Abstract: A method and computer system for analyzing sentences of various languages and constructing a language-independent semantic structure are provided. On the basis of comprehensive knowledge about languages and semantics, exhaustive linguistic descriptions are created, and lexical, morphological, syntactic, and semantic analyses for one or more sentences of a natural or artificial language are performed. A computer system is also provided to implement, analyze and store various linguistic structures and to perform lexical, morphological, syntactic, and semantic analyses. As result, a generalized data structure, such as a semantic structure, is generated and used to describe the meaning of one or more sentences in language-independent form, applicable to automated abstracting, machine translation, control systems, Internet information retrieval, etc.

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: Various embodiments are provided for enabling audio tagging of image files. The audio messages are obtained by the system, usually by recording an audio message from a user, and then converted into a textual tag, using speech recognition technology. In some implementations semantic analysis of text component of these massages is performed. In some implementations the textual tags are then propagated to other image files associated with the user.

Abstract: Disclosed is a method for translating text fragments displayed on a screen from an input language into an output language and displaying the result. Translation may use electronic dictionaries, machine translation, natural language processing, control systems, information searches, (e.g., search engine via an Internet protocol), semantic searches, computer-aided learning, and expert systems. For a word combination, appropriate local or network accessible dictionaries are consulted. The disclosed method provides a translation in grammatical agreement in accordance with grammatical rules of the output language in consideration of the context of the text.

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: 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. A natural language compiler (NLC) system is used to translate the sentence from the source language into a target language based on the syntactic and semantic descriptions of the source sentence. A vector of quality ratings is generated where each quality rating in the vector of quality ratings is of a corresponding parameter in the vector of parameters. Quality ratings are evaluated according to specific criterion, which comprise parameters such as a BLEU score and a number of emergency sentences. A number of parameters in the vector of parameters are replaced with adjusted parameters.

Abstract: The present disclosure provides methods and systems for performing syntactic analysis of a text. In some implementations the method includes performing rough syntactic analysis of the text, generating a graph of generalized constituents of the text and filtering arcs of the graph of generalized constituents with a combination classifier which includes a tree classifier and one or more linear classifiers. The combination classifier is trained using parallel analysis of an untagged two-language text corpus.

Abstract: Various embodiments are provided for enabling audio tagging of image files. The audio messages are obtained by the system, usually by recording an audio message from a user, and then converted into a textual tag, using speech recognition technology. In some implementations semantic analysis of text component of these massages is performed. In some implementations the textual tags are then propagated to other image files associated with the user.

Abstract: An illustrative method according to a set of instructions stored on a memory of a computing device includes receiving, by a processor of the computing device, a search input. The method further includes determining, by the processor, the presence of a plurality of electronic files related to the search input. The method further includes displaying, by the processor, on a graphical user interface (GUI), representative information of the plurality of electronic files related to the search input, where the representative information comprises a hierarchical tree structure.

Abstract: Various embodiments are provided for enabling tagging of image files based on tagging or commenting on images on a social networking site. The tagging or commenting on an image on the social networking site is detected by the system. The social network tag or comment is analyzed to determine a textual tag to be assigned to image files corresponding to the social network images that have been tagged or commented on. In some implementations semantic analysis of text component of the social network tags or comments is performed. In some implementations the textual tags are then propagated to other image files associated with the user.

Abstract: An illustrative method according to a set of instructions stored on a memory of a computing device includes determining, by a processor of the computing device, a presence of a plurality of electronic files stored on a plurality of electronic devices. The plurality of electronic files are associated with a user account. The method also includes displaying, by the processor, in a single window format of a graphical user interface (GUI), representative information of the plurality of electronic files. The representative information includes descriptive information relating to the plurality of electronic files and location information indicating actual locations of the plurality of electronic files.

Abstract: An illustrative method according to a set of instructions stored on a memory of a computing device includes receiving, by a processor of the computing device, a search input. The method further includes identifying, by the processor, a plurality of electronic files related to the search input. The method further includes calculating, by the processor, a rank for each of the plurality of electronic files based on statistical data of the plurality of electronic files.

Abstract: An illustrative method according to a set of instructions stored on a memory of a computing device includes identifying, by the processor, a plurality of data units associated with a user. The plurality of data units are stored on a plurality of electronic devices. The plurality of data units are accessible through a plurality of platforms. The plurality of data units are a plurality of different data types. The method further includes determining, by the processor, for a first data unit accessible through a first platform, connection data between the first data unit and a second data unit accessible through a second platform. The method further includes generating, by the processor, a dossier for the first data unit, where the dossier includes representative information of the first data unit and the connection data.

Abstract: An illustrative method according to a set of instructions stored on a memory of a computing device includes identifying, by a processor of the computing device, a plurality of electronic files stored on a plurality of electronic devices. The plurality of electronic files includes different file types. The plurality of electronic files is also associated with a user. The method also includes determining, by the processor, metadata for the plurality of electronic files. The method also includes generating, by the processor, tags for the plurality of electronic files based on the metadata.

Abstract: An illustrative method according to a set of instructions stored on a memory of a computing device includes receiving, by a processor of the computing device, an instruction to add, modify, or delete data relating to an electronic file. The method also includes determining, by the processor, that an electronic device where the electronic file is stored is not accessible by the processor. The method also includes storing, by the processor, the instruction in response to determining that the electronic device is not accessible. The method also includes determining, by the processor, that the electronic device has become accessible by the processor. The method also includes executing, by the processor, the instruction by adding, modifying, or deleting the data relating to the electronic file in response to determining that the electronic device is currently accessible by the processor.

Abstract: An illustrative method according to a set of instructions stored on a memory of a computing device includes receiving, by a processor of the computing device, a search input. The method further includes searching, by the processor, a plurality of electronic storage locations for electronic files related to the search input. The method further includes determining, by the processor, the presence of an electronic file on a first electronic storage location of the plurality of electronic storage locations that is related to the search input. The method further includes displaying, by the processor, on a graphical user interface (GUI), representative information of the electronic file. The representative information includes descriptive information relating to the electronic file.

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: 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.