Devices and techniques are generally described for a speech processing routing architecture. In various examples, first data comprising a first feature definition is received. The first feature definition may include a first indication of first source data and first instructions for generating feature data using the first source data. In various examples, the feature data may be generated according to the first feature definition. In some examples, a speech processing system may receive a first request to process a first utterance. The feature data may be retrieved from a non-transitory computer-readable memory. The speech processing system may determine a first skill for processing the first utterance based at least in part on the feature data.

The present invention relates to an artificial intelligence method and system for event predication, comprising: receiving, user messages, user activity data, event data, user identification information and transaction data; scraping webpages for additional event data; applying a natural language processing module to process the event data; constructing a training data set using the processed event data; constructing user preferences from the user messages, the user activity data, the user identification information and the transaction data; training a predictive model using the training data set to determine at least one upcoming event predictions determining to display the at least one event predictions based on the user profile; if it is determined to display one of the at least one event predictions, generating a graphical user interface display with a calendar depicting the at least one event prediction; and presenting the graphical user interface display to the user.

In one embodiment, a method includes receiving a user request from a client system associated with a user, generating a response to the user request which references one or more entities, generating a personalized recommendation based on the user request and the response, wherein the personalized recommendation references one or more of the entities of the response, and sending instructions for presenting the response and the personalized recommendation to the client system.

To enable provision of appropriate information for a user query even in a case there are multiple information provision modules which are different in answer generation processing. A query sending unit 212 sends a user query to each one of a plurality of information provision module units 220 that are different in the answer generation processing and that each generate an answer candidate for the user query. An output control unit 214 performs control such that the answer candidate acquired from each one of the plurality of information provision module units 220 is displayed on a display unit 300 on a per-agent basis with information on an agent associated with that information provision module unit 220.

A method and a computer system for performing the method of determining an initial value or lifetime value for a domain name is provided. The method for determining an initial value includes obtaining, over a communication network, a domain name from requestor; obtaining, over the communication network, one or more inputs from one or more domain name data sources; applying the one or more inputs and the domain name to an initial lifetime worth computer model, wherein the one or more inputs comprise data related to comparable historical domain names, data from a linguistic model analysis, data from a linguistic frequency list, and data related to a second-level domain to top-level domain relationship analysis; determining, by a hardware processor, an initial lifetime worth for the domain name based on the initial lifetime worth computer model; and providing the initial lifetime worth for the domain name to the requestor.

Techniques for selecting an emotion type code associated with semantic content in an interactive dialog system. In an aspect, fact or profile inputs are provided to an emotion classification algorithm, which selects an emotion type based on the specific combination of fact or profile inputs. The emotion classification algorithm may be rules-based or derived from machine learning. A previous user input may be further specified as input to the emotion classification algorithm. The techniques are especially applicable in mobile communications devices such as smartphones, wherein the fact or profile inputs may be derived from usage of the diverse function set of the device, including online access, text or voice communications, scheduling functions, etc.

A system and method for chatbot and search engine integration comprising chatbot crawler engine configured to detect all possible paths through a conversational flow between a chatbot and a user, and also comprising a chatbot search integration manager configured to receive a processed conversation flow from the chatbot crawler engine, parse the conversation flow to identify keywords and features, and build an indexable data structure which can be integrated into search engines in order to expose the information and data contained within the chatbot's knowledge base. This integration may allow search engine users to be redirected to a website hosting the chatbot when an indexed data structure comprises information relevant to a search engine query.

A computer-implemented method comprising: outputting questions to a user via one or more user devices, and receiving back responses to some of the questions from the user via one or more user devices; over time, controlling the outputting of the questions so as to output the questions under circumstances of different values for each of one or more items of metadata, wherein the one or more items of metadata comprise at least a time and/or a location at which a question was output to the user via the one or more user devices; monitoring whether or not the user responds when the question is output with the different metadata values; training the machine learning algorithm to learn a value of each of the items of metadata which optimizes a reward function, and based thereon selecting a time and/or location at which to output subsequent questions.

A third-party service may be used to assist entities in responding to requests of users. A third-party service may receive, directly or indirectly, a request of a first user for assistance from a first entity. The third-party service may request information about the first user by sending a request to a computer of the first entity. The third-party service may use the request of the first user and the information about the first user to automatically generate a response to the request of the first user. The third-party service may then transmit, directly or indirectly, the response to the first user.

The present disclosure generally relates to a computer-implemented system for intelligently retaining and recalling memory data. An exemplary method comprises receiving, via a microphone of an electronic device, a speech input of the user; receiving a text input of the user; constructing a first instance of a memory data structure based on the speech input; constructing a second instance of the memory data structure based on the text input; adding the first instance and the second instance of the memory data structure to a memory stack of the user; displaying a user interface for retrieving memory data of the user; receiving, via the user interface, a beginning of a statement from the user; retrieving a particular instance of the memory data structure from the memory stack based on the beginning of the statement; and automatically displaying a completion of the statement.