Abstract: A method comprising a preliminary automated analysis of at least one corpus of natural language text is disclosed. For each sentence of a corpus, the method includes performing a syntactic analysis using linguistic descriptions to generate at least one syntactic structure for the sentence, building a semantic structure for the sentence, associating each generated syntactic and semantic structure with the sentence, and saving each structure. For each corpus text that was preliminary analyzed, performing an indexing operation to index lexical meanings and values of linguistic parameters of each syntactic structure and each semantic structure associated with sentences in the corpus text. A semantic search includes at least one automatic preliminary analyzed corpus of sentences comprising searched values of linguistic, syntactic and semantic parameters.

Abstract: In one embodiment, the invention provides a method for a system to provide information based on a query, the method comprising: performing a first search of at least one first source for information responsive to the query; providing a result of the search to a user; searching documents using at least a part of the result of the search; providing the user with at least one example of usage of the result of the search obtained from the searching of stored documents; based on user input, performing a second search of at least one second source for information responsive to the query; and providing a result of said second search to the user. The invention provides ways of showing the most relevant examples from parallel text corpora according to a ranking.

Abstract: In one embodiment, there is provided a computer-implemented method and system for implementing the method. The method comprises: preliminarily analyzing at least one corpus of natural language text comprising for each sentence of each natural language text of the corpus, performing syntactic analysis using linguistic descriptions to generate at least one syntactic structure for the sentence; building a semantic structure for the sentence; associating each generated syntactic and semantic structure with the sentence; and saving each generated syntactic and semantic structure; for each corpus of natural language text that was preliminarily analyzed, performing an indexing operation to index lexical meanings and values of linguistic parameters of each syntactic structure and each semantic structure associated with sentences in the corpus; and searching in at least one preliminarily analyzed corpora for sentences comprising searched values for the linguistic parameters.

Abstract: A method and system comprising an automated analysis of at least one corpus of natural language text is disclosed. For each sentence of a corpus, the analysis includes performing a syntactic analysis using linguistic descriptions to generate at least one syntactic structure for the sentence, building a semantic structure for the sentence, associating each generated syntactic and semantic structure with the sentence, and saving each generated syntactic and semantic structure. For each corpus text that was preliminary analyzed, performing an indexing operation to index lexical meanings and values of linguistic parameters of each syntactic structure and each semantic structure associated with sentences in the corpus text. A semantic search as disclosed herein includes at least one automatic preliminary analyzed corpus of sentences comprising searched values of linguistic, syntactic and semantic parameters.

Abstract: Methods and computer systems for translating sentences between languages from an intermediate language-independent semantic representation are provided. Based on a comprehensive understanding about languages and semantics, exhaustive linguistic descriptions are used to analyze sentences, build syntactic structures and language independent semantic structures and representations, and synthesize one or more sentences in a natural or artificial language. A computer system is also provided to analyze and synthesize various linguistic structures and perform translation of a wide spectrum of various sentence types. As result, a generalized data structure, such as a semantic structure, is generated from a sentence of an input language and can be transformed into a natural sentence expressing its meaning correctly in an output language. The methods and systems can be applied to automated abstracting, machine translation, natural language processing, control systems, Internet information retrieval, etc.

Abstract: Computer-implemented systems and methods align fragments of a first text with corresponding fragments of a second text, which is a translation of the first text. One preferred embodiment preliminarily divides the first and second texts into fragments; generates a hypothesis about the correspondence between the fragments of the first and second texts; performs a lexico-morphological analysis of the fragments using linguistic descriptions; performs a syntactic analysis of the fragments using linguistic descriptions and generates syntactic structures for the fragments; generates semantic structures for the fragments; and estimates the degree of correspondence between the semantic structures.

Abstract: Methods for processing machine-readable forms or documents of non-fixed format are disclosed. The methods make use of, for example, a structural description of characteristics of document elements, a description of a logical structure of the document, and methods of searching for document elements by using the structural description. A structural description of the spatial and parametric characteristics of document elements and the logical connections between elements may include a hierarchical logical structure of the elements, specification of an algorithm of determining the search constraints, specification of characteristics of searched elements, and specification of a set of parameters for a compound element identified on the basis of the aggregate of its components. The method of describing the logical structure of a document and methods of searching for elements of a document may be based on the use of the structural description.

Abstract: A system for natural language processing is provided. A first natural language processing program may be constructed using language-independent semantic descriptions, and language-dependent morphological descriptions, lexical descriptions, and syntactic descriptions of one or more target languages. The natural language processing program may include any of machine translation, fact extraction, semantic indexing, semantic search, sentiment analysis, document classification, summarization, big data analysis, or another program. Additional sets of natural language processing programs may be constructed.

Abstract: The preferred embodiments provide an automated machine translation from one language to another. The source language may contain expressions or words that are not readily handled by the translation system. Such problematic words or word combinations may, for example, include the words not found in the dictionary of the translation system, as well as text fragments corresponding to structures with low ratings. To improve translation quality, such potentially erroneous words or questionable word combinations are identified by the translation system and displayed to a user by distinctive display styles in the display of a document in the source language and in its translation to a target language. A user is provided with a capability to correct erroneous or questionable words so as to improve the quality of translation.

