A collaborative platform applies various machine learning techniques to correlate potential purchasers with high-value articles of property that may be of interest. Attributes, characteristics, preferences, and the like of a potential purchaser are scored against attributes and features of articles. The platform learns from interaction by the agents and the potential purchasers to become more attuned to the desires and lifestyle of purchasers and to gain more and more pertinent information from the listing agents regarding high-value articles, to ultimately to arrive at a better match between a high value article for sale and a likely purchaser.

Techniques are described that include creating and retrieving equipment information via a digital distributed ledger-based system. The techniques include authenticating a user of a digital distributed ledger-based system. The techniques further include receiving an operations data from the user, wherein the operations data comprises equipment data logged during operations of an equipment. The techniques additionally include storing the operations data and identification information for the equipment in at least one or more blocks of a digital distributed ledger, and distributing the one or more blocks among nodes of the digital distributed ledger, wherein the digital distributed ledger is configured to immutably store the operations data.

In a database, product image data is accumulated. A search portion acquires product image data having the image characteristics information that is the same as or similar to the image characteristics information that indicates the characteristics of the image of input image data from the database for the input image data. A search server outputs information on another product that is different from the product corresponding to the product image data together with the product image data acquired by the search portion.

Embodiments disclosed provide a virtual currency system within a messaging application by performing operations comprising: launching, within a messaging application, a third-party application; receiving, by the messaging application from the third-party application, a request to perform an ecommerce transaction in relation to an item available for consumption on the third-party application; determining, by the messaging application, an expected attribute for the item based on accessing a database that stores expected attribute information for multiple items; verifying, by the messaging application, that an attribute of the item specified by the request corresponds to the expected attribute for the item; and processing, by the messaging application, the ecommerce transaction in response to successfully verifying that the attribute of the item satisfies a verification criterion based on the expected attribute for the item.

Aspects described herein may allow for generating a customized price rating using a machine learning algorithm. This may have the effect of improving the display of information about merchants by including customized, personalized price ratings that better reflect the tastes and preferences of a user or group of users. According to some aspects, these and other benefits may be achieved by using a machine learning model, trained to receive input corresponding to both user data and merchant data and output an indication of customized price rating(s) for the merchant that is specific to one or more users, and then to generate information about the merchant for display that includes the customized price rating(s).

Some aspects of the present disclosure are directed to computerized methods for extracting attributes from product titles. The method may include: retrieving a title associated with a product listing and historical product title data; refining the title; determining at least one tag associated with an attribute; generating, based on the at least one extracted tag and the historical title data, a first combination of one or more attributes; determining whether the title includes at least one plurality of product options, and if so: determining, for each product option hi the plurality of product options, a second combination of one or more attributes by removing attributes associated with alternative product options from the first combination; and generating a product identifier based on the second combination; and if the title does not include at least one plurality of product options, generating, the product identifier based on the first combination.

Embodiments of the disclosure provide for a knowledge search engine platform to identifying first data associated with a merchant system from one or more databases based on a search query submitted by a user device. The knowledge search engine platform generates a user dialog interface to display to the user device to enable a communication to collect additional information to supplement the first data. Second data to supplement the first data is received from the user system via the user dialog interface. Responsive to receiving the second data, a set of communications are transmitted to a set of search provider systems, where each communication of the set of communications comprising a recommended update comprising the first data and the second data.

In some embodiments, methods and systems are provided for processing information requests of workers at a retail facility and retrieving information associated with the retail facility based on the information requests. An electronic device permits a worker at the retail facility to input an information request in association with at least one worker at the retail facility or at least one product at the retail facility. A computing device receives, from the electronic device, electronic data representative of a scope of the information request, analyzes this electronic data to determine the scope of the information request, obtain relevant information from one or more databases, and transmits the obtained information to the electronic device, which in turn outputs the information to the worker.

Integrating an image capturing mechanism into an ecommerce application is described. Images of items offered for sale via ecommerce channels associated with an ecommerce service provider and performance metrics associated with the images and/or content items with which the images are presented via the ecommerce channels can be analyzed. Based partly on the analyzing, a characteristic associated with the images that are associated with a performance metric that satisfies a threshold or that are presented by the content items that are associated with the performance metric that satisfies the threshold can be determined. A new image of an item to be offered for sale by a merchant via an ecommerce channel can be received and, based at least partly on the characteristic, it can be determined whether to integrate the new image into a content item for the merchant, wherein the content item to be presented via the ecommerce channel.

A rental self-service (“RSS”) computer system, including a processor and a memory, is provided. The processor is programmed to: (i) retrieve policyholder insurance data using a claim identifier and a policyholder identifier; (ii) generate a customized link including the claim identifier and the policyholder identifier, wherein the customized link is executable on a user device to cause display of a searchable interface configured to enable the claimant to search for rentable vehicles from a plurality of vendors; (iii) in response to receiving the customized link from the user device, retrieve rental vehicle data including at least one rental vendor location and vehicle rental cost information; (iv) cause the retrieved rental vehicle data to be displayed on the user device to enable the claimant to view available rental options; and (v) receive confirmation of a rental reservation request of a selected rental option at a selected rental vendor location.