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.

A phrase that includes a trigger word that modifies a meaning within the phrase is received. The trigger word is identified. The words of the phrase that are modified by the trigger word are identified by analyzing features of the phrase that link the trigger word to other words. The phrase is interpreted by modifying the second subset of words according to the modification of the trigger word.

Embodiments are directed to organizing conversation information. Two or more machine learning (ML) models and a plurality of sentences provided from a conversation may be employed to generate insight scores for each sentence such that each insight score correlates to a probability that its sentence includes one or more of an action or a question. In response to one or more sentences having insight scores that exceed a threshold value an information score and a definiteness score may be determined for the one or more sentences. And one or more insights associated with the conversation may be generated based on the one or more sentences. A report may be generated that associates the one or more insights with one or more portions of the conversation that include the one or more sentences that are associated with the insights.

A system for parsing separate intents in natural language speech configured to (i) receive, from the user computer device, a verbal statement of the user including a plurality of words; (ii) translate the verbal statement into text; (iii) label each of the plurality of words in the verbal statement; (iv) detect one or more potential splits in the verbal statement; (v) divide the verbal statement into a plurality of intents based upon the one or more potential splits; and (vi) generate a response based upon the plurality of intents.

A syntax analyzing device includes: a syntax analyzing unit that analyzes syntax of a sentence received by a receiving unit, thereby acquiring a first analysis result, which is an analysis result having one or more elements constituting the sentence and parts of speech of the respective one or more elements and has one or more binary trees each having the parts of speech or the elements as nodes; a category acquiring unit that acquires categories of the respective one or more elements constituting the sentence; a category inserting unit that acquires a second analysis result in which the categories of the elements are respectively inserted between the elements and the parts of speech of the elements, which respectively correspond to the one or more categories, and constituting the first analysis result; and a learning unit that outputs the second analysis result acquired by the category inserting unit.

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.

A method for generating summaries includes selecting a first subset of text units of a text composition to incorporate into a first summary of the text composition using a weighting of the text units that indicates for each text unit a relative importance of including the text unit in summaries of the text composition. The weighting of the text units is modified to reduce the relative importance of each text unit in the first subset based on the text unit having been selected for the first subset. A second subset of the text units is selected to incorporate into a second summary of the text composition using the modified weighting of the text units. At least one of the first summary and the second summary are provided to a user device.

There is provided a system and a method of generating an annotated structured dataset, comprising: receiving a medical classification term, searching over the unstructured patient data for extracting unclassified unstructured text fragments, presenting a subset of the unclassified unstructured text fragments, receiving an indication of a selection of none or at least one of the text fragments, and one of: (i) classifying non-selected unclassified unstructured text fragments according to the medical classification term, and classifying selected text fragments as not satisfying the medical classification term, and (ii) classifying selected unclassified unstructured text fragments according to the medical classification term, and classifying non-selected unclassified unstructured text fragments as not satisfying the medical classification term, and iterating the searching, and/or the presenting, until no text fragments are obtained by the search, wherein the annotated structured dataset is created by the classification of unclassified unstructured text fragments into the medical classification term.

There is provided a system and a method of generating an annotated structured dataset, comprising: receiving a medical classification term, searching over the unstructured patient data for extracting unclassified unstructured text fragments, presenting a subset of the unclassified unstructured text fragments, receiving an indication of a selection of none or at least one of the text fragments, and one of: (i) classifying non-selected unclassified unstructured text fragments according to the medical classification term, and classifying selected text fragments as not satisfying the medical classification term, and (ii) classifying selected unclassified unstructured text fragments according to the medical classification term, and classifying non-selected unclassified unstructured text fragments as not satisfying the medical classification term, and iterating the searching, and/or the presenting, until no text fragments are obtained by the search, wherein the annotated structured dataset is created by the classification of unclassified unstructured text fragments into the medical classification term.

Disclosed are method and apparatus for speech analysis. The speech analysis apparatus and a server are capable of communicating with each other in a 5G communication environment by executing mounted artificial intelligence (AI) algorithms and/or machine learning algorithms. The speech analysis method and apparatus may collect and analyze speech data to build a database of structured speech data.