A keyword to be categorized is received. A category dictionary including categories having associated registered keywords, and a text corpus are received. Registered keywords are identified in the category dictionary having a degree of similarity to the keyword to be categorized that is equal to or greater than a predetermined value, and the categories associated with the identified registered keywords are extracted. Registered keywords are identified that are co-occurring in the text corpus with the keyword to be categorized, and the categories associated with the identified co-occurring registered keywords are extracted. A degree of importance is determined for each extracted category based on a function of the identified registered keywords in the category dictionary and/or a function of the identified co-occurring registered keywords. The extracted categories are outputted, with at least an indication of each category's relative importance, as category candidates for categorizing the keyword to be categorized.

A method is provided for creating a lexical tree from a statement in a natural language. The method is implemented by a natural-language processing module. The method includes: receiving a statement in natural language in the form of a string of characters; iteratively processing the statement as a function of at least one processing parameter and one ontological dictionary, delivering at least one relational graph corresponding to at least one lexical item included in the statement in natural language; and creating a data structure at output having all possible combinations of the lexical items of the statement in natural language on the basis of the at least one relational graph.

In an approach for changing a password. Aspects of an embodiment of the present invention include an approach for changing a password, wherein the approach includes a processor identifies a resource protected by a password. A processor discovers at least one information source containing information relevant to a process for changing the password of the resource. A processor constructs a set of procedures to change the password using the information relevant to the process for changing the password. A processor alters the password of the resource according to the constructed set of procedures.

A method, system and computer-usable medium are disclosed for computing file system management. A corpus of content is processed to extract metadata associated with folders and files referenced by a directory structure. Natural Language Processing (NLP) operations are then performed on the corpus to generate concept and entity data associated with each folder and file, followed by performing Natural Language (NL) classification operations to generate intent classification data, which in turn is processed. to determine ranked, dominant intents for each folder and file. The corpus content, extracted metadata, concept and entity data, and ranked dominant intents are then processed to generate indexed content and term data. Application context data associated with an interaction is collected and processed to determine a user intent, which is then processed with the indexed content and term data to identify a corresponding folder and file, which in turn are provided to the user.

Aspects of the present disclosure involve systems, methods, devices, and the like for emoji mashup generation. The system and method introduce a method and model that can generate emoji mashups representative of contextual information received by a user at an application. The emoji mashup may come in the form of two or more emojis coherently combined to represent the contextual idea or emotion being conveyed.

An information search system, including: a database (12); a query sentence acceptance unit (26) that accepts a query sentence; an inputted search keyword extractor (44) that extracts an inputted search keyword from the query sentence; a shared keyword dictionary (30) in which relevant keywords are registered in association with each other; a local keyword dictionary (102) in which district keywords used in particular districts are registered; a candidate search keyword reader (32) that reads out a keyword that is relevant to the inputted search keyword; and a retrieval executor (40) that executes retrieval processing from the database using the inputted search keyword, wherein, in a case in which the inputted search keyword is not registered in the local keyword dictionary, the candidate search keyword reader refers to the shared keyword dictionary, so as to read out a keyword that is relevant to the inputted search keyword.

An information search system, including: a database (12); a query sentence acceptance unit (26) that accepts a query sentence; an inputted search keyword extractor (44) that extracts an inputted search keyword from the query sentence; a shared keyword dictionary (30) in which relevant keywords are registered in association with each other; a local keyword dictionary (102) in which district keywords used in particular districts are registered; a candidate search keyword reader (32) that reads out a keyword that is relevant to the inputted search keyword; and a retrieval executor (40) that executes retrieval processing from the database using the inputted search keyword, wherein, in a case in which the inputted search keyword is not registered in the local keyword dictionary, the candidate search keyword reader refers to the shared keyword dictionary, so as to read out a keyword that is relevant to the inputted search keyword.

Embodiments of the present disclosure include a method that obtains a digital image. The method includes extracting a word block from the digital image. The method includes processing the word block by evaluating a value of the word block against a dictionary. The method includes outputting a prediction equal to a common word in the dictionary when a confidence factor is greater than a predetermined threshold. The method includes processing the word block and assigning a descriptor to the word block corresponding to a property of the word block. The method includes processing the word block using the descriptor to prioritize evaluation of the word block. The method includes concatenating a first output and a second output. The method includes predicting a value of the word block.

Embodiments of the present disclosure include a method that obtains a digital image. The method includes extracting a word block from the digital image. The method includes processing the word block by evaluating a value of the word block against a dictionary. The method includes outputting a prediction equal to a common word in the dictionary when a confidence factor is greater than a predetermined threshold. The method includes processing the word block and assigning a descriptor to the word block corresponding to a property of the word block. The method includes processing the word block using the descriptor to prioritize evaluation of the word block. The method includes concatenating a first output and a second output. The method includes predicting a value of the word block.

Disclosed is an approach for performing auto-classification of documents. A machine learning framework is provided to analyze the document, where labels associated with certain documents can be propagated to other documents.