Systems, devices, and methods of the present invention create a searchable index that includes informative portions of text. In an example, a computer-implemented method creates a discourse tree from a body of text. For each non-terminal node in the discourse tree, the method identifies a rhetorical relationship associated with the non-terminal node. The method labels each terminal node associated with the non-terminal node as either a nucleus or a satellite. The method further accesses a rule associated with the rhetorical relationship, and selects, based on the rule, selects the fragment associated with the nucleus. The method creates a searchable index including the selected fragments.

A rule storing unit stores a set of rules each defining facts and a relation between the facts, and weights representing importance levels of the rules. An input data storing unit stores input data. A query storing unit stores a query. An importance level calculating unit calculates an importance level of each fact type of the facts defined by the rules. A fact data generating unit generates, for each fact type, fact data in which true/false is observed as a fact by a number corresponding to the importance level of the fact type, from the input data. A fact data storing unit stores the fact data. An inference performing unit performs probabilistic inference of a result of the query by using the fact data, the rules, and the weights. An output unit outputs a result of the inference.

Methods, non-transitory computer readable media, and computing devices for three-dimensional searching that precisely targets retrieval within diverse types of content includes retrieving web content in response to a received request from a client device. A destination page, an address within the page, and an offset distance from a starting point at the address to a correlated responsive portion of the web content to the received request is identified. The responsive web content with the identified destination page, the address, and the offset distance is provided to the requesting client device.

A computer divides a character string included in text data into a plurality of tokens. The computer searches, by performing matching processing between a token string indicating a specific number of consecutive tokens among the plurality of tokens and dictionary information including a plurality of named entities, the plurality of named entities for a similar named entity whose similarity to the token string is equal to or more than a threshold. The computer converts matching information indicating a result of the matching processing between the token string and the similar named entity into first vector data. The computer generates input data by using a plurality of pieces of vector data converted from the plurality of tokens and the first vector data. The computer generates a named entity recognition model that detects a named entity by performing machine learning using the input data.

Concepts for recreating electronic content are presented. One example comprises identifying one or more content references in one or more content sources, wherein each of the one or more content references is associated with a content item. The method then comprises, for each of the one or more identified content references, retrieving the associated content item, then normalizing the one or more retrieved content items to obtain one or more normalized content items. The method then comprises recreating electronic content by combining the one or more normalized content items.

The present disclosure may include receiving a query from a computing device at a server having a database, the query identifying a desired attribute. The present disclosure may also include searching the database to identify contact information for at least one individual having the attribute corresponding to the query. The attribute may include at least one of skills, expertise, product, organization, geography and language The contact information may be transmitted to the computing device via an electronic message identifying the contact information.

A system includes a user interface presented to a developer. The developer selects a first function to supplement functionality of a first application with external functionality available from third party applications. A code generation module provides a software object to the developer for incorporation into a first state of the first application. The first state includes a user interface element associated with an entity. User selection of the user interface element initiates preparation of a query wrapper including a combination of the entity's name and a predefined text string corresponding to the first function. The query wrapper is transmitted to a search system and a result set is received and displayed. A first item of the result set includes an access mechanism for a specified state of a target application. User selection of the first item causes the access mechanism to open the target application to the specified state.

In the field of government engagement management, for users of an employee desktop web client, it is now possible, within the web client application, to search and read articles and/or knowledge content that has been authored to external locations. Due to this integration to external, third-party applications, content and/or articles can be displayed to an agent on the employee desktop web client graphical user interface. Agents can enter free text into a specific search field and review the results in summary form, and then select an article in HTML format to progress the current interaction with the client. This functionality adds value to the agent experience and enables the agent to provide an improved service to the end client. Results may be filtered by the search engine as well. Moreover, this system and method improves the operation of the computer in that the computer running such a system in the past was not able to integrate in such a fashion in a web client format. This system and method also enables an agent to handle calls with the web client more efficiently, and allows agents on the web client to automatically classify.

Systems, apparatuses, and methods are provided for identifying a corresponding string stored in memory based on an incomplete input string. A system can analyze and produce phonetic and distance metrics for a plurality of strings stored in memory by comparing the plurality of strings to an incomplete input string. These similarity metrics can be used as the input to a machine learning model, which can quickly and accurately provide a classification. This classification can be used to identify a string stored in memory that corresponds to the incomplete input string.

Systems, methods, devices, instructions, and other examples are described for natural language processing. One example includes accessing natural language processing general encoder data, where the encoder data is generated from a general-domain dataset that is not domain specific. A domain specific dataset is accessed and filtered encoder data using a subset of the encoder data is generated. The filtered encoder data is trained using the domain specific dataset to generate distilled encoder data, and tuning values for the distilled encoder data are generated to configure task outputs associated with the domain specific dataset.