76 results about "Clickstream" patented technology

The present invention is directed to generating audience analytics that includes providing a database containing a plurality of user input pattern profiles representing the group of users of terminal device, in which each user of the group is associated with one of the plurality of user input pattern profiles. A clickstream algorithm, tracking algorithm, neural network, Bayes classifier algorithm, or affinity-day part algorithm can be used to generate the user input pattern profiles. A user input pattern is detected based upon use of the terminal device by the current user and the user input pattern of the current user is dynamically matched with one of the user input pattern profiles contained in the database. The current user is identified based upon dynamic matching of the user input pattern generated by the current user with one of the user input pattern profiles. The present invention processes each user input pattern profile to identify a demographic type. A plurality of biometric behavior models are employed to identify a unique demographic type. Each user input pattern profile is compared against the plurality of biometric behavior models to match each user input pattern profile with one of the biometric behavior models such that each user input pattern profile is correlated with one demographic type. Audience analytics are then based upon the identified demographic types.

Methods and data processing system readable media have been created to graph user clickstream data over a network or at a network site to yield meaningful and visually esthetic information. In one set of embodiments, the method can comprise (i) performing a significance test on data from a network log and generating significance results. The method can also comprise (ii) determining which of network addresses and clicktrails between network addresses meet a traffic flow criterion. The data that meet a significance criterion, traffic criterion, or both can form (iii) graphable addresses and relationships. The method can further comprise (iv) generating statistics about the graphable addresses and relationships. The method can still further comprise (v) generating a graph based on the statistics about the graphable addresses and relationships, and (vi) changing any or all of the traffic flow, significance criterion, and statistics being computed, and regenerating the graph.

Methods, apparatus and computer code for providing information retrieval services (e.g. handling search queries and providing electronic advertising) in accordance with a given user's social network are disclosed herein. In some embodiments, an information retrieval operation is handled according to the click stream and/or taste profile and/or user profile of different associated users of the social network—for example, indirect contacts. The respective influence, for any associated user (i.e. within the social network), of the associated user's click stream and/or taste profile and/or user profile on the handling of an information retrieval operation for the “given user” may be determined by a “closeness function” between the associated user and the given user. The closeness function and/or the taste profile and/or user profile of any associated user may, in some embodiments, be determined by analyzing electronic communications—for example, text chat communications and/or voice communications that optionally include video.

Methods, systems, computer program products, and methods of doing business by improving collection of clickstream data in network exchanges comprising a plurality of related request and response messages. A clickstream cookie is created by an application, and contains a clickstream data collection correlator for messages of a particular transaction. A Uniform Resource Locator (“URL”) token is created, and is used both in URLs of messages and in cookies downstream of a cookie jar for locating the application-generated correlator. In preferred embodiments, this application-generated correlator is a unique value which is used to identify related clickstream data once it is collected. A flag may also be used to indicate whether data collection is enabled. No changes are required on client devices or in client software, and there is no dependency on a client to support cookies. Using the disclosed techniques, a particular application may specify varying clickstream data collection requirements for the transactions it generates.

An improved system and method for web destination profiling for online population-targeted advertising is provided. A web destination profiler may be provided for generating web destination profiles. Traffic may be analyzed at a particular web destination in order to understand the population visiting the web destination. The analysis of user traffic, including differentiated clickstream data, may be applied for determining known characteristics of a web destination profile. Moreover, unknown characteristics of a web destination profile may be determined using a variety of techniques including inferring characteristics by modeling traffic flow through other web destinations, estimating characteristics from other web destination profiles by predicting traffic flow through other web destinations, propagating characteristics to a web destination profile by smoothing a joint distribution of characteristics of other web destination profiles, and so forth. Web destination profiles may be used by applications such as an online application for population-targeted advertising.

A method and associated system of cross-retail marketing based on analysis of multichannel clickstream data that comprises a client application capturing, aggregating, and analyzing multiple clickstreams of a user. These clickstreams may be captured from multiple unrelated or competing sales or distribution channels and from multiple electronic platforms. The analysis may use methods of artificial intelligence, text analytics, semantic analytics, or other analytical methods to infer characteristics of the user, of the user's online commercial behavior and other commercial activities, and of products or services that the user may be interested in purchasing. The output of this analysis is forwarded to other channels or platforms visited by the user in order to allow those other channels or platforms to perform targeted commercial marketing functions related to the user's prior activities. In preferred embodiments, this method may be require an active consent or other authorization from the user.

