Abbyy Infopoisk LLC

Abbyy Production LLC

Abbyy Infopiosk LLC

Tatiana Danielyan

Maria Iontseva

Konstantin Zuev

Vladimir Pavlovich Selegey

Konstantin Anisimovich

Anatoly Starostin

Stepan Evgenyevich Matskevich

Tatiana Parfentieva

Elmira Rakhmatulina

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.

Method and device to estimate similarity between documents having multiple segments

Display screen or portion thereof with a transitional graphical user interface

Display screen with graphical user interface

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.

Indicating and correcting errors in machine translation systems

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.

Method and system for semantic searching

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.

Exhaustive automatic processing of textual information

Systems and methods for creating ontologies by analyzing natural language texts. An example method comprises: receiving a plurality of semantic structures associated with a text corpus; identifying a first semantic structure and a second semantic structure, wherein the first semantic structure comprises a first substructure and a second substructure, wherein the second semantic structure comprises a third substructure and a fourth substructure, and wherein the first substructure is similar to the third substructure in view of a first similarity criterion; and responsive to determining that the second substructure is similar to the fourth substructure in view of a second similarity criterion, associating, with a certain concept of an ontology associated with the text corpus, objects represented by the second substructure and the fourth substructure.

Creating ontologies by analyzing natural language texts

Systems and methods for task distribution are provided. A total number of available computing system's processing units is defined, where the total number of available processing units includes a set of regular processing units available for executing tasks and a set of processing units that constitute the reserve pool. Tasks are assigned to processing units. The number of processing units assigned to the next task in the queue is no more than the total number of processing units available at the time, multiplied by the availability ratio. Iterative assignment of processing units to tasks according to the method described is performed as long as there are idle processing units available for task execution, when no more processing units are available, the processing units from the reserve pool are assigned. As a result, the method allows processing units to be available for allocation to a new incoming task at any time.

Task distribution method and system

Display screen or portion thereof with a graphical user interface

Methods are described for performing classification (categorization) of text documents written in various languages. Language-independent semantic structures are constructed before classifying documents. These structures reflect lexical, morphological, syntactic, and semantic properties of documents. The methods suggested are able to perform cross-language text classification which is based on document properties reflecting their meaning. The methods are applicable to genre classification, topic detection, news analysis, authorship analysis, etc.

Cross-language text classification

Methods are described for performing clustering or classification of texts of different languages. Language-independent semantic structures (LISS) are constructed before clustering is performed. These structures reflect lexical, morphological, syntactic, and semantic properties of texts. The methods suggested are able to perform cross-language text clustering which is based on the meaning derived from texts. The methods are applicable to genre classification, topic detection, news analysis, authorship analysis, internet searches, and creating corpora for other tasks, etc.

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Moscow, Russia

Tatiana Danielyan