272 results about "Verb" patented technology

A method and system for automatically extracting relations between concepts included in electronic text is described. Aspects the exemplary embodiment include a semantic network comprising a plurality of lemmas that are grouped into synsets representing concepts, each of the synsets having a corresponding sense, and a plurality of links connected between the synsets that represent semantic relations between the synsets. The semantic network further includes semantic information comprising at least one of: 1) an expanded set of semantic relation links representing: hierarchical semantic relations, synset / corpus semantic relations verb / subject semantic relations, verb / direct object semantic relations, and fine grain / coarse grain semantic relationship; 2) a hierarchical category tree having a plurality of categories, wherein each of the categories contains a group of one or more synsets and a set of attributes, wherein the set of attributes of each of the categories are associated with each of the synsets in the respective category; and 3) a plurality of domains, wherein one or more of the domains is associated with at least a portion of the synsets, wherein each domain adds information regarding a linguistic context in which the corresponding synset is used in a language. A linguistic engine uses the semantic network to performing semantic disambiguation on the electronic text using one or more of the expanded set of semantic relation links, the hierarchical category tree, and the plurality of domains to assign a respective one of the senses to elements in the electronic text independently from contextual reference.

A method and system for automatically extracting relations between concepts included in electronic text is described. Aspects the exemplary embodiment include a semantic network comprising a plurality of lemmas that are grouped into synsets representing concepts, each of the synsets having a corresponding sense, and a plurality of links connected between the synsets that represent semantic relations between the synsets. The semantic network further includes semantic information comprising at least one of: 1) an expanded set of semantic relation links representing: hierarchical semantic relations, synset / corpus semantic relations verb / subject semantic relations, verb / direct object semantic relations, and fine grain / coarse grain semantic relationship; 2) a hierarchical category tree having a plurality of categories, wherein each of the categories contains a group of one or more synsets and a set of attributes, wherein the set of attributes of each of the categories are associated with each of the synsets in the respective category; and 3) a plurality of domains, wherein one or more of the domains is associated with at least a portion of the synsets, wherein each domain adds information regarding a linguistic context in which the corresponding synset is used in a language. A linguistic engine uses the semantic network to performing semantic disambiguation on the electronic text using one or more of the expanded set of semantic relation links, the hierarchical category tree, and the plurality of domains to assign a respective one of the senses to elements in the electronic text independently from contextual reference.

Systems and methods are provided for automated semantic role labeling for languages having complex morphology. In one aspect, a method for processing natural language text includes receiving as input a natural language text sentence comprising a sequence of white-space delimited words including inflicted words that are formed of morphemes including a stem and one or more affixes, identifying a target verb as a stem of an inflicted word in the text sentence, grouping morphemes from one or more inflicted words with the same syntactic role into constituents, and predicting a semantic role of a constituent for the target verb.

Methods, systems and computer programs for automatic, highly accurate machine comprehension of a plurality of segments of free form unstructured text in a natural language. The system answers a plurality of complex, free-form questions asked in a natural language, based on the totality of input text. The system further uses a multi-dimensional data model to measure the total effects of actions / verbs acting on various unique nouns present in the input text. The system may convert the questions into another multi-dimensional data model and may then compare the two data models in program memory to derive the answers to the posed questions. The system may then automatically detect unknown words and optionally look them up in digital information sources, such as online dictionaries and encyclopedias, to fill in the gaps in knowledge to answer the questions with expert-like reliability.

A system and method for estimating a metric of a proposed product from a document describing the product in an arbitrary degree of detail provides accuracy comparable to a function point assessment of a fully detailed document by parsing a document into a plurality of lines in an outline form and assigning a hierarchy to each line. Values or weights are determined for each of a relatively small plurality of key words in accordance with the key word and the hierarchy level of the line in the parsed document in which the key word is found. An adjustment is made based on a category of the key word such as nouns and verbs and the hierarchy level of the lines as compared with the number of hierarchy levels found in the document. Further adjustments may be made for subject matter domain of the product and the source or author of the document.

A mechanism for performing remote direct memory access (RDMA) operations between a first server and a second server over an Ethernet fabric. The RDMA operations are initiated by execution of a verb according to a remote direct memory access protocol. The verb is executed by a CPU on the first server. The apparatus includes transaction logic that is configured to process a work queue element corresponding to the verb, and that is configured to accomplish the RDMA operations over a TCP / IP interface between the first and second servers, where the work queue element resides within first host memory corresponding to the first server. The transaction logic includes transmit history information stores and a protocol engine. The transmit history information stores maintains parameters associated with said work queue element. The protocol engine is coupled to the transmit history information stores and is configured to access the parameters to enable retransmission of one or more TCP segments corresponding to the RDMA operations.

