152 results about "Verbnoun" patented technology

A command engine of the present invention correlates user intentions with website capabilities. Rather than merely matching words against indexes, user intentions are approximated and desired results are retrieved directly, bypassing multiple steps in the process. Preferably, the user query is written as an action verb in “do” and an object in “what”. Additional prepositional phrases further determine user intentions.

A useful object-oriented knowledge base system is provided, which comprises an 'object-oriented knowledge base', an inference mechanism, and an ideal dictionary, etc. Sentences used as a 'rule' and / or as a 'fact' in the 'object-oriented knowledge base' are described according to a simple English grammar. Hierarchical structure of nouns-system in an 'ideal thesaurus' is constructed, on the basis of special kind of 'object-oriented-lexical-definition of nouns' recorded in the ideal dictionary. Lexical meaning of a verb whose meaning is specific are derived from that of a verb whose meaning is general and universal, by using 'dichotomy' on the basis of C-language-like way of description of English sentences in the lexicon. The hierarchical structure of verbs-system in an 'ideal classification table' is constructed on the basis of them. The Inference mechanism processes not only mathematically well defined equations but, also simple English sentences, by making full use of the 'ideal thesaurus' and the 'ideal classification table', on the basis of specially contrived 'sentence based object-oriented categorical syllogism'.

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.

A structured natural language query and knowledge system is provided to allow a user who lacks programming skills to enter a database query or a rule in the form of a structured natural language sentence. The scope of the sentence is preferably defined by an improved object relational query language, an object relational algebra, or both. Command and conditions that appear in natural language form are defined with corresponding formal query texts. A user is prompted to compose a structured natural language sentence using the defined commands and conditions. The user-selected command and its arguments appear as the verb phrase of a structured natural language sentence. The user-selected conditions and their parameters appear as the adjective phrases of the sentence. The sentence is parsed and changed into a translated formal query text for formal database query and rule processing.

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.

A system for coding and decoding languages that includes a first set of computerized databases and each of database storing a predetermined number of indexed information elements (such as words) and a second set of computerized databases wherein each database includes a predetermined number of structural arrangements for using the information elements. The indexed information elements are classified by the component class of a sentence or phrase. They may be classified as verbs, adjectives, etc. and this holds true for the same indexed entry for the different databases for a particular information element. The system decodes the information elements in a sentence, or phrase and matches a corresponding structural arrangement in a given language which holds for the other language.

This invention utilizes a concept called color, which implies a variation, and applies it to natural language attributes like verbs and nouns. The verb color is defined as a role or operation in which the field participates. The noun color is defined as a form of the field. The auxiliary verb color is defined as a path to the field from a known object reference. The noun color may be defined by the user or may be determined, based on the object state in which the field resides. Equations are made generic, by making the colors of the fields parametric. The equivalence of methods and equations was established, and a method might be invoked, as if it was a rule. Similarly, processes involving several methods, and other rules, may be described by rules. A special kind of classes called conceptual classes were invented, which can project a subset of the fields of a class, as well as group and reorder a particular field found in several classes. Several objects called collaboration objects, may interact with each other in several cycles, and in each cycle, several methods of the objects are invoked. Each method may view the collaboration objects in a predefined order called collaboration sequence. Temporary variables created during processing may be stored in a global or local table, and may be assigned user defined or state based nouns. By utilizing all the mechanisms defined above, rules may be specified and evaluated in a generic manner.

A method of storing service description documents in a computerised storage system in which each document is associated with at least one verb ontological node (204) and at least one noun ontological node (254), each verb ontological node having one or more links to other verb ontological nodes and each noun ontological node having one or more links to other noun ontological nodes whereby the verb nodes form a verb space (200) and the noun nodes form a noun space (250) and a method of retrieving service description documents from a plurality of service description documents stored in this way comprising the steps of: controlling a user interface to request from a user at least one verb request term (405) and at least one noun request term (410), associating the or each verb request term (405) with a corresponding verb node (204) and the or each noun request term (410) with a corresponding noun node (254), comparing the or each corresponding verb node (204) with the or each verb node (212, 214) associated with each of the stored service description documents, comparing the or each corresponding noun node (254) with the or each noun node (262, 266) associated with each of the stored service description documents, and selecting for retrieval zero or more of the stored service description documents on the basis of the comparison steps and controlling the user interface to inform the user of the selected documents to enable the user to retrieve one or more of the selected documents.