Abstract: In one embodiment, the invention provides a method for machine translation of a source document in an input language to a target document in an output language, comprising generating translation options corresponding to at least portions of each sentence in the input language; and selecting a translation option for the sentence based on statistics associated with the translation options.

Abstract: In one embodiment, the invention provides a method, comprising detecting data fields on a scanned document image; generating a flexible document description based on the detected data fields, including creating a set of search elements for each data field, each search element having associated search criteria; and training or modifying the flexible document description using, for example, a search algorithm to detect the data fields on additional training images based on the set of search elements.

Abstract: A method and computer system for translating sentences between languages from an intermediate language-independent semantic representation is provided. On the basis of comprehensive understanding about languages and semantics, exhaustive linguistic descriptions are used to analyze sentences, to build syntactic structures and language independent semantic structures and representations, and to synthesize one or more sentences in a natural or artificial language. A computer system is also provided to analyze and synthesize various linguistic structures and to perform translation of a wide spectrum of various sentence types. As result, a generalized data structure, such as a semantic structure, is generated from a sentence of an input language and can be transformed into a natural sentence expressing its meaning correctly in an output language.

Abstract: The preferred embodiments provide an automated machine translation from one language to another. The source language may contain expressions or words that are not readily handled by the translation system. Such problematic words or word combinations may, for example, include the words not found in the dictionary of the translation system, as well as text fragments corresponding to structures with low ratings. To improve translation quality, such potentially erroneous words or questionable word combinations are identified by the translation system and displayed to a user by distinctive display styles in the display of a document in the source language and in its translation to a target language. A user is provided with a capability to correct erroneous or questionable words so as to improve the quality of translation.

Abstract: In one embodiment, the invention provides a method for machine translation of a source document in an input language to a target document in an output language, comprising generating translation options corresponding to at least portions of each sentence in the input language; and selecting a translation option for the sentence based on statistics associated with the translation options.

Abstract: In one embodiment, the invention provides a method for a machine to perform machine-readable form pre-recognition analysis. The method comprises preliminarily assigning at least one graphic image in a form for identification of form type, preliminarily creating at least one model of the said graphic image for identification of the form type, parsing a form image into regions, determining an image form type for the form image, comprising: (a) detecting on the form image at least one of said graphic images for identification of the form type, (b) performing a primary identification of the form image type based on a comparison of the detected graphic image with the said model, and(c) performing a profound analysis using a supplementary data said-primary identification results in multiple possibilities for the form image type.

Abstract: Embodiments of the invention disclose techniques for processing of machine-readable forms of unfixed or flexible format. An auxiliary brief description may be optionally specified to determine the spatial orientation of the image. A method of searching for elements of a document comprises the following main operations in addition to the operations of preliminary image processing: selecting the varieties of structural description from several available variants, determining the orientation of the image, selecting the text objects, where the text must be recognized, and determining the minimal required volume of recognition, recognizing the text objects, searching for elements of the form. Searching for elements of the form comprises the following actions: selecting a searched element in the structural description, gaining the algorithm of search constraints from the structural description, searching for the element, testing the obtained variants.

Abstract: A system is proposed for automated document processing, comprising a document, consisting of two sections—a main section, containing data in printed character form, and a supplementary section in a machine-readable form; a document forming means; a document inputting means; a character recognition means; a main and supplementary data comparison means. Said system uses the supplementary section data to confirm the main section data. The supplementary section data can fully or partly duplicate the main section data, supplement it and also comprise other additional data. The supplementary machine-readable section can be realized in a form of coded consecutive characters, printed graphic image (bar-code), magnetic, optical, microprocessor or other kind of data storage means. For enhancing security of documents all or a part of data can be coded prior to introduction into the supplementary section.

Abstract: Described herein are methods for finding substantially similar/different sources (files and documents), and estimating similarity or difference between given sources. Similarity and difference may be found across a variety of formats. Sources may be in one or more languages such that similarity and difference may be found across any number and types of languages. A variety of characteristics may be used to arrive at an overall measure of similarity or difference including determining or identifying syntactic roles, semantic roles and semantic classes in reference to sources.

Abstract: A method and system for facilitating a semantic search based on one or more corpuses of natural language texts are provided. One or more corpuses of natural language texts are received including indexed linguistic parameters and semantic structures of lexical units. The linguistic parameters and semantic structures are generated during a preliminary syntactico-semantic analysis. Searching for text fragments satisfying a query in the one or more corpuses is performed. Relevance of the search results is estimated.

Abstract: Described herein are methods for finding substantially similar/different sources (files and documents), and estimating similarity or difference between given sources. Similarity and difference may be found across a variety of formats. Sources may be in one or more languages such that similarity and difference may be found across any number and types of languages. A variety of characteristics may be used to arrive at an overall measure of similarity or difference including determining or identifying syntactic roles, semantic roles and semantic classes in reference to sources.