An embodiment may involve a database containing a first user profile that specifies a first preferred language of a first user and a second user profile that specifies a second preferred language of a second user. The embodiment may also involve one or more processors configured to: receive, from the first user and within a chat session, a first set of messages in the first preferred language; cause the first set of messages to be translated into the second preferred language; provide, to the second user and within the chat session, the first set of messages as translated; receive, from the second user and within the chat session, a second set of messages in the second preferred language; cause the second set of messages to be translated into the first preferred language; and provide, to the first user and within the chat session, the second set of messages as translated.

Exemplary embodiments relate to a system for recovering a conversation between a user and the system when the system is unable to properly respond to a user's input. The system may process the user input and determine an error condition exists. The system may query one or more storage systems to identify candidate text data based on their semantic similarity to the user input. The storage systems may store data related to past frequently entered inputs and/or user-generated inputs. Alternative text data is selected from the candidate text data, and presented to the user for confirmation.

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.

The present teaching relates to providing a query suggestion. In one example, a request is received for query suggestions with respect to a query prefix input by a user. A plurality of query suggestions is determined based on the query prefix and a preceding query input by the user. A degree of popularity of the preceding query is determined. One or more query suggestions are selected from the plurality of query suggestions based on the degree of popularity of the preceding query. The one or more query suggestions are provided as a response to the request.

Some embodiments may perform operations of a process that includes obtaining a natural language text document and use a machine learning model to generate a set of attributes based on a set of machine-learning-model-generated classifications in the document. The process may include performing hierarchical data extraction operations to populate the attributes, where different machine learning models may be used in sequence. The process may include using a pre-trained Bidirectional Encoder Representations from Transformers (BERT) model augmented with a pooling operation to determine a BERT output via a multi-channel transformer model to generate vectors on a per-sentence level or other per-text-section level. The process may include using a finer-grain model to extract quantitative or categorical values of interest, where the context of the per-sentence level may be retained for the finer-grain model.

Embodiments of the present disclosure relate to a data analysis system that may receive data comprising a plurality of raw data items from one or more data sources, such as a monitoring agent located in a monitored network. The received data may be scored using one or more scoring rules and/or algorithms, with raw data items satisfying a score threshold designated as “data item leads.” Raw data items associated with a data item lead may be searched and displayed to the user via an interactive user interface. The data analysis system may be used to execute searches and additional enrichments against the received raw data items. The data analysis system may group received raw data items based upon shared attribute values. The data analysis system may be used to categorize received data and construct timelines, histograms, and/or other visualizations based upon the various attributes of the raw data items.

Systems and methods for conversational user experiences and conversational database analysis disclosed herein improve the efficiency and accessibility of low-latency database analytics. The method may include obtaining data expressing a usage intent with respect to the low-latency database analysis system, wherein the data expressing the usage intent includes a current request string expressed in a natural language, a current context associated with the current request string, and a previously generated context associated with a previously generated resolved-request, identifying, from the current request string, a conversational phrase corresponding to a conversational phrase pattern from a defined set of conversational phrase patterns, generating a resolved-request based on the identified conversational phrase, including the resolved-request in the current context, obtaining results data responsive to the resolved-request from a distributed in-memory database, generating a response including the results data and the current context, and outputting the response.

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.

Provided is a method for querying questions. The method includes: acquiring input information of a user; acquiring intention information of the user based on the input information of the user; determining an answer generation rule; and generating, based on the input information and the intention information, a first answer in accordance with the answer generation rule, and providing the first answer to the user.