User selections entered in the media application or any user input device behavior with user devices may be recorded as clickstream data. The clickstream data may be used to deduce information about the user or a media item being consumed. A user may be profiled based on his or her input device behavior using a plurality of time-stamped indicators. A degree of user interest may be determined based on a time period between the time-stamped indicators, the number of time-stamped indicators within a period of time, and/or a type of user action.

A client component runs on a user computer in conjunction with a web browser and detects errors, such as but not limited to “404: page not found” errors, in which a requested web page or other object cannot be displayed. In response to detecting the error, the client component notifies an error processing server, which uses the URL of the failed request to identify an alternate object to display. The alternate object may, for example, be (a) an object retrieved from replacement URL, or from a URL that is otherwise related to the requested object, (b) a cached version of the requested object, (c) an object retrieved from a closely matching URL found in the user's clickstream history, or (d) a dynamically generated page that includes links to one or more of the foregoing types of alternate objects. Also disclosed are methods for identifying alternate objects for a given URL.

Displaying a funnel from clickstream data as a hierarchy to a user for analysis wherein the funnel represents an ordered path of web pages successively viewed by the user. The invention includes clickpath visualization software to enable the user to easily analyze and evaluate clickpaths by focusing only on subpaths of interest. The invention software provides the user with various functions including, but not limited to, zoom, sort, expand, reverse, preview, and activate.

Technology for predicting online user shopping behavior, such as whether a user will purchase a product, is described. An example method includes receiving current session data describing a current session for a current user, extracting a current clickstream from the current session data classifying the current clickstream as a purchase clickstream or a non-purchase clickstream by processing the current clickstream using one or more sets of Hidden Markov Model parameters produced by one or more Hidden Markov Models, and computing, using the one or more computing devices, a purchase probability that the current user will purchase a product during the current session based on the classifying.

The system of the present invention provides systems and methods for selling goods and services on, over, through, and in conjunction with the Internet. The system receives session (clickstream) information on a customer's website session from the enterprise's website and may also receive customer information on the customer from the enterprise's CRM or eCRM system. The session information referred to comprises the goods or services the customer is searching and metadata about such search and the relevant products, such as the surfing pattern itself. The system determines from the received information, based on the interaction between matching rules created using the system by the enterprise and the system's matching engine, whether the customer is a candidate for assistance from a sales associate. The system creates and indexes information on available sales associates and their performance, selling capabilities and product expertise. The system further matches the customer with at least one sales associate, ideally the most appropriate sales associate, based on the customer, session, and sales profile associate information, and facilitates communication between the sales associate and the customer. Additionally, the system provides information on the customer, products or services the customer is interested in, and the collateral sales materials (both internal and external to the enterprise) and selling techniques to the sales associate based on the particular sales opportunity. The system facilitates communication between the sales associate and the customer on the basis of chat, voice over IP, email and the public switched telephone network, including the concept of bridging a chat session into a PSTN conference call during which call the sales associate and customer maintain a co-browsing session with regard to the opportunity over the Internet.

An improved system and method for web destination profiling for online population-targeted advertising is provided. A web destination profiler may be provided for generating web destination profiles. Traffic may be analyzed at a particular web destination in order to understand the population visiting the web destination. The analysis of user traffic, including differentiated clickstream data, may be applied for determining known characteristics of a web destination profile. Moreover, unknown characteristics of a web destination profile may be determined using a variety of techniques including inferring characteristics by modeling traffic flow through other web destinations, estimating characteristics from other web destination profiles by predicting traffic flow through other web destinations, propagating characteristics to a web destination profile by smoothing a joint distribution of characteristics of other web destination profiles, and so forth. Web destination profiles may be used by applications such as an online application for population-targeted advertising.

