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Abbyy Infopoisk Llc patents


Recent patent applications related to Abbyy Infopoisk Llc. Abbyy Infopoisk Llc is listed as an Agent/Assignee. Note: Abbyy Infopoisk Llc may have other listings under different names/spellings. We're not affiliated with Abbyy Infopoisk Llc, we're just tracking patents.

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Verification of information object attributes

Systems and methods for utilizing user-verified data for training confidence level models. An example method comprises: receiving a first attribute value and a second attribute value associated with an information object representing an entity referenced by a natural language text; receiving a first confidence level associated with the first attribute value and a second confidence level associated with the second attribute value; responsive to determining that the first confidence level falls below a threshold confidence value, displaying the first attribute value using a verification graphical user interface; responsive to receiving, via the verification graphical user interface, a first input verifying the first attribute value, performing at least one of: increasing the first confidence level by a first pre-defined value or setting the first confidence level to a second pre-defined value; displaying the second attribute value using the verification graphical user interface; and responsive to failing to receive, before a triggering event, via the verification graphical user interface, a second input verifying the second attribute value, performing at least one of: increasing the second confidence level by a third pre-defined value or setting the second confidence level to a fourth pre-defined value, wherein the third pre-defined value is less than the first pre-defined value and the fourth pre-defined value is less than the second pre-defined value.. ... Abbyy Infopoisk Llc

Utilizing user-verified data for training confidence level models

Systems and methods for utilizing user-verified data for training confidence level models. An example method comprises: performing syntactico-semantic analysis of a natural language text to produce a plurality of semantic structures; interpreting, using a set of production rules, the plurality of semantic structures to extract a plurality of information objects representing entities referenced by the natural language text; determining an attribute value for an information object of the plurality of information objects; determining a confidence level associated with the attribute value, by evaluating a confidence function associated with the set of production rules; responsive to determining that the confidence level falls below a threshold confidence value, verifying the attribute value; appending, to a training data set, at least part of the natural language text referencing the information object and the attribute value; and determining, using the training data set, at least one parameter of the confidence function.. ... Abbyy Infopoisk Llc

Information extraction using alternative variants of syntactico-semantic parsing

Systems and methods for information extraction using alternative variants of syntactico-semantic analysis. An example method comprises: performing a syntactico-semantic analysis of at least part of a natural language text to produce a plurality of syntactico-semantic structures representing the part of the natural language text, wherein the plurality of syntactico-semantic structures comprises a first alternative syntactico-semantic structure and a second alternative syntactico-semantic structure; merging the plurality of syntactico-semantic structures to produce a merged syntactico-semantic structure; and identifying, within the part of the natural language text, one or more information objects by interpreting the merged syntactico-semantic structure to associate one or more tokens comprised by the part of the natural language text with a category of information objects.. ... Abbyy Infopoisk Llc

Smart document building using natural language processing

A smart document generator receives a natural language text that comprises a plurality of text regions, performs natural language processing analysis of the natural language text to determine one or more semantic relationships within the plurality of text regions, generates a search query based on the results of the natural language processing to search for additional content related to at least one text region of the plurality of text regions, and transmits the search query to available information resources. Upon receiving additional content items that each relate to a respective text region in response to the search query, a combined document is generated that includes a plurality of portions, each of the plurality of portions comprising one of the plurality of text regions, and at least one of the plurality of portions further comprising one or more of the plurality of additional content items that relate to a respective text region.. ... Abbyy Infopoisk Llc

Extracting facts from natural language texts

Systems and methods for extracting facts from natural language texts. An example method comprises: receiving an identifier of a token comprised by a natural language text, wherein the token comprising at least one natural language word references a first information object; receiving identifiers of a first plurality of words representing a first fact of a specified category of facts, wherein the first fact is associated with the first information object of a specified category of information objects; identifying, within the natural language text, a second plurality of words; and responsive to receiving a confirmation that the second plurality of words represents a second fact associated with a second information object of the specified category of information objects, modifying a parameter of a classifier function that produces a value reflecting a degree of association of a given semantic structure with a fact of the specified category of facts.. ... Abbyy Infopoisk Llc

Aspect-based sentiment analysis using machine learning methods

Systems and methods for aspect-based sentiment analysis using machine learning methods. An example method comprises: performing, by a computer system, a syntactico-semantic analysis of at least part of a natural language text to produce a plurality of syntactico-semantic structures representing the part of the natural language text; interpreting the syntactico-semantic structures using a set of production rules to detect, within the part of the natural language text, at least one aspect term representing an aspect associated with a target entity; and evaluating, using one or more text characteristics produced by the syntactico-semantic analysis, a classifier function to determine a polarity associated with the aspect term.. ... Abbyy Infopoisk Llc

Aspect-based sentiment analysis and report generation using machine learning methods

Systems and methods for aspect-based sentiment analysis using machine learning methods. An example method comprises: receiving, by a computer system, a custom dictionary comprising a list of lexemes referencing at least one of: a target entity or an aspect associated with the target entity; performing, using the custom dictionary, a syntactico-semantic analysis of at least part of a natural language text to produce a plurality of syntactico-semantic structures representing the part of the natural language text; evaluating, using one or more text characteristics produced by the syntactico-semantic analysis, a classifier function to determine polarities associated with one or more aspect terms; and generating a report comprising the aspect terms and polarities of aspects referenced by the aspect terms.. ... Abbyy Infopoisk Llc

