched to the suppliers of related search result sets and/or the ads to be placed in the index file(s). The search results may be ranked based on various criteria such as yield, click through rates and history of dealings. Search result sets for the keywords from the matching suppliers and the ads to be placed may be combined to produce a search result set ranked in accordance with estimated yields for advertisements associated with each result in the search result set and delivered in response to the received query. The search results in the combined set may be reranked and/or repriced.

The invention discloses a method and device for predicting advertisement click rate based on user behaviors. The method comprises the following steps of: behavior directional prediction: training a behavior directional model by analyzing the user behaviors, and predicting the click rates of the user on different types of advertisements to obtain a predicted value of the click rate; in-type sorting: sorting the advertisements of each type according to the current behavior type of the user to obtain an in-type advertisement sorting list; and comprehensive sorting: sorting the click rates of all advertisements according to the predicted value of click rate and the in-type advertisement sorting list to obtain a comprehensive sorting list. Through the method disclosed by the invention, a prediction model can be established for each type of advertisements so as to sort the advertisements more accurately according to the type characteristics of the advertisements.

A banner advertisement selecting method is disclosed comprising the steps of (a) estimating the input probability of each attribute and the click rate of each advertisement for each attribute corresponding to an input attribute distribution of the banner advertisement and a click history of which the banner advertisement was clicked, (b) obtaining a display probability of each banner advertisement for each attribute so that the total click rate becomes maximum with conditions such as the desired number of display times of each banner advertisement being satisfied, (c) selecting a banner advertisement according to the display probability, and (d) transforming a restricted objective function maximizing problem obtained at step (b) to a transportation problem and solving the transportation problem.

Various techniques are disclosed for facilitating on-line contextual analysis and/or advertising operations implemented in a computer network. According to some embodiments, various aspects may be used for enabling advertisers to provide contextual advertising promotions to end-users based upon real-time analysis of web page content which may be served to an end-user's computer system. In at least one embodiment, the information obtained from the real-time analysis may be used to select, in real-time, contextually relevant information, advertisements, and/or other content which may then be displayed to the end-user, for example, via real-time insertion of textual markup objects and/or dynamic content. According to specific embodiments, various operations may be performed for adapting or modifying a conventional context-based advertising systems to improve various features such as, for example, ad relevance estimation, click-through rate estimation, advertisement selection and layout, balancing exploration and exploitation, etc.

The present invention relates generally to an individualized web-based browser interface and associated software for accessing at least one web-based search engine with the ability to wrapper and present some or all of the search results obtained from the at least one search engine in a presentation format or order that is based upon the profile of a particular end user for a computer system where the browser is installed. The invention further relates to a method for improved web-based advertising by validating advertising click-throughs of web page thumbnails or advertisements that are presented to an individual having a particular profile with respect to an advertiser's metrics in place of, or in addition to, presenting such a thumbnail from the advertiser to anyone who structures a search having certain terms or meta data criteria corresponding to a specific group of corresponding web pages.

Various techniques are disclosed for facilitating on-line contextual analysis and/or advertising operations implemented in a computer network. According to some embodiments, various aspects may be used for enabling advertisers to provide contextual advertising promotions to end-users based upon real-time analysis of web page content which may be served to an end-user's computer system. In at least one embodiment, the information obtained from the real-time analysis may be used to select, in real-time, contextually relevant information, advertisements, and/or other content which may then be displayed to the end-user, for example, via real-time insertion of textual markup objects and/or dynamic content. According to specific embodiments, various operations may be performed for adapting or modifying a conventional context-based advertising systems to improve various features such as, for example, ad relevance estimation, click-through rate estimation, advertisement selection and layout, balancing exploration and exploitation, etc.

The invention belongs to internet massage processing field, characterized in that: common inquiry set which is cared by user, according to one ore more search engine logs, is screened out firstly using the inquiry of corresponding information of user number; then calculating user touching ratio corresponding to user touching page of inquiry in common inquiry set, if multi-search engine logs is used, user touching ratio are united; user touching pages are effectively screened out based on user touching ratio, the ralated inquiry and corresponding result page address are stored related database; at last, the result from user information and the result by searching by search engine are united effectively when user puts in the demand of inquiry, and are reordered to return to user. The method has the advantage that computer is completed automatically and efficiently submits search engine performance in real time and objectively.

A computer implemented method comprises analyzing a plurality of attributes of a sample of online documents using a boosted decision tree and generating a model from it. The model is used to predict a click through rate (CTR) of an additional online document based on the analyzing. The predicted CTR is output to a display device, storage medium or network.

