The present disclosure relates generally to Lightweight Directory Access Protocol (LDAP), and more particularly, to techniques for improving query performance on an LDAP server. One particular technique includes receiving a LDAP query having search criteria, identifying one or more search filters within the search criteria, determining candidate indices based on the identified one or more search filters, evaluating the candidate indices based on statistics collected for the candidate indices, selecting one or more indices from the candidate indices based on the evaluating, and executing the LDAP query on an LDAP directory using the selected one or more indices.

Disclosed herein is a search method performed by a server, including: receiving a user question from a user terminal; generating a user question vector for the user question; selecting similar question candidates based on a similarity to the user question vector; generating an answer to the user question based on the similar question candidates; and transmitting the answer to the user question to the user terminal.

The present teaching relates to a method, system and programming for operating a data storage. The data storage comprises of different portions including: a first portion having a plurality of metadata objects stored therein, each of the metadata objects being associated with a filter and corresponding to a range of keys, wherein at least one of the metadata objects is associated with a data structure, and a second portion having a plurality of files stored therein, each of the plurality of files being associated with one of the plurality of metadata objects; The data storage synchronizes a scan request with respect to one or more write requests based on a parameter associated with the scan request and each of the one or more write requests.

Embodiments relate to an intelligent computer platform to identify a lexical answer type (LAT), a first concept relevant to the received request and a second concept related to the identified first concept. The LAT, together with the first and second concepts are utilized to create a first and second cluster. Documents are selectively populated into the clusters. The clusters are subject to sorting based on a relevancy protocol.

An online concierge system generates an item graph connecting item nodes with attribute nodes of the items. Example attributes include a brand, a category, a department, or any other suitable information about the item. When the online concierge system receives a search query to identify one or more items from a customer, the online concierge system parses the search query into combinations of terms and identifies item nodes and attribute nodes related to the search query. The online concierge system identifies item nodes and attribute nodes that are likely to result in a conversion. Information about the identified nodes is presented to the customer. The customer may select an item node to purchase the item, or an attribute node to execute a new search query based on terms associated with the attribute node.

An electronic device obtains a plurality of collections of media content items, each collection of media content items being associated with text generated by one or more users of the media-providing service. The electronic device determines a coincidence metric for a first descriptor and a first media content item, the coincidence metric corresponding to a likelihood that the first descriptor appears in the text associated with a respective collection of media content items that includes the first media content item. Based on the coincidence metric, the electronic device generates a new collection of media content items for a first user. The new collection of media content items corresponds to the first descriptor and includes the first media content item.

Embodiments of the present disclosure provide methods, apparatus, systems, computer program products for transferring a performance of a procedure found in technical documentation for an item via an interactive electronic technical manual system (IETM) configured to provide electronic and credentialed access to the technical documentation. In one embodiment, a method is provided comprising: providing the steps of the procedure in an order in which the steps are to be carried out; and while a user is participating in the performance of the procedure: causing a particular step that is being carried out to be highlighted; receiving input of a selection of a transfer mechanism and in response: causing an indication to be displayed between the particular step and a next step to be carried out identifying where the performance has been suspended; providing a transfer window displaying transfer information; and recording the transfer information and an identifier for the indication.

Methods, systems, and program products for streamlined auditing that receive an input audit request via the data interface; source entity type data (ETD) from one or more databases; prepare the ETD for input into an entity clustering module; match the ETD via the entity clustering module to locate linkages within the ETD and discover relationships amongst one or more entities identified within the ETD; cluster datapoints in the ETD that refer to the same real-world entities; analyze the ETD relationships via an entity intelligence module to identify and segment targeted entities, from the one or more entities, that are applicable to the audit request; generate inclusion lists of those targeted entities that are determined to fulfill the audit request; finalize the inclusion lists of targeted entities that fulfill the audit request to generate streamlined audit results; and output the streamlined audit results to an end user.

A system and method for modeling preferences of customers to drive personalized contextual recommendations using cognitive deep constrained filtering includes receiving a user query on an online retail platform, in response to receiving the user query, performing a first online matrix manipulation and a second online matrix manipulation, and sending a list of ranked recommended products.

Assets in an asset portfolio are evaluated using historical data and, optionally, additional other measurable characteristics for the assets in the asset portfolio. Each asset is assigned a valuation that represents past consumption and expected future consumption of the asset. The valuation is used to create recommended sets of assets from the asset portfolio. The recommended sets of assets are sent to user devices for consumption which is further monitored for accuracy.