Multi-stage recognition of named entities in natural language text based on morphological and semantic features

Systems and methods for multi-stage recognition of named entities based on morphological and semantic features of natural language texts. An example method comprises: performing a lexico-morphological analysis of a natural language text comprising a plurality of tokens, each token comprising at least one natural language word; determining, based on the lexico-morphological analysis, one or more lexical meanings and grammatical meanings associated with each token of the plurality of tokens; for each token the plurality of tokens, evaluating one or more classifier functions using the lexical and grammatical meanings associated with the tokens, wherein a value of each classifier function is indicative of a degree of association of the token with a category of named entities; performing a syntactico-semantic analysis of at least part of the natural language text to produce a plurality of semantic structures representing the part of the natural language text; and interpreting the semantic structures using a set of production rules to determine, for one or more tokens comprised by the part of the natural language text, a degree of association of the token with a category of named entities.. ... Abbyy Infopoisk Llc

Determining confidence levels associated with attribute values of informational objects

Systems and methods for determining confidence levels associated with attribute values of informational objects. An example method comprises: receiving a natural language text; performing syntactico-semantic analysis of the natural language text to produce a plurality of semantic structures; interpreting the plurality of semantic structures using a set of production rules to produce a plurality of data items, each data item associating an attribute value with an informational object representing an entity referenced by the natural language text; and determining, for at least one data item of the plurality of data items, a confidence level associated with the attribute value, by evaluating a confidence function associated with the set of production rules.. ... Abbyy Infopoisk Llc

Evaluating text classifier parameters based on semantic features

Systems and methods for evaluating text classifier parameters based on semantic features. An example method comprises: performing a semantico-syntactic analysis of a natural language text of a corpus of natural language texts to produce a semantic structure representing a set of semantic classes; identifying a natural language text feature to be extracted using a set of values of a plurality of feature extraction parameters; partitioning the corpus of natural language texts into a training data set comprising a first plurality of natural language texts and a validation data set comprising a second plurality of natural language texts; determining, in view of the category of the training data set, the set of values of the feature extraction parameters; validating the set of values of the feature extraction parameters using the validation data set.. ... Abbyy Infopoisk Llc

Natural language text classification based on semantic features

An example method for natural language text classification based on semantic features comprises: performing semantico-syntactic analysis of a natural language text to produce a semantic structure representing a set of semantic classes; associating a first semantic class of the set of semantic classes with a first value reflecting a specified semantic class attribute; identifying a second semantic class associated with the first semantic class by a pre-defined semantic relationship; associating the second semantic class with a second value reflecting the specified semantic class attribute, wherein the second value is determined by applying a pre-defined transformation to the first value; evaluating a feature of the natural language text based on the first value and the second value; and determining, by a classifier model using the evaluated feature of the natural language text, a degree of association of the natural language text with a particular category of a pre-defined set of categories.. . ... Abbyy Infopoisk Llc

Extracting entities from natural language texts

Systems and methods for creating ontologies by analyzing natural language texts. An example method comprises: receiving identifiers of a first plurality of word groups within a natural language text, each word group comprising one or more natural language words; associating an object represented by each word group with a concept of an ontology; identifying, within the natural language text, a second plurality of word groups, wherein each word group of the second plurality of word groups is associated with the concept of the ontology; responsive to receiving a confirmation that a word group of the second plurality of word groups represents an object associated with the concept of the ontology, modifying a parameter of a classification model that produces a value reflecting a degree of association of a given object with the concept of the ontology.. ... Abbyy Infopoisk Llc

Identifying word collocations in natural language texts

Systems and methods for identifying word collocations in natural language texts. An example method comprises: performing, by a computing device, semantico-syntactic analysis of a natural language text to produce a plurality of semantic structures; generating, in view of relationships defined by the semantic structures, a raw list of word combinations; producing a list of collocations by applying a heuristic filter to the raw list of word combinations; and using the list of collocations to perform a natural language processing operation.. ... Abbyy Infopoisk Llc

Extracting information from structured documents comprising natural language text

Systems and methods for extracting information from structured documents comprising natural language text. An example method comprises: receiving a table comprising a natural language text; identifying, within the table, a header and a plurality of cells organized into rows and columns; performing semantico-syntactic analysis of the natural language text to produce a plurality of semantic structures; interpreting the plurality of semantic structures using a first set of production rules to produce a data object representing the table; analyzing the header to identify a plurality of ontology classes associated with respective table columns; and modifying the data object representing the table using a second set of production rules associated with the ontology classes associated with the table columns.. ... Abbyy Infopoisk Llc

02/02/17 / #20170031900

Automatic training of a syntactic and semantic parser using a genetic algorithm

Disclosed are methods, systems, and computer-readable mediums for automatic training of a syntactic and semantic parser using a genetic algorithm. An initial population is created, where the initial population comprises a vector of parameters for elements of syntactic and semantic descriptions of a source sentence. ... Abbyy Infopoisk Llc








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