Abstract: Mechanisms are provided to implement an answer change notification system. The mechanisms receive a change operation to change a portion of a user profile data structure associated with a user and identify a first entry in a question and answer (QA) log data structure, corresponding to the user, having an indicator identifying a previous answer of the first entry as being dependent upon information in the user profile data structure. The mechanisms resubmit a question of the first entry to a question and answer (QA) system to generate a new answer to the question in response to identifying the entry. The mechanisms receive the new answer from the QA system and output, to a client device associated with the user, a notification identifying the new answer to the question in response to receiving the new answer.

Abstract: Systems, methods, and computer program products to perform an operation comprising receiving a policy document specifying a plurality of criteria, identifying, in a segment of unstructured text in the policy document, a criteria delimiter, creating a first portion and a second portion of the segment of unstructured text, wherein the first and second portions are created based on the criteria delimiter, wherein the first and second portions comprise a first criterion and a second criterion, respectively, and responsive to identifying an anaphora in the second portion of the segment of unstructured text that is related to a term in the first portion of the segment of unstructured text, combining the first criterion and the second criterion into a composite criterion.

Abstract: An approach is provided to train a question answering (QA) system using answer keys based on forum content. In the approach, a question is selected from a post in a threaded discussion. An answer to the selected question is automatically identified from crowd-based sources, with the identified answer having a confidence level greater than a threshold. An answer key is built using the selected question and the identified answer. The QA system is automatically trained using the answer key.

Abstract: An approach is provided to resolve anaphors between posts, or threads, in a threaded discussion, for example an online forum. The approach analyzes a number of posts that are included in threads of an online forum. During the analysis, the approach identifies terms in parent posts, detects anaphors in child posts that reference the terms in the parent posts, and resolves the anaphor found in the child post with the term. The parent post with the identified term and the child post with the resolved anaphor are then stored in the memory for use by information handling systems, such as question answering (QA) systems.

Abstract: Mechanisms are provided, in a question and answer (QA) system, for monitoring changes in answers to previously submitted questions. A question is received for which an answer is to be generated. One answer for the question is generated and the question, answer, and a notification party are registered in a question registration data structure. Another answer to the question is generated, at a later time than when the previous answer was generated. A degree of a change in the two answers to the question is determined. An answer change notification is transmitted to the notification party based on the degree of the change in the two answers to the question. The notification party may be the source of the question or a registered party to which notifications are to be sent.

Abstract: Aspects include monitoring accesses to computer source code. A method includes detecting an access, by a user, to a source code repository. It is determined whether the access is consistent with a history of accesses by the user to the source code repository. Based on determining that the access is not consistent with the history of accesses by the user, the access is analyzed for a reason for the user to perform the access. The analyzing is based on information about the user and information about the access. A notification of the access is generated based on the analyzing resulting in an absence of a reason for the user to perform the access.

Abstract: Test cases for a text annotator are generated by determining types of inputs to the annotator and analyzing language structures in a corpus to identify sentence types and grammar constructs. An input type can correspond to multiple grammar constructs. Test cases are generated by performing grammar tree transformations on selected fragments from the corpus based on the sentence types and the grammar constructs. Additional test cases are generated by replacing starting phrases in selected fragments with substitute phrases from dictionaries associated with the input types (a dictionary can include a false synonym for an input type for purposes of negative testing). The two generating approaches can be combined, i.e., performing one or more successive (different) grammar tree transformations to yield a sentence which is then subjected to phrase substitution.

Abstract: Mechanisms are provided for processing natural language content having a computer code segment. Natural language content is processed using a natural language processing (NLP) engine and a segment of content within the natural language content is identified that is not recognized by the NLP engine. The segment is analyzed to determine whether the segment contains computer code and, if so, a code segment annotation for the computer code is generated that provides a natural language description of functionality of the computer code in the segment. The code segment annotation is stored in association with the natural language content and natural language processing is performed using the NLP engine on the code segment annotation to further process the natural language content.

Abstract: An approach is provided in which a cognitive digital security assistant intercepts a personal data request from a client that is requesting personal data from a user. The cognitive digital security assistant analyzes the personal data request against the user's security statements to determine whether to provide the user's personal data to the client. During the analysis, the cognitive digital security assistant determines whether the personal data request includes benefits that meet the user's benefit thresholds included in the user's security statements. When the benefits meet the user's benefit thresholds, the cognitive digital security assistant provides the requested personal data to the client in exchange for the benefit from the client.

Abstract: A method includes receiving a text. The method also includes identifying a set of linguistic characteristics contained in the text. The method also includes determining a plurality of time periods in which the text was potentially written based on the set of linguistic characteristics. The method also includes retrieving a set of reference documents for each time period. The method also includes producing a set of proximity scores by performing a set of proximity checks using the set of linguistic characteristics, the set of reference documents, and the text, where the proximity checks analyze how often and how close linguistic characteristics are to one another. The method also includes ranking the plurality of time periods based on the set of proximity scores and returning a set of one or more ranked time periods of the plurality of time periods.