The present invention provides for the detection of abnormal user behavior for a query session of an electronic search engine. A query session is initiated upon receipt of a user search request that includes one or more search terms. The search engine, in accordance with known search technology, generates a search results page that includes various hyperlinks, including for example web content hyperlinks, page navigation hyperlinks and advertising hyperlinks. Tracking user activities generates the clickstream associated with the search results page. The present invention determines a probability score for the clickstream and then this score is normalized. A comparison of the normalized probability score with other normalized probability scores for similar query sessions determines of the normalcy of the query session.

A computer-implemented system and method for enabling content recommendation in a content browsing and recommendation system are disclosed. The system and method in an example embodiment includes: gathering available content information related to particular items of content from a plurality of content sources via a data network; receiving user behavior information from a user platform via a clickstream processing system; processing the content information, using a data processor, to provide a searchable database of processed content information, the processed content information including a recommendation for processed content information that is likely of interest to a user based on the user behavior information received from the user platform; providing a service, accessible via the data network, to enable the user platform to request the recommendation for processed content information and to identify a selected content item; and directing at least one content source to provide the selected content item directly to the user platform.

A technique for implementing in a networked client-server environment, e.g., the Internet, network-distributed advertising in which advertisements are downloaded, from an advertising server to a browser executing at a client computer, in a manner transparent to a user situated at the browser, and subsequently displayed, by that browser on an interstitial basis, in response to a click-stream generated by the user to move from one web page to the next. Specifically, an HTML advertising tag is embedded into a referring web page. This tag contains two components. One component effectively downloads, from an distribution web server and to an extent necessary, and then persistently instantiates an agent at the client browser. This agent "politely" and transparently downloads advertising files (media and where necessary player files), originating from an ad management system residing on a third-party advertising web server, for a given advertisement into browser cache and subsequently plays those media files through the browser on an interstitial basis and in response to a user click-stream. The other component is a reference, in terms of a web address, of the advertising management system. This latter reference totally "decouples" advertising content from a web page such that a web page, rather than embedding actual advertising content within the page itself, merely includes an advertising tag that refers, via a URL, to a specific ad management system rather than to a particular advertisement or its content. The ad management system selects the given advertisement that is to be downloaded, rather than having that selection or its content being embedded in the web content page.

Large amounts of data from user interactions with web resources is available as data logs. Analysis may be performed to process the data log in order to determine the characteristics of the user interactions. Data log analysis may include identifying page states, which may be sets of frequent attributes and values that occur together in a session. The data log analysis may also include generating semantic labels of page states, which may describe the function of pages corresponding to different page states. Text mining models may be used to determine the semantic labels. Analysis may also include aggregating sets of page paths to create page journeys. These page journeys may be aggregated over all users, all user sessions, or other subsets of the clickstream. In some embodiments, comparing page journeys may provide recommendations for potential methods to improve the site and enhance user experiences.

Systems and methods for providing targeted content to a network user. In one embodiment, a method for providing targeted content to a consumer via a network during the consumer's viewing of a webpage can be provided. The method can include aggregating data from one or more of the following: crawled webpage data, vertical clickstream data, and previously stored webpage visitation data. The method can further include determining one or more trends associated with an industry vertical based at least in part on some of the aggregated data. Further, the method can include determining at least one content recommendation for the consumer based at least in part on one or more trends associated with an industry vertical. Moreover, the method can include outputting the at least one content recommendation to the consumer via the webpage.

Disclosed are systems and methods for generating viewing recommendations in a television viewing personalization system, including parsing, in accordance with a set of stored processing rules, a stream of command signals generated by a remote control unit in response to control sequences entered into the control unit by a viewer, to generate information representative of the viewer's viewing behavior; and determining, from the generated information, at least one viewing recommendation.

A method for graphical visualization of multiple clickstreams traversed by a user that involves initiating a clickstream session in response to a user log-in and intercepting and storing all navigation interactions of the user during the clickstream session by a clickstream recorder component. In response to the user's request, the stored navigation interactions of the user for the clickstream session are analyzed by a clickstream analyzer to identify segments comprising interconnected nodes sequentially traversed by the user in a single navigation path during the session and to distinguish segments comprising nodes unrelated to other nodes traversed during the session. A graphic depiction of the identified segments comprising the interconnected nodes sequentially traversed by the user in a single navigation path during the session is presented to the user by a clickstream visualizer.