The invention discloses a Chinese entity relation extraction method based on keyword and verb dependency. Taking large-scale unstructured free text as target text, firstly, the text is segmented and keywords are extracted to form a text keyword thesaurus. Then the text is subjected to sentence segmentation, word segmentation, part-of-speech tagging, named entity recognition, dependency parsing, and entity corpus is constructed by combining named entity thesaurus and keyword thesaurus. According to the characteristics of Chinese sentence structure, syntactic structure and the dependency betweenwords, the entity-relation syntactic rules are constructed from verbs, and then each sentence in the text is matched with the relation syntactic rules. Finally, the relation triple is output and theset of text relation triple is obtained. The invention can make the entity relation extraction of the large-scale Chinese text more effective and more accurate.

Systems and processes are disclosed for handling a multi-part voice command for a virtual assistant. Speech input can be received from a user that includes multiple actionable commands within a single utterance. A text string can be generated from the speech input using a speech transcription process. The text string can be parsed into multiple candidate substrings based on domain keywords, imperative verbs, predetermined substring lengths, or the like. For each candidate substring, a probability can be determined indicating whether the candidate substring corresponds to an actionable command. Such probabilities can be determined based on semantic coherence, similarity to user request templates, querying services to determine manageability, or the like. If the probabilities exceed a threshold, the user intent of each substring can be determined, processes associated with the user intents can be executed, and an acknowledgment can be provided to the user.

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'.

A verbal classification system and method for the efficient sending and receiving of desired information is described. Web-site proprietors (314) and Internet marketers provide a host server (320) with descriptive data about their web-sites and messages (336) according to a predefined verbal hierarchy of nouns, verbs and modifiers. An Internet user creates a role or roles (340) that describes desired information according to the same predefined verbal hierarchy of nouns, verbs, and modifiers and transmits that role (340) to the host server (320), provides the Internet user with desired web-site addresses (336) and message by matching the role (338) to web-site and message descriptive data (336). The Internet user may access a web-site using one or more roles (340) and the web-site may provide the user with custom content by matching content (338) to the Internet user's role and roles (340). The host server (320) collects role information (340) from Internet users and web-sites to generate marketing and demographics data (346) about Internet users and web-sites (328). Internet user privacy is protected because role data (340) is encrypted and contains no personal identification information (348).

The invention provides a named entity relation extraction and construction method based on deep learning, which is applied to the technical field of internet information. The method includes, to a specific field, capturing news data within the field from a vertical website and preprocessing the captured news data; segmenting the news data, extracting key words to generate a field lexicon, and segmenting the news data again according to the field lexicon; extracting a seeded lexicon; constructing an entity relation network in an unsupervised manner, extracting sentences containing at least two entities from the news data, extracting verbs of the sentences and corresponding documents, building a word clustering model based on deep learning to the extracted documents, and constructing the entity relation network according to relation between words described by the verbs; and finally defining category of the entity relation and performing relation classification to each entity pair of the entity relation network. Without input of large-scale manpower to mark sample data, dependence to the corpus is reduced and performance of entity relation extraction is high.

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.

An approach for building an ontology is provided. Based on a grammar, extracted complex triples are syntactically transformed to identify core terms. The syntactically transformed complex triples are semantically transformed into simplified triples referring to new terms that conceptualize the core adjectives, adverbs and verbs, and assigning the core terms to respective definitions and keys in a reference ontology, thereby retaining the semantics of the complex triples. Based on a meta-schema of the reference ontology, an enrichment transformation of the simplified triples is performed to create simplified and enriched triples by adding relations derived from a correspondence each term in the simplified triples has with the reference ontology and by adding representations of semantics of reference ontology definitions of the terms. The simplified and enriched triples are stored as an ontology representing knowledge in an application providing the free-form text from which the complex triples were extracted.

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.

The invention discloses a classified processing method of internet public information. The method comprises the following steps: selecting a classified public information text as a training text, and parsing words; selecting and screening nouns and verbs, acquiring feature words by extraction, vectorizing the training text, then acquiring a PCA transformation feature matrix, a BP neural network model, and a decision tree rule; performing dimension reduction on vectors of the vector matrix of the public information text to be classified by the PCA transformation feature matrix, and transforming the vectors by the BP neural network model to obtain an output vector which has the same number of dimensions as the classified number, and then performing matching by the decision tree rule, and determining that the public information text to be classified belongs to the public information category marked by the rule if the matching is successful. As the PCA transformation converts a feature word space related to a high dimension into a low-dimensional orthogonal feature space, the disadvantage of inaccurate classification is solved; meanwhile, the decision tree rule is used for classification without data similarity comparison so that a plurality of data sources can be processed in a short time.

A system and method for semantic extraction using a neural network architecture includes indexing each word in an input sentence into a dictionary and using these indices to map each word to a d-dimensional vector (the features of which are learned). Together with this, position information for a word of interest (the word to labeled) and a verb of interest (the verb that the semantic role is being predicted for) with respect to a given word are also used. These positions are integrated by employing a linear layer that is adapted to the input sentence. Several linear transformations and squashing functions are then applied to output class probabilities for semantic role labels. All the weights for the whole architecture are trained by backpropagation.

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.

