A query generation system includes a database and a processor. The database stores information to be searched, the information being associated with features having multiple types of expressions. The processor is configured to, when a character string to be used to search the database is input without constraint on a type of expression, apply a first dictionary to a character string having a first type of expression, which is included in the input character string, to generate a query for a search from the character string having the first type of expression.

Systems and methods providing drill-down access to timeline events to a user by a user interface are disclosed herein. In some embodiments, a timeline is presented to a user by the user interface. The timeline may comprise a plurality of event cards comprising event data associated with a customer. The user may select an input associated with the event card. Upon selection of the input, a second plurality of event cards indicative of an event category and associate with the customer may be displayed.

In some implementations, a user device (e.g., a computing device) can perform client-side personalization of search results. For example, a computing device can obtain search results matching user specified search parameters from a server device and/or from various services on the user device. The user device can score the search results based on various search result item attributes. After scoring, the user device can promote or demote search results items based on whether the search results item is relevant to recent user behavior. The promotion and/or demotion of search results items can cause search results items scores to be adjusted to generate a personalized score for each search result. The search results can then be ordered and/or presented based on the personalized score for each search results item. When presenting search results items, the user device can present information indicative of the source of the search results items.

A computer system is provided for retrospectively processing a data structure that includes a plurality of entries. The computer system determines if certain data transactions requests that have been recorded in the data structure could have been executed differently (e.g., by being processed at an earlier point in time). For a given entry in the data structure, the system determines if data transaction request could have at least partly succeeded against a prior recorded state of at least one of two ordered lists of pending data transaction requests. Another entry is then found that caused the initial entry to fail in execution and a time delta is stored between the timestamp of the another entry and the timestamp of the initial entry.

Methods, apparatus, systems, and articles of manufacture for training a neural network are disclosed. An example apparatus includes a training data segmenter to generate a partial set of labeled training data from a set of labeled training data. A matrix constructor is to create a design of experiments matrix identifying permutations of hyperparameters to be tested. A training controller is to cause a neural network trainer to train a neural network using a plurality of the permutations of hyperparameters in the design of experiments matrix and the partial set of labeled training data, and access results of the training corresponding of each of the permutations of hyperparameters. A result comparator is to select a permutation of hyperparameters based on the results, the training controller to instruct the neural network trainer to train the neural network using the selected permutation of hyperparameters and the labeled training data.

A two-step algorithm for conducting near real-time fuzzy searches of a target on one or more large data sets is described. This algorithm includes the simplification of the data by removing grammatical constructs to bring the target search term (and the stored database) to their base elements and then performing a Levenstein comparison to create a subset of the data set that may be a match. Then performing a scoring algorithm while comparing the target to the subset of the data set to identify any matches.

Technology is disclosed herein for enhanced similarity search. In an implementation, a search environment includes one or more computing hardware, software, and/or firmware components in support of enhanced similarity search. The one or more components identify a modality for a similarity search with respect to a query object. The components generate an embedding for the query object based on the modality and based on connections between the query object and neighboring nodes in a graph. The embedding for the query object provides the basis for the search for similar objects.

One or more embodiments relate to a computer implemented method that includes extracting file attribute values for multiple files on a conferencing endpoint, and extracting, from a conferencing application, conference attribute values. Responsive to a trigger of a file share via the conferencing application and during a conference call, the computer implemented method further includes selecting a matching file from the multiple files by applying a matching algorithm to the conference attribute values and the file attribute values, and presenting, during the conference call, recommended content including the matching file.

Systems and methods providing drill-down access to timeline events to a user by a user interface are disclosed herein. In some embodiments, a timeline is presented to a user by the user interface. The timeline may comprise a plurality of event cards comprising event data associated with a customer. The user may select an input associated with the event card. Upon selection of the input, a second plurality of event cards indicative of an event category and associate with the customer may be displayed.

A computer system is provided for retrospectively processing a data structure that includes a plurality of entries. The computer system determines if certain data transactions requests that have been recorded in the data structure could have been executed differently (e.g., by being processed at an earlier point in time). For a given entry in the data structure, the system determines if data transaction request could have at least partly succeeded against a prior recorded state of at least one of two ordered lists of pending data transaction requests. Another entry is then found that caused the initial entry to fail in execution and a time delta is stored between the timestamp of the another entry and the timestamp of the initial entry.