Abstract: An approach is provided to discover new portmanteau, such as when ingesting documents into a question answering (QA) system. The approach works by analyzing a words included in electronic documents and identifies words as being possible portmanteaus. To analyze a portmanteau found in a document, the approach identifies morphemes that are included in the identified portmanteau and candidate words that correspond to each of the identified morphemes. A meaning for the new portmanteau is then derived from the meanings of the candidate word meanings.

Abstract: A method and system for determining a location of origin and a time period in which a document was written is disclosed. A text is received and a set of linguistic characteristics for the text are identified. A set of possible locations and time periods for the text are determined based on the set of linguistic characteristics. A set of reference documents are used to determine a proximity rating for the text based upon a determination of how close the text is to the reference documents. The potential locations and time periods are ranked and returned for presentation.

Abstract: An approach is provided to discover new portmanteau, such as when ingesting documents into a question answering (QA) system. The approach works by analyzing a words included in electronic documents and identifies words as being possible portmanteaus. To analyze a portmanteau found in a document, the approach identifies morphemes that are included in the identified portmanteau and candidate words that correspond to each of the identified morphemes. A meaning for the new portmanteau is then derived from the meanings of the candidate word meanings.

Abstract: A method includes receiving a text and identifying a set of linguistic characteristics contained in the text, where linguistic characteristics include grammatical, syntactic, and idiomatic features of the text. The method also includes determining a plurality of locations of origin in which the text was potentially written based on the set of linguistic characteristics. The method also includes retrieving a set of reference documents for each location of origin in the plurality of locations of origin and producing a set of proximity scores by performing a set of proximity checks using the set of linguistic characteristics, the set of reference documents, and the text, wherein the proximity checks analyze how often and how close linguistic characteristics are to one another. The method also includes ranking the plurality of locations of origin based on the set of proximity scores and returning a set of one or more ranked locations of origin.

Abstract: A technique for pre-filling a computing device form with information associated with an action command found in a message includes receiving a message. Content of the message is analyzed utilizing natural language processing (NLP) to locate an action command within the message. NLP is applied to text in the message that is associated with the action command to determine a context of the action command. A similarity algorithm is applied to the text and one or more input fields of the form to identify one or more matching elements between the text and the input fields of the form. Finally, the input fields of the form are automatically pre-filled with information associated with the matching elements in the message whose similarity exceeds a predetermined threshold.

Abstract: A technique for pre-filling a computing device form with information associated with an action command found in a message includes receiving a message. Content of the message is analyzed utilizing natural language processing (NLP) to locate an action command within the message. NLP is applied to text in the message that is associated with the action command to determine a context of the action command. A similarity algorithm is applied to the text and one or more input fields of the form to identify one or more matching elements between the text and the input fields of the form. Finally, the input fields of the form are automatically pre-filled with information associated with the matching elements in the message whose similarity exceeds a predetermined threshold.

Abstract: Mechanisms are provided for processing natural language content having a computer code segment. Natural language content is processed using a natural language processing (NLP) engine and a segment of content within the natural language content is identified that is not recognized by the NLP engine. The segment is analyzed to determine whether the segment contains computer code and, if so, a code segment annotation for the computer code is generated that provides a natural language description of functionality of the computer code in the segment. The code segment annotation is stored in association with the natural language content and natural language processing is performed using the NLP engine on the code segment annotation to further process the natural language content.

Abstract: A mechanism is provided in a data processing system for predicting and enhancing ingestion time for a set of input documents. The mechanism receives a set of documents to be added to a corpus of the data processing system. The mechanism records document features of each document within the set of documents using an annotation engine within the data processing system. The mechanism predicts an ingestion time for each document within the set of documents based on the document characteristics and a machine learning model. The mechanism assigns the set of documents to data processing system resources to be processed based on the predicted ingestion time for each document.

Abstract: Mechanisms are provided for evaluating test cases for testing a software product based on a requirements change. The mechanisms analyze a test case corpus to identify a plurality of first relationships between elements of test cases in the test case corpus and generate a test case relationship model based on the identified plurality of first relationships. The mechanisms receive a proposed requirements change to change one or more requirements of the software product and then perform a search of the test case relationship model to identify test case relationships corresponding to the proposed requirements change. The mechanisms identify a subset of test cases affected by the proposed requirements change and generate an output specifying the identified subset of test cases.

Abstract: Mechanisms are provided for evaluating test cases for testing a software product based on a requirements change. The mechanisms analyze a test case corpus to identify a plurality of first relationships between elements of test cases in the test case corpus and generate a test case relationship model based on the identified plurality of first relationships. The mechanisms receive a proposed requirements change to change one or more requirements of the software product and then perform a search of the test case relationship model to identify test case relationships corresponding to the proposed requirements change. The mechanisms identify a subset of test cases affected by the proposed requirements change and generate an output specifying the identified subset of test cases.