Lakshimi Duraivenkatesh

A counterfeit item detection system detects counterfeit items during an item listing processes provided by an online marketplace. The system enhances the ability of the online marketplace to identify and reject potential counterfeit items. The system collects item data in various formats. The item data is analyzed using speech-to-text software and natural language processing to determine data elements representing items, item features, and language context. Questions are generated using the items and item features, and stored for each item. Answers to the questions have associated counterfeit indication weights. The weights are modified and used to rank the questions as feedback is received about counterfeit items. The ranking determines future question selection, allowing the best questions to continually be identified and provided. The counterfeit item detection system also trains a neural network to detect counterfeit items in images, where the training images are obtained from videos related to the item.

Different action user-interface components in a comparison view are described. Initially, a selection is received to display a comparison view via a user interface of a listing platform. Multiple listings of the listing platform are selected for inclusion in the comparison view. A comparison view system determines which action of a plurality of actions, used by the listing platform, to associate with each of the listings. A display device displays the multiple listings concurrently in a comparison view via a user interface of the listing platform and also displays an action user-interface component (e.g., a button) in each of the plurality of listings. The action user-interface component is selectable to initiate the action associated with the respective listing. In accordance with the described techniques, the action user-interface component displayed in at least two of the multiple listings is selectable to initiate different actions in relation to the respective listing.

Techniques for prefetching operation cost based digital content and digital content with emphasis that overcome the challenges of conventional systems are described. In one example, a computing device may receive digital content representations of digital content from a service provider system, which are displayed on a user interface of the computing device. Thereafter, the computing device may also receive digital content as prefetches having a changed display characteristic as emphasizing a portion of the digital content based on a model trained using machine learning. Alternatively, the computing device may receive digital content as a prefetch based on a model trained using machine learning in which the model addresses a likelihood of conversion of a good or service and an operation cost of providing the digital content. Upon receiving a user input selecting one of the digital content representations, digital content is rendered in the user interface of the computing device.

Different action user-interface components in a comparison view are described. Initially, a selection is received to display a comparison view via a user interface of a listing platform. Multiple listings of the listing platform are selected for inclusion in the comparison view. A comparison view system determines which action of a plurality of actions, used by the listing platform, to associate with each of the listings. A display device displays the multiple listings concurrently in a comparison view via a user interface of the listing platform and also displays an action user-interface component (e.g., a button) in each of the plurality of listings. The action user-interface component is selectable to initiate the action associated with the respective listing. In accordance with the described techniques, the action user-interface component displayed in at least two of the multiple listings is selectable to initiate different actions in relation to the respective listing.

Systems and methods for processing webpage calls via multiple module responses are described. A system may receive, from a client device, a first call for module data associated with a set of webpage modules for presentation in a webpage. The system may subsequently transmit, to the client device based on receiving the first call, a first response including first module data associated with a first subset of the set of webpage modules. The first response may additionally include a token identifying the webpage. The server may additionally transmit, to the client device based on transmitting the first response, a second response including the token identifying the webpage and second module data associated with a second subset of the set of webpage modules that differs from the first subset of the set of webpage modules.

Technologies described reduce the amount of time between requesting content and receiving the requested content. In some embodiments, a client provides a search query. A search result page is generated and, prior to returning the search result page to the client, some or all of the search results are asynchronously pre-fetched and cached. The search query can include custom parameters that are also included in the pre-fetch requests. Web addresses in the search results page can be modified to indicate whether a prefetch operation was initiated. Once a user activates one of the search results, the responding web server uses the cached data while generating a response.