Abstract: Systems, devices, and methods of the present invention are related to determining an intent of an utterance. For example, an intent classification application accesses a sentence with fragments. The intent classification application creates a parse tree for the sentence. The intent classification application generates a discourse tree that represents rhetorical relationships between the fragments. The intent classification application matches each fragment that has a verb to a verb signature, thereby creating a communicative discourse tree. The intent classification application creates a parse thicket by combining the communicative discourse tree and the parse tree. The intent classification application determines an intent of the sentence from a predefined list of intent classes by applying a classification model to the parse thicket.

Abstract: Systems, devices, and methods of the present invention detect affective argumentation in text. In an example, an application executing on a computing device accesses text comprising fragments. The application creates a discourse tree from the text. The discourse tree includes nodes, each nonterminal node representing a rhetorical relationship between two of the fragments and each terminal node of the nodes of the discourse tree is associated with one of the fragments. The application matches each fragment that has a verb to a verb signature, thereby creating a communicative discourse tree. The application determines whether the communicative discourse tree represents text that includes affective argumentation by applying a classification model trained to detect affective argumentation to the communicative discourse tree.

Abstract: Techniques are disclosed for textual analysis. In an example, a text analysis application constructs a discourse tree that represents rhetorical relationships between fragments of text. The application matches each fragment that has a verb to a verb signature, thereby creating a communicative discourse tree. The application identifies, in the communicative discourse tree, a terminal node including a nucleus elementary discourse unit, which is dominant to a corresponding satellite elementary discourse unit. The application extracts, from the communicative discourse tree, a particular verb signature corresponding to the nucleus elementary discourse unit. The application determines a subject from the verb signature and forms a question fragment from the subject.

Abstract: Systems, devices, and methods of the present invention validate argumentation in text. In an example, an application forms a communicative discourse tree from a subset of text by matching each fragment of the subset that has a verb to a verb signature. The application identifies that the subset includes an argument by applying a classification model trained to detect argumentation to the communicative discourse tree. The application further creates a logic system based on a claim of the argument, a domain definition clause associated with a domain of the text, a set of defeasible rules based on the communicative discourse tree, and a set of facts from one or more of the communicative actions of the communicative discourse tree. The application evaluates a consistency of the argument with respect to itself and with respect to the domain definition clauses by solving the logic system, thereby validating a claim associated with the argument.

Abstract: Systems, devices, and methods provide improved autonomous agents by creating a concept lattice that represent objects and attributes and using the concept lattice to manage a dialogue with a user device. An autonomous agent application can receive queries from a user and serve response (e.g., responses identifying objects and/or object attributes) based on one or more traversals of a concept lattice. In some embodiments, the concept lattice can be generated from tabular data indicating a set of objects and respective sets of attributes. The user can provide further input to traverse from one selected node to another within the concept lattice in order to identify other nodes in the concept lattice that meet the user's needs.

Abstract: Systems, devices, and methods of the present invention relate to text classification. A text classification system accesses an utterance of text. The utterance includes at least one word. The text classification system generates a parse tree for the utterance. The parse tree includes at least one terminal node with a word type. The terminal node represents a word of the utterance. The text classification system applies one or more rules to the text. The text classification system then classifies the utterance as a question or a request for an autonomous agent to perform an action.

Abstract: Systems, devices, and methods of the present invention calculate a rhetorical relationship between one or more sentences. In an example, a computer-implemented method accesses a sentence comprising a plurality of fragments. At least one fragment includes a verb and a words. Each word includes a role of the words within the fragment. Each fragment is an elementary discourse unit. The method generates a discourse tree that represents rhetorical relationships between the sentence fragments. The discourse tree includes nodes including nonterminal and terminal nodes, each nonterminal node representing a rhetorical relationship between two of the sentence fragments, and each terminal node of the nodes of the discourse tree is associated with one of the sentence fragments. The method matches each fragment that has a verb to a verb signature, thereby creating communicative discourse tree.

Abstract: Techniques are disclosed for generating a virtual persuasive dialogue. In an example, a dialogue application receives a selection of a topic from a user device. The application identifies document results that are associated with the topic. Using communicative discourse trees, the application identifies document results that include argumentation, transforms these document results into a dialogue form, and presents the results to a user device as a virtual persuasive dialogue.

Abstract: Techniques are disclosed for detecting distributed incompetence in text of a conversation using communicative discourse trees and then inserting an automatic response from an autonomous agent (chatbot) or other entity. For example, a computing system generates a communicative discourse tree from utterances from multiple agents to a user. The computing system obtains a prediction of whether the text includes distributed incompetence by applying a trained predictive model to the communicative discourse tree. Based on the detection, the computing system generates an updated response to a user device.

Abstract: Improved techniques for dialogue management are disclosed. In particular, disclosed systems facilitate improved autonomous agents that can generate a virtual social dialogue from a corpus of text. A virtual social dialogue is a dialogue between autonomous agents and user devices. For example, a virtual social dialogue can include viewpoints, concerns, or questions of various actors on a particular topic. By presenting textual content in this manner, disclosed techniques improve information comprehension and increase the practicality of autonomous agents.