The invention discloses an SVM based micro-blog emotion classification method fusing various kinds of emotion resources. The method includes the following steps: constructing relevant dictionaries including an emotion dictionary, a negation dictionary, and a degree adverb dictionary; performing pretreatment on different corpora, performing word segmentation and part-of-speech tagging on the corpora, and performing sentence structure analysis; comparing the segmented words and positive and negative dictionaries to acquire initial word polarity, comparing words ahead of emotion words and the word degree grade dictionary and the negation dictionary to acquire modifier weight, and multiplying the initial word polarity by the modifier weight to acquire emotion scores of each micro-blog; extracting features such as nouns, verbs, adjectives, positive and negative emotion words, degree adverb weights, emotion scores, privatives and specific symbols from part-of-speech features, emotion features, sentence pattern features, and semantic features; and inputting the extracted features into an Libsvm to perform model training so as to acquire a training model. The method can achieve emotion 5-grade classification of micro-blogs, and can accurately and roundly acquire emotion tendency of netizens.

A useful object-oriented knowledge base system is provided, which comprises an 'object-oriented knowledge base', an inference mechanism, and an ideal dictionary, etc. Sentences used as a 'rule' and / or as a 'fact' in the 'object-oriented knowledge base' are described according to a simple English grammar. Hierarchical structure of nouns-system in an 'ideal thesaurus' is constructed, on the basis of special kind of 'object-oriented-lexical-definition of nouns' recorded in the ideal dictionary. Lexical meaning of a verb whose meaning is specific are derived from that of a verb whose meaning is general and universal, by using 'dichotomy' on the basis of C-language-like way of description of English sentences in the lexicon. The hierarchical structure of verbs-system in an 'ideal classification table' is constructed on the basis of them. The Inference mechanism processes not only mathematically well defined equations but, also simple English sentences, by making full use of the 'ideal thesaurus' and the 'ideal classification table', on the basis of specially contrived 'sentence based object-oriented categorical syllogism'.

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.

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.

Disclosed herein is a system structure for extracting relations between technical terms within a large amount of literature information using verb-based patterns. The present invention provides a system that is capable of extracting relations based on verb-based patterns from abstract and bibliography databases in all fields of science and technology using a Tech Association Mining Appliance (TAMA) capable of detecting the technical terms of text and relations therebetween in academic literature databases in the fields of science and technology. The present invention has an advantage of providing a practical relation extraction system structure using a number of academic databases.

Systems, devices, and methods of the present invention are related to determining a document classification. For example, a document classification application generates a set of discourse trees, each discourse tree corresponding to a sentence of a document and including a rhetorical relationship that relates two elementary discourse units. The document classification application creates one or more communicative discourse trees from the discourse trees by matching each elementary discourse unit in a discourse tree that has a verb to a verb signature. The document classification application combines the first communicative discourse tree and the second communicative discourse tree into a parse thicket and applies a classification model to the parse thicket in order to determine whether the document is public or private.

The invention relates to a structured natural language query and knowledge system, which allows a user lack of programming experience to input database for query or input rules in the form of structured language sentences. The range of the sentences is defined by improved object-related query languages for preference, object-related algebra, or both the object-related query languages and the object-related algebra. Conditions which appear in the form of the natural language are defined by corresponding form query texts, the user is prompted to use defined instructions and conditions for arranging and structuring natural language sentences, the instructions selected by the user and the parameters thereof are used as verb phrases of structured natural language sentences to appear, and the conditions selected by the user and the parameters thereof are used as adjective phrases to appear. The sentences are divided and changed to query texts in the form of translation used for database query and rule treatment.

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.