A method for processing natural language Chinese sentences can transform a Chinese sentence into a Triple representation using shallow parsing techniques. The method is concerned with parsing Chinese sentences by employing lexical and syntactical information to extract more prominent entities in a Chinese sentence, and the sentence is then transformed into a Triple representation by employing the Triple rules referring to elemental Chinese syntax—SVO (subject, verb, and object in order). The lexical and syntactical information in our method is referring a lexicon possessed of part-of-speech (POS) information and phrase-level syntax in Chinese respectively. The Triple representation consists of three elements which are agent, predicate, and patient in a sentence.

Systems and processes are disclosed for handling a multi-part voice command for a virtual assistant. Speech input can be received from a user that includes multiple actionable commands within a single utterance. A text string can be generated from the speech input using a speech transcription process. The text string can be parsed into multiple candidate substrings based on domain keywords, imperative verbs, predetermined substring lengths, or the like. For each candidate substring, a probability can be determined indicating whether the candidate substring corresponds to an actionable command. Such probabilities can be determined based on semantic coherence, similarity to user request templates, querying services to determine manageability, or the like. If the probabilities exceed a threshold, the user intent of each substring can be determined, processes associated with the user intents can be executed, and an acknowledgment can be provided to the user.

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 provides a control method of Chinese entity relationship extraction based on word co-occurrence, which comprises the steps of: a. calculating a word correlation degree by statistics of co-occurrence frequency of words; b. calculating word similarity according to the word correlation degree; and c. determining an entity relationship according to the word similarity. The invention also provides a corresponding control device. A corpus used by the method is a news corpus, so that the corpus can be directly created by extracting news texts and titles via the current mature webpage analysis technology without a large amount of manpower participating in the corpus creation; and the method is capable of obtaining such information as word frequency used for calculating the word correlation degree, word position considered when calculating the matching similarity, part of speech of the words and whether the words are verbs, and the like, by utilizing a shallow language rule, for example, participle and part of speech marking in natural language processing and simple statistical techniques, and the method can combine the semantic information of the words with a traditional mode matching method.

A method for accelerating 3D animation production, the method comprising: inputting a text string command; analyzing grammar of the text string command to find out the subject, the verb and the object or the quantity and object, through a main program. Then, the main program deliveries order to a subprogram which controlling the subject, to execute judgment and treatment of the action and behavior of the subject. After that, the subprogram finds out the default parameters relating to the relative coordinate and relationship between the subject and object, the current state of the subject, the actions and behaviors to be executed by the subject as well as environmental factors and personality of the subject. Finally, the subprogram judges and integrates those default parameters to control the subject executing appropriate actions or behaviors in response to the text string command.

A method and system are described for using business artifacts to identify elements of a component business model. Artifacts operated upon by the business are first identified, and then used to analyze the business into business operations. This is done by identifying every business activity that acts on an artifact, creating directed graphs for the business activities, and decomposing the directed graphs into sub-graphs, each sub-graph representing a business operation and being annotated by a verb expression, the annotated sub-graph representing a business service. The business services are then clustered into non-overlapping components, using common affinities reflected in the verb expressions, and organized by partitioning into internal and external operations, exposing a business service for each external operation. The components are then clustered into non-overlapping business competencies, and arranged by accountability level.

A method and system are provided in which static lists facilitate arbitrary grouping of items of data independent of their locations and in ways that are meaningful to the user. A static list is a set of items defined by a root item, a direction, and the entry relationships with that root item in that direction. The static list also defines the properties that each entry relationship in the list is required to have. Verbs are provided to manage a static list. A verb is an action that may be performed on the items in the static list, and includes, among others, move, copy, add, remove, and delete. A view is provided to specify characteristics for displaying data from a static list, including visibility, order, and formatting, among other characteristics.

A method includes receiving one or more natural language dependency parse trees as input. A hardware processor is used for processing the dependency parse trees by creating a mapping from nodes of the one or more dependency parse trees into actions, roles and contextual predicates. The mapping is used for information extraction. The actions include the verbs along with attributes of the verbs. The roles include arguments for the verbs. The contextual predicates include modifiers for the verbs.

The invention relates to a news comment webpage-based emotion tendency analysis system, which is characterized by comprising a user input model, an entity extraction and hierarchical relationship discovery module, a peer entity extraction layer, an entity feature extraction module, an entity positioning module and an emotion output module, wherein the user input module comprises a news comment webpage collection input by a user and emotion analysis rules comprising reference entities and emotive verbs; the entity extraction and hierarchical relationship discovery module is used for extracting effective entities from news comment webpages and establishing entity hierarchical relationship graph; and the peer entity extraction module positions the reference entities in the entity hierarchical relationship graph and establishes an entity emotion relationship graph consisting of an emotion relationship tree; the entity feature extraction module is used for acquiring intermediate entities in the news comment webpages and outputs emotion analysis data of the intermediate entities; and the entity positioning module judges whether the intermediate entities exist in the entity emotion relationship graph and the emotion relationship tree.