Abstract: A mechanism is provided updating a knowledge base of a sentiment analysis system, the knowledge base being operable for storing natural language terms and a score value related to each natural language term, the score value characterizing the sentiment of the natural language term. Messages comprising natural language are received. Using content of the knowledge base, a decision is made as to whether at least one message of the received messages has a positive sentiment or a negative sentiment. A term is extracted from the message that is not present in the knowledge base. Based on a frequency of occurrence of the term in the received messages and the sentiment of the messages in which the term occurs, a score value of the term is calculated, and the term and the calculated score value are stored into the knowledge base.

Abstract: In an approach to invention purpose, for controlling evacuation of a plurality of individuals carrying corresponding portable computing devices from a venue having a plurality of exits associated with corresponding exit computing devices, wherein the method comprises, under the control of the portable computing device of each of the individuals. One or more computer processors receive one or more of evacuation messages of wireless type each being transmitted by a source entity. The one or more computer processors select a selected evacuation message of the received evacuation messages according to the hop number of the received evacuation messages. The one or more computer processors subscribe to a directed exit being set to the origin exit of the selected evacuation message.

Abstract: In an approach to invention purpose, for controlling evacuation of a plurality of individuals carrying corresponding portable computing devices from a venue having a plurality of exits associated with corresponding exit computing devices, wherein the method comprises, under the control of the portable computing device of each of the individuals. One or more computer processors receive one or more of evacuation messages of wireless type each being transