Abstract: A method for adjusting device system settings in response to analysis of displayed content. In some embodiments, a processor may extract content from contents displayed on a screen of a device. The processor may analyze features of the content. The processor may classify the content as belonging to a content class, based on analysis of the content features, utilizing a machine learning model. The processor may update the device system settings based on the content class.

Abstract: An embodiment for expanding a search query is provided. The embodiment may include receiving a stopping criterion for stopping a search. The embodiment may also include receiving an initial search query. The embodiment may further include submitting the initial search query to an information retrieval system. The embodiment may also include identifying enrichment terms from the retrieved initial set of documents. The embodiment may further include generating a subsequent search query that includes one or more enrichment terms from the retrieved initial set of documents. The embodiment may also include submitting the subsequent search query to the information retrieval system. The embodiment may further include determining whether the stopping criterion is met, and in response to determining the stopping criterion is not met, iterating identifying, generating, submitting steps until the stopping criterion is met.

Abstract: A method, system, and computer-usable medium are disclosed for answering general background questions on a topic from documents with glossary sections, A set of documents with glossaries is received from which a set of terms and associated glossary entries are extracted, where each term has a corresponding glossary entry. Association is performed of related glossary entries. The associations is based on a similarity algorithm to form glossary clusters where each glossary cluster refers to one or more glossary entries. A query with query terms tailored to general information is received. The glossary clusters are ranked relevance to the query terms to form a ranked set. A set of glossary clusters meeting a high ranked threshold is selected and provided.

Abstract: Embodiments are provided that relate to a computer system, a computer program product, and a machine-implemented method for assessing a statement by an entity to a recipient group, particularly in a social media environment, for an inconsistency with a previous (historical) statement to the same recipient group, and notifying the entity of the inconsistency. In certain embodiments, an alternative statement is provided.

Abstract: An embodiment for expanding a search query is provided. The embodiment may include receiving a stopping criterion for stopping a search. The embodiment may also include receiving an initial search query. The embodiment may further include submitting the initial search query to an information retrieval system. The embodiment may also include identifying enrichment terms from the retrieved initial set of documents. The embodiment may further include generating a subsequent search query that includes one or more enrichment terms from the retrieved initial set of documents. The embodiment may also include submitting the subsequent search query to the information retrieval system. The embodiment may further include determining whether the stopping criterion is met, and in response to determining the stopping criterion is not met, iterating identifying, generating, submitting steps until the stopping criterion is met.

Abstract: A method for adjusting device system settings in response to analysis of displayed content. In some embodiments, a processor may extract content from contents displayed on a screen of a device. The processor may analyze features of the content. The processor may classify the content as belonging to a content class, based on analysis of the content features, utilizing a machine learning model. The processor may update the device system settings based on the content class.

Abstract: A method, system, and computer-usable medium are disclosed for answering general background questions on a topic from documents with glossary sections, A set of documents with glossaries is received from which a set of terms and associated glossary entries are extracted, where each term has a corresponding glossary entry. Association is performed of related glossary entries. The associations is based on a similarity algorithm to form glossary clusters where each glossary cluster refers to one or more glossary entries. A query with query terms tailored to general information is received. The glossary clusters are ranked relevance to the query terms to form a ranked set. A set of glossary clusters meeting a high ranked threshold is selected and provided.

Abstract: Embodiments are provided that relate to a computer system, a computer program product, and a machine-implemented method for assessing a statement by an entity to a recipient group, particularly in a social media environment, for an inconsistency with a previous (historical) statement to the same recipient group, and notifying the entity of the inconsistency. In certain embodiments, an alternative statement is provided.

Abstract: Embodiments relate to an intelligent computer platform to create a document specific error correction model for amending OCR values. An image of a document is received and OCR is applied to the received image. Text is extracted from at least one static content field and the extracted text is compared to stored text from known static content. Responsive to a deviation identified in the comparison, a document specific error correction model is created and leveraged to correct OCR output. The model generates one or more variants for the dynamic content field associated with the static content field having the identified deviation. The generated variant(s) is subject to processing and one of the variants is selected as amended document content. A new document version is created from the amendment, the new document version including corrected OCR output.

Abstract: An approach is provided in which an information handling system analyzes a message tone vector corresponding to a message against a target tone vector corresponding to a recipient of the message. The message tone vector includes a set of message tone attributes and the target tone vector includes a set of target tone thresholds. The information handling system, in response to determining a difference between the message tone vector and the target tone vector, creates a variant message by substituting words in the message with one or more similar words based on the target tone vector. In turn, the information handling system sends the variant message to the recipient.

Abstract: Embodiments relate to an intelligent computer platform to create a document specific error correction model for amending OCR values. An image of a document is received and OCR is applied to the received image. Text is extracted from at least one static content field and the extracted text is compared to stored text from known static content. Responsive to a deviation identified in the comparison, a document specific error correction model is created and leveraged to correct OCR output. The model generates one or more variants for the dynamic content field associated with the static content field having the identified deviation. The generated variant(s) is subject to processing and one of the variants is selected as amended document content. A new document version is created from the amendment, the new document version including corrected OCR output.

Abstract: An approach is provided in which an information handling system analyzes a message tone vector corresponding to a message against a target tone vector corresponding to a recipient of the message. The message tone vector includes a set of message tone attributes and the target tone vector includes a set of target tone thresholds. The information handling system, in response to determining a difference between the message tone vector and the target tone vector, creates a variant message by substituting words in the message with one or more similar words based on the target tone vector. In turn, the information handling system sends the variant message to the recipient.