A method for automatically analyzing the text of a document to generate verification questions to be administered to a user as a quiz for the purpose of verifying whether the user has read the document. Syntactic analysis is applied to statements (e.g. sentences) in the text to automatically generate various types of verification questions, including fill-in-the-blank, true / false, and multiple-choice questions. Nouns and proper nouns in a statement may be used to generate fill-in-the-blank questions; numerical values may be used to generate fill-in-the-blank, true / false and multiple-choice questions; and verbs, adjectives and adverbs may be used to generate true / false questions. The questions may be generated dynamically for each user, or generated once, stored and used for multiple users.

The invention discloses a spoken language evaluation method based on grammatical analysis and a spoken language evaluation system. The spoken language evaluation method is characterized in that syntax content of a voice segment can be extracted, and a syntactic tree can be established according to the syntax, and then the node similarity between the syntactic tree and the preset syntactic tree can be calculated, and the word order evaluation result of the voice segment can be acquired; the predicate verb of the voice segment can be acquired, and the predicate verb in the preset predicate verb corpus can be identified to acquire the tense evaluation result of the voice segment; the grammatical evaluation result of the voice segment can be acquired according to the word order evaluation result of the voice segment and the tense evaluation result of the voice segment. According to the invention, the spoken language evaluation can be carried out from three aspects, namely fluency, accuracy, and grammatical evaluation, and then by combining the spoken language voice quality evaluation index and the spoken language content evaluation index, the evaluation model is more objective, comprehensive, and accurate.

The invention provides an English composition grammatical mistake correction method based on rules. According to the method, an English composition grammatical mistake correction model composed of an English composition preprocessing module, a rule grammatical mistake correction processing module and a grammatical mistake correction result generating module which are sequentially connected is included. After an English composition is processed through the correction model, finally article mistakes, adjective phrase mistakes, prepositional phrase mistakes, pronoun mistakes, verb tense mistakes, verb voice mistakes, irregular verb mistakes, auxiliary verb and modal verb mistakes, subject-verb disagreement mistakes, singular and plural disagreement mistakes, set structure mistakes, conjunction mistakes, word class confusion mistakes, word reuse mistakes, punctuation mark mistakes, abbreviation mistakes and sentence initial case-sensitive mistakes in the English composition can be corrected. The problem that an English composition grammatical mistake statistics correction method is not high in mistake correction precision and has fewer mistake correction types is solved.

Systems, devices, and methods of the present invention relate to detecting a request for explanation in text. In an example, a method creates a discourse tree from a subset of 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 method forms a communicative discourse tree from the discourse tree by matching each fragment that has a verb to a verb signature. The method further identifies that the subset of text comprises a request for an explanation by applying a classification model trained to detect a request for an explanation to the communicative discourse tree.

Systems, devices, and methods of the present invention are related to determining a document classification. For example, a document classification application generates a set of discourse trees, each discourse tree corresponding to a sentence of a document and including a rhetorical relationship that relates two elementary discourse units. The document classification application creates one or more communicative discourse trees from the discourse trees by matching each elementary discourse unit in a discourse tree that has a verb to a verb signature. The document classification application combines the first communicative discourse tree and the second communicative discourse tree into a parse thicket and applies a classification model to the parse thicket in order to determine whether the document is public or private.

The invention discloses a multi-document subject discovery method based on two-layer clustering. The multi-document subject discovery method comprises the following steps: S1 using a plurality of documents as input, pretreating each document, i.e. the documents are broken up into clauses, and the clauses are broken up into words, so as to obtain a noun group and a verb group in a multi-document group, and performing emantic disambiguation processing on polysemes in the noun group and the verb group; S2 respectively performing word clustering analysis on the noun group and the verb group which are output in the step S1 according to word similarity by adopting an improved OPTICS algorithm, extracting semantic concepts, and establishing vector space models on the clauses according to the semantic concepts; S3 performing clustering analysis on the clauses by using an improved K-medoid algorithm, so as to obtain a subject. Inner semantic relations between words are extracted by the multi-document subject discovery method, and the problem of non-orthogonality among feature items when feature vectors of the clauses are established is solved.

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.

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.

The invention relates to an event sentence extraction method for a financial field. The method comprises the following steps of 1) performing company name identification by utilizing internet search and listed company name information; 2) by comprehensively considering characteristics in four aspects of statement positions, company name information, field verb information, and statement and title similarity, constructing weight expression; and 3) extracting financial event sentences from a sentence set. The invention provides an internet information-based company name identification method; few rules are used, identification is not limited by training corpora, preparations can be made fully for event sentence extraction and event element identification, and the problems of frequent use of abbreviations and serious colloquial phenomenon during company name identification are solved; and sentences are subjected to comprehensive weight calculation in the four aspects of the company name information, the field verb information, the statement and title similarity and the statement positions, and finally the financial event sentences are selected out, so that the financial event sentences can be efficiently identified and extracted.

A system stored in a non-transitory medium executable by processor circuitry is provided for generating sponsored verbs and contexts. The system includes interface circuitry for receiving a search query from a user device and query processing circuitry for identifying search results comprising entity search result objects and non-entity search result objects related to the search query. Targeting circuitry determines a set of verb keywords associated with the search result objects and analytics circuitry selects one or more sponsored verbs for at least one entity or non-entity search result. Display logic circuitry is communicatively coupled to the interface circuitry and dynamically generates interface elements for each of the one or more sponsored verbs, and displays, in response to the search query, the interface elements as a sub-component of the at least one entity or non-entity search result.

The invention relates to a predicate identification method based on a combination of rules and statistics, and belongs to the field of natural language processing and machine learning. The identification method aims at achieving high-precision and high-efficiency predicate identification. The stepped identification method identifies predicates from morphology and syntax labeled sentences, and comprises the steps of conducting morphological analysis on the sentences to be detected, obtaining suspicious predicates and a number thereof, preliminarily identifying the predicates by using preliminary identification judgment conditions, extracting relevant morphological and syntactic characteristics of the suspicious predicates dissatisfying the preliminary identification judgment conditions, judging the predicates with a decision-making tree judgment model obtained from C4.5 training, and finally summarizing identification results in the two steps to present the predicates of the sentences to be detected. The identification method has the characteristics of high accuracy rate, identification speed and identification rate for the non-verbal predicates, and the like, is applicable to the field requiring high-precision Chinese predicate identification, greatly promotes development of sentence meaning analysis, and has high application and popularization values.

The invention discloses a synonym expansion method and a synonym expansion device both used for text duplication detection, which include a text preprocessing unit used for deleting stop words in a suspected text and tagging the part-of-speech, wherein verbs, nouns, and adjectives are taken as the to-be-processed objects; through retrieving synonyms of single words, computing the Cartesian product and obtaining the initial expansion set of all word collocations in the suspected text; through comparing the initial expansion set and an actual corpus, filtering word collocations impossible in an actual language environment, simplifying the set, and obtaining the final expansion set; and during the duplication detection, according to different collocation results, giving the words different weights which are taken as the computation base for the duplication detection results. Through applying the method or the device disclosed by the embodiment of the invention, the problem of synonym replacement in text duplication can be efficiently overcome, the efficiency is higher, and the accuracy of the duplication detection is greatly improved.

Abbreviations are displayed for user-entered text commands, to facilitate discovery of keyboard shortcuts and to reinforce branding. Users enter commands by typing them into a text input field. Commands can be provided in a verb-noun structure, where the verb specifies what is to be done and the noun specifies the object or a parameter for the verb. Upon user entry of a command, or portion thereof, the entered portion is replaced by an abbreviation. The abbreviation can represent a single key, key combination, or multi-character string. The abbreviation can also include a logo or other graphic component, if desired. The abbreviation can replace the verb portion of the entered command, or it can be shown alongside or adjacent to the text input field, or it can be shown in an overlay or according to any other mechanism. A transition effect can be performed when introducing the abbreviation.

The present invention discloses a density-based text clustering algorithm research method. The method comprises the following steps: using the ICTCLAS word segmentation system to carry out word segmentation on a text in a text set, and extracting corresponding keywords from the word segmentation according to the three parts of speech of the noun, the verb, and the adjective, and the word frequency; using an improved HowNet word similarity algorithm to calculate keyword similarity of the obtained keywords; according to the keyword similarity in the text, calculating text similarity; and according to the obtained text similarity, using the density-based clustering algorithm to carry out clustering on the text, so that the performance of the existing text-related information retrieval technology can be significantly improved.