A system for adaptively adjusting related search words are provided. The system includes an input device, a search log collection module, a threshold setting module and a process evolution module. The input device receives a search word. The search log collection module determines whether the cumulative search count of the search word is greater than a first threshold or less than a second threshold. The threshold setting module sets the first threshold and the second threshold in terms of the number of search logs. When the cumulative search count of the search word is between the first threshold and the second threshold, the process evolution module optimizes the middle search process to find out at least one related word and/or at least one historical search word most related to the attributes or content of the search word from the indexed text and the historical search log.

Systems, apparatuses, and methods for providing content using notifications with content-specific keywords are provided. In one example embodiment, a method includes identifying, by one or more computing devices, a media content item for a user of a user device. The method includes generating, by the one or more computing devices, a keyword for the user of the user device based at least in part on data associated with the media content item. The keyword is indicative of the media content item. The method includes providing, by the one or more computing devices to the user device, for display a notification indicating that the media content is available for the user. The notification includes the keyword and the keyword is viewable by the user.

Aspects of the present disclosure relate to systems and methods for dynamically adjusting queries based on data protection configurations. In one example, a request for data is received from an application. The data is indexed in at least one of a first index database, a second index database and a third index database. A first key notification indicating a protection status of a personal device is received. A query is sent to each of the first index database, the second index database and the third index database for the requested data based on the protection status of the personal device. The requested data is loaded into the application. A second key notification indicating a change in the protection status of the personal device is received. At least some of the loaded data is removed from the application based on the change in the protection status of the personal device.

Techniques for reducing CPU consumption in a federated search are disclosed. In some example embodiments, a computer-implemented method comprises determining an initial search scope by selecting a subset of searchable resources from a plurality of searchable resources based on interaction data of a user, with the initial search scope being defined by the selected subset of searchable resources, and the interaction data indicating online activity of the user directed towards past search results of past search queries submitted by the user. A federated search for a current search query is then performed using the initial search scope, with the federated search for the current search query being restricted to only the subset of searchable resources, and current search results for the current search query are generated based on the performing of the federated search.

A resource-efficient technique is described for producing and utilizing a set of trained embeddings. With respect to its training phase, the technique receives a group of sparsely-expressed training examples of high dimensionality. The technique processes the training examples using a distributed training framework of computing devices. With respect to its inference stage, the technique draws on the embeddings produced by the training framework. But in one implementation, the inference-stage processing applies a different prediction function than that used by the training framework. One implementation of interference-stage processing involves determining a distance between a query embedding and a candidate item embedding, where each such embedding is obtained or derived from the trained embeddings produced by the training framework. Another manifestation of inference-stage processing involves adjusting click counts based on identified relations among items embeddings.

A tangible, non-transitory machine-readable medium includes machine-readable instructions that, when executed by one or more processors, cause the one or more processors to access user information, generate a cloud representation having a plurality of word clouds with varying levels of emphasis based at least in part on the user information, and output the cloud representation on a display of a computing device. The plurality of word clouds include one or more word clouds, one or more image clouds, or both.

A customer inputs a question sentence indicating a problem that the customer needs to resolve, to an automatic question answering system, and the system answers the question sentence. A history of the conversation is recorded in the system as conversation history data. When the system fails to give a suitable answer in a question-and-answer session, the system escalates the question to a support representative. In such a case, the question sentences and an answer sentence given by the support representative to resolve the problem are added to question-answer pair data as new question-answer pairs. The accuracy of automatic question answering is thus enhanced.

The systems and methods disclosed herein can increase the speed and ease with which a user can discover compatible replacement parts for a specified model of a product by automatically determining when the user is interested in replacement parts. A replacement part system can conclude that a user is looking for replacement parts based on the user's search queries, the user's browsing behavior, or the user's prior purchases. By automatically deducing an intention to purchase a replacement part, the replacement part system can make it easier for a user to locate suitable replacement parts. In addition, the replacement part system can be configured to tailor listing set of replacement parts search results it provides to a user. The set of search results can be tailored based on a number of criteria to increase the speed with which the user finds a compatible replacement part.

The current document is directed to a query-as-a-service system (“QAAS system”) that collects enormous volumes of data from network-connected entities, referred to as “Things” in the phrase “Internet of Things,” persistently stores the collected data and provides a distributed-query-execution engine that allows remote clients to continuously execute queries against the collected data. In a described implementation, both the raw data and query results are persistently stored in the QAAS system, with the raw data stored for significantly longer periods of time. Query results generated by the query-processing engine are securely transmitted to QAAS remote clients for distribution to file systems, storage.

Aspects of the present disclosure relate to systems and methods for dynamically adjusting queries based on data protection configurations. In one example, a request for data is received from an application. The data is indexed in at least one of a first index database, a second index database and a third index database. A first key notification indicating a protection status of a personal device is received. A query is sent to each of the first index database, the second index database and the third index database for the requested data based on the protection status of the personal device. The requested data is loaded into the application. A second key notification indicating a change in the protection status of the personal device is received. At least some of the loaded data is removed from the application based on the change in the protection status of the personal device.