Various embodiments are generally directed to techniques for selecting a user experience design in a time-critical environment, such as based on the results of multiple classification processes while maintaining appropriate responsiveness, for instance. Some embodiments are particularly directed to selecting a website design experience based on results, or lack thereof, provided by a plurality of inference processes of varying accuracy within a predefined amount of time. For example, a page request, or indication thereof, may be received by an inference manager from a client device. In response to the page request, the inference manager may initiate one or more inference processes, and based on the response, or lack thereof, from each of the one or more inference process within a predetermine amount of time, the inference manager may provide an indication to an experience design selector. The experience design selector may then select, based on the indication, from a plurality user experience designs to provide to the client device in a page response.

A system and method for detecting webpage zones of interest. A method includes receiving at least one webpage analysis request, wherein the received at least one webpage analysis request includes at least one webpage in a website; identifying, in the at least one webpage, at least one zone, wherein the at least one zone is a content element of a webpage; classifying the at least one zone into a category of interest, wherein the classification is based on a trained machine learning model configured to classify DOM elements of the least one webpage, and wherein a category of interest is a category determined based on a functionality of the website; and storing the classification by indicating the category of interest for each zone.

A system and method for automating a task on a web page. The system and method include a recording engine, wherein a user can record a new task. Based on template matching, the system and method can be used to generate a model for carrying out the task on a new website. Based on a natural language input, the system can determine the task, specifics for implementing the task, and the web page or web pages to carry out the task on.

A system and method uses a vectorization model to determine similar elements within a web page to the known web page. The vectorization model takes a known web element and generates a first set of vectors, representative of the various properties of the web element. A vectorization model generates a second set of vectors for each element in a new web page. The first set of vectors is compared to each second set of vectors for each element in the new web page to select the most similar web element.

An information processing apparatus (100) includes a specification unit (102) that accepts a plurality of tags being specified at a timing before an input for a search, and a storage processing unit (104) that stores, in a history DB (112) and a tag history DB (116), browsing information including a uniform resource locator (URL) of a browsed web page, in association with the specified tags.

A baseline request produced from an annotated node of a document object model (DOM) tree and a label assigned to the annotated node are obtained. The label is assigned to a set of neighboring nodes of the DOM that perform a same function by recursively causing the system to, for each neighboring node to the annotated node in the DOM tree an additional request produced in response to performance of simulated human interaction with the neighboring node is identified, if the additional request matches the baseline request, the label is assigned to the neighboring node, and the neighboring node is selected to be the annotated node.

Disclosed herein is novel system and method for website rendering. In exemplary embodiments, the system and method comprise downloading a rendering engine onto a client device. The rendering engine downloads website specific data and website template data. The rendering engine merges the website specific data and website template data. The rending engine obtains website assets identified by the merged data, and a template .css file. The rendering engine renders a website utilizing the merged data, the assets and the .css file.

A website is navigated automatically in a sequential manner, for example by performing a series of specific network requests in a specified order, without necessarily using a browser, and without necessarily rendering each web page in the sequence. Interactions with a website are automatically recorded, stored, and analyzed. Requests and responses can be associated with particular input/output operations. Based on the analysis, the system can determine what data is expected by web servers, so that it can effectively simulate browser operations in connection with those web servers, and extract useful information from the data received in response to those operations. Thus, data extraction and/or other operations can be performed more efficiently and more quickly, while reducing the computing resources needed.

The present disclosure relates to a statement presentation system. The statement presentation system may include a computer-readable storage medium that may be configured to store executable modules. The computer-readable storage medium may include a statement browser that may be configured to receive a statement file and present a statement. The computer-readable storage medium may also include a statement generation engine that may be configured to modify the statement file, and generate a modified statement file. The statement generation engine may extract data from a data source based on the modified statement file, and operate the extracted data. The operation may be conducted by loadable operation code, a loadable operation library file, or a loadable operation tool. The statement generation engine may render the operated data and display the rendered data on the statement browser in the form of a statement.

A system and method for detecting webpage zones of interest. A method includes receiving at least one webpage analysis request, wherein the received at least one webpage analysis request includes at least one webpage in a website; identifying, in the at least one webpage, at least one zone, wherein the at least one zone is a content element of a webpage; classifying the at least one zone into a category of interest, wherein the classification is based on a trained machine learning model configured to classify DOM elements of the least one webpage, and wherein a category of interest is a category determined based on a functionality of the website; and storing the classification by indicating the category of interest for each zone.