A computer-implemented method, system and computer program product for improving understandability of text by a user. A final word vector for each word in a sentence of a document is computed, such as by averaging a first word vector and a second word vector for that word. Furthermore, elements of a user portrait are vectorized. A distance is then computed between a vector for each word in the sentence and a vectorized element in the user’s portrait which is summed to form an evaluation result for the element. An evaluation result is also formed for every other element in the user’s portrait by performing such a computation step. A “final evaluation result” is then generated corresponding to the evaluation results for every element in the user’s portrait. The document is then transformed in response to the final evaluation result indicating a lack of understanding of the sentence by the user.

Unstructured text is identified as larger than a threshold size. Named-entity recognition analysis is executed on the unstructured text. One or more anchor entities of the unstructured text are determined that each occur more than a threshold amount of times within the unstructured text. Two or more instances of the one or more anchor entities that are separated by at least a threshold amount of text of the unstructured text are identified. The unstructured text is partitioned into at least three sections. The unstructured text is partitioned at respective natural language demarcation points associated with each of the two or more instances such that each of the at least three sections is smaller than the threshold size. Separate coreference analyses are performed in parallel on each of the at least three sections.

Intent-resolution using a phrase index may include obtaining data expressing a usage intent, the data expressing the usage intent including an unresolved data portion, identifying a phrase fragment based on the data expressing the usage intent and a defined phrase pattern, the phrase fragment including the unresolved data portion, identifying, by a processor, an indexed phrase as a candidate phrase by searching a phrase index based on the phrase fragment, wherein the candidate phrase at least partially matches the phrase fragment in accordance with the defined phrase pattern, and outputting the candidate phrase for presentation to a user as a candidate for resolving the unresolved portion.

System and method for relation extraction using adaptive thresholding and localized context pooling (ATLOP). The system includes a computing device, the computing device has a processer and a storage device storing computer executable code. The computer executable code is configured to provide a document; embed entities in the document into embedding vectors; and predict relations between a pair of entities in the document using their embedding vectors. The relation prediction is performed based on an improved language model. Each relation has an adaptive threshold, and the relation between the pair of entities is determined to exist when a logit of the relation between the pair of entities is greater than a logit function of the corresponding adaptive threshold.

The present disclosure is related in general to software testing and a method and a system for automatically identifying violation in the test cases. A test case validation system categorizes the test cases into event-based test cases and binary test cases. Further, a Part-Of-Speech (POS) pattern is detected in the one or more test cases based on POS tags assigned to each of the tokens in test cases. Thereafter, comparison of the detected POS pattern and the one or more tokens with predefined POS patterns and predefined tokens identifies violations in the one or more test cases if any, using pattern matching and Natural Language Processing (NLP). The predefined POS patterns and tokens used for comparison are filtered based on category of the test case thus accelerating the process of the violation identification. The test case validation system is capable of accurately identifying more than one type of violations simultaneously.

A computer-implemented method for decomposing a decision table includes decomposing, by a computer processor, a decision table into a first sub-table and a second sub-table. The decision table includes two or more columns, and the decomposition is based on a semantic model describing relations among the two or more columns of the decision table. The first sub-table and the second sub-table together represent the decision table.

In an example embodiment, input is received from a first user of a computer system. A text object relating to a first item from the input is created, and translated from a first language to a second language. A plurality of text objects, in the second language, having text similar to the translated text object, are located in a database, each text object comprising textual information pertaining to the first item. The plurality of text objects having text similar to the translated text are then ranked based on a comparison of the contextual information about the first item and the contextual information stored in the database for the plurality of text objects having text similar to the translated text object. At least one of the ranked text objects is translated to the first language.

A method and system are described that provide responses to natural language queries regarding the performance of a business. The method and system processes data from multiple data sources including information generated by the business and analyzes the data to provide actionable suggestions as to how to determine how to improve the performance of the business. The use of natural language queries allows for a merchant without a business intelligence background obtain these insights easily.

A third-party service may be used to assist entities in responding to requests of users. A third-party service may receive, directly or indirectly, a request of a first user for assistance from a first entity. The third-party service may request information about the first user by sending a request to a computer of the first entity. The third-party service may use the request of the first user and the information about the first user to automatically generate a response to the request of the first user. The third-party service may then transmit, directly or indirectly, the response to the first user.

A mechanism is provided in a data processing system having a processor and a memory storing a store of semantic types and instructions for implementing a natural language processing engine for generating semantically equivalent variants of a natural language term. The mechanism receives an input term for variant analysis. The natural language processing engine executing on the data processing system identifies a semantic type of the input term based on a store of semantic types. The natural language processing engine performs a type-specific series of rule-based expansions of the input term based on the identified semantic type of the input term to form a set of semantically equivalent variants of the input term. The natural language processing engine performs a natural language processing operation using the input term and the set of semantically equivalent variants of the input term.