Abstract: Techniques for using noisy-robust discourse trees to determine a rhetorical relationship between sentences. In an example, a rhetoric classification application creates a noisy-robust communicative discourse tree. The application accesses accesses a first communicative discourse tree derived from a first sentence, a third sentence, and a fourth sentence and a second communicative discourse tree derived from a second sentence, the third sentence, and the fourth sentence. The application determines that syntactic parse trees cannot be generated for the first sentence and the second sentence. The application identifies a common rhetorical relationship between the first communicative discourse tree and the second communicative discourse tree. The application removes an elementary discourse unit that does not correspond to the common rhetorical relationship from the first communicative discourse tree and the second communicative discourse tree.

Abstract: Systems, devices, and methods of the present disclosure use discourse analysis and other techniques to form questions and answers from text. The questions and answers can be used for different applications, including providing a virtual dialogue or generating training data for machine-learning models. For example, a dialogue application generates a discourse tree that represents text and identifies a question from a satellite elementary discourse unit of the discourse tree. The dialogue application annotates the text by inserting the generated question and labeling the satellite elementary discourse unit as an answer.

Abstract: Systems, devices, and methods of the present invention detect argumentation in text. In an example, an application executing on a computing device accesses text comprising fragments. The application creates a discourse tree from the text. The discourse tree includes nodes, each nonterminal node representing a rhetorical relationship between two of the fragments and each terminal node of the nodes of the discourse tree is associated with one of the fragments. The application matches each fragment that has a verb to a verb signature, thereby creating a communicative discourse tree. The application determines whether the communicative discourse tree represents text that includes argumentation by applying a classification model trained to detect argumentation to the communicative discourse tree.

Abstract: Techniques are described herein for enabling autonomous agents to generate conclusive answers. An example of a conclusive answer is text that addresses concerns of a user who is interacting with an autonomous agent. For example, an autonomous agent interacts with a user device, answering user utterances, for example questions or concerns. Based on the interactions, the autonomous agent determines that a conclusive answer is appropriate. The autonomous agent formulates the conclusive answer, which addresses multiple user utterances. The conclusive answer provided to the user device.

Abstract: Systems, devices, and methods of the present invention uses noisy-robust discourse trees to determine a rhetorical relationship between one or more sentences. In an example, a rhetoric classification application creates a noisy-robust communicative discourse tree. The application accesses a document that includes a first sentence, a second sentence, a third sentence, and a fourth sentence. The application identifies that syntactic parse trees cannot be generated for the first sentence and the second sentence. The application further creates a first communicative discourse tree from the second, third, and fourth sentences and a second communicative discourse tree from the first, third, and fourth sentences. The application aligns the first communicative discourse tree and the second communicative discourse tree and removes any elementary discourse units not corresponding to a relationship that is in common between the first and second communicative discourse trees.

Abstract: An aspect of the present disclosure relate to translating natural language queries into native database queries. For example, a database application receives a natural language query from a user, divides the query into clauses, determines keywords from the clauses, and maps keywords in the query to native query that can query a database. In the case that the natural language query includes keywords that are not mapped, the application resolves an ambiguity by communicating with a user device. In the case that a keyword cannot be mapped, the application can map the keyword to a custom index that includes synonyms derived using pair-wise generalization or other techniques. Once all keywords are mapped, the database application generates a native database query and obtains results from a database.

Abstract: There is provided systems and method for content inversion for use in user searches and product recommendations. The methods include receiving a first content, wherein the first content includes a first sentence having at least one first sentiment expression, creating a syntactic parse tree of the first sentence, identifying a first sentiment in the at least one first sentiment expression, wherein the first sentiment corresponds to a first polarity, determining a first needs expression corresponding to the first sentiment, wherein the first needs expression includes a first subject. The method may further include creating a sub-tree corresponding to the first needs expression, and grouping the content with other content having similar sub-trees.

Abstract: An aspect of the present disclosure relate to translating natural language queries into native database queries. For example, a database application receives a natural language query from a user, divides the query into clauses, determines keywords from the clauses, and maps keywords in the query to native query that can query a database. In the case that the natural language query includes keywords that are not mapped, the application resolves an ambiguity by communicating with a user device. In the case that a keyword cannot be mapped, the application can map the keyword to a custom index that includes synonyms derived using pair-wise generalization or other techniques. Once all keywords are mapped, the database application generates a native database query and obtains results from a database.

Abstract: Techniques for computer-generated conversation are disclosed. In an example, a method identifies text postings from a conversation. The method creates, for each text fragment of each text posting, a syntactic tree and a discourse tree. The method creates parse thickets, each parse thicket including the syntactic tree and discourse tree of a unique pair of text postings. The method extracts, from each parse thicket, a common text segment and obtains a set of candidate search results by providing the common text segments to a search engine. The candidate search results can be further refined for relevancy and mental state and posted as a response to a conversation.

Abstract: Improved systems and methods for generating training data for classification models are disclosed. In an example, a training application accesses two fragments of text. The application represents each fragment of text as a parse thicket. The parse thickets jointly represent syntactic and discourse information. From the parse thickets, the application generalizes the text by identifying common entities or common rhetorical relations between parse thickets. The generalized text is added to a training data set, thereby increasing the coverage of the training set.