144 results about "Verbnoun" patented technology

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.

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.

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.

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.

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.

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.

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.

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.

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.

A structured natural language inquire and knowledge system allows user lacked programming experience to input database inquire or rule input with structured language sentence. The sentence range is superior defined by improved SQL, SCA or both pf them. The conditions appeared in natural language format inquire text definition by corresponding format. User is prompted to use defined command and conditions to arrange and structure natural language sentence. The command and conditions user selected appear as verb phrase of structured natural language sentence, and the conditions and its parameters user selected appear as adjective phrase. The sentence is separated and changed to inquire text with translation format for database inquire and rule process.

The invention discloses a Japanese verb identification method for machine translation and belongs to the field of natural language processing. The method has the advantages that the method is based on rules and combines with dictionaries by analyzing the conjugated form rules of Japanese verbs, the verbs in a text can be identified completely, and basic forms of the verbs can be obtained by form restoration; the method can use common universal dictionaries and is high in adaptability and robustness; by the method, the lexical analysis accuracy and bilingual word corresponding effect in machine translation are increased, and the translation quality of machine translation is increased as a whole.