An internet marketing analytics system to quantify visitor website activity, the system including a database having a plurality of parameters having any portion of the following; site visits, total revenue, bounce rate, conversion rate, orders, average order value, value per visit, pages per visit, new visits, units, cart additions, cart removals, internal search, click through rate, revenue per visit, open rate, email list, impressions, visit duration, percent new visitors, percent return visitors, post volume, net promoter score, social referring traffic, total cost, search term, exit rate, page views, and product type, plus non website related visitor internet activity. The system producing a multi-variate visual spatial display of the database including at least three parameters being simultaneously displayed and modifying the display to selectively emphasize a parameter to be displayed as an X, Y, or Z axis for clarity, for modifying a component of the database to optimize website efficiency.

A method of targeted online advertising provides to a user advertisements that meet the user preferences. The method stores user information of users, organize the users into user layers, identifies the stored user information of a visiting user based on a user identifier, and identify a target user layer associated with the visiting user. The method then determines a targeted advertisement type for the visiting user based on the favorite advertisement type of the target user layer and the user information of the current visiting user, and accordingly selects a targeted advertisement to be presented to the visiting user. The user information of the visiting user and the related user layer(s) are updated with the new user information including the records of the user's visit activities. The method provides targeted ads to users, and improves the click rates and the efficiency of the online advertisements.

Methods and apparatus for a recommendation system based on collaborative filtering is provided. Explicit and implicit ratings of items by network users are used to create a contextual model. The explicit ratings comprise different rating types regarding different item attributes. The implicit ratings comprise different rating types derived from different user events and may include recency, intensity, or frequency ratings. The contextual model may be optimized for a specific objective function, such as click-through-rate or conversion rate. In other embodiments, item information is used to produce a content model where item information for an item is encoded as metadata into a document that represents the item. The contextual or content model is used to recommend one or more items to a current user. The basic unit of the recommendation system may be an item set of two or more items or a particular sequence of two or more items.

The present invention provides a solution for predicting an advertisement click-through rate. The solution comprises: acquiring characteristic related information of multiple characteristic types related to multiple past delivered advertisements in a predetermined past time period; performing cross combination on characteristic related information of at least two characteristic types of each past delivered advertisement, to determine multiple cross characteristic sets, and calculating to determine cross characteristic identifiers separately corresponding to the multiple cross characteristic sets; extracting an advertisement display quantity and an advertisement click quantity corresponding to each cross characteristic set, and calculating to determine an advertisement click-through rate corresponding to each cross characteristic set, so as to use the advertisement click-through rate as a cross characteristic value; performing training on a logistic regression model based on the cross characteristic identifiers and the cross characteristic values separately corresponding to the multiple cross characteristic sets, and calculating to determine a model training parameter; and performing prediction calculation on an advertisement click-through rate of a to-be-predicted advertisement based on the model training parameter. According to the solution, more reliable training data is provided for prediction calculation of an advertisement, so that accuracy of a prediction calculation result of an advertisement click-through rate is ensured.

A system and method for achieving optimal advertising is disclosed. In Internet advertising embodiments, small quantities of experimental advertising banner designs are tested to extract valuable information from the experiments. One or more embodiments can also incorporate array mathematics to help select and analyze the ad design elements that improve the results (e.g., click-thru-rate, revenue-per-impression, etc.) of the overall advertising campaigns. Embodiments of the present invention can also utilize a process of identifying influential design elements, selecting and testing banners representative of such design elements, obtaining feedback, and analyzing it to extract information from the experiments about which design elements are most important and which combination of design elements lead to the best overall banner. By providing substantive results via fewer test banner designs, the present invention decreases the costs associated with running advertising campaigns and otherwise improves the efficiency and success rates of an advertising provider.

In a web page advertising method with a learning mechanism, a plurality of advertisement files are transformed to vector equations in advance. Content of a web page file that is being displayed is analyzed and transformed to a vector equation in real time. An advertisement search conditional set is determined according to the analyzed web page file. The advertisement files are subjected to a similarity analysis using vector computations so as to select at least one advertisement file that has a high correlation to the overall concept of the content of the web page. Adjustment and training with the advertisement file are conducted through analyzing actions of a user, thereby increasing considerably the click rate of the advertisement file and achieving full utilization of advertising resources. An advertising agent employing the web page advertising method purchases advertising spaces from a medium and bills advertisers on a pay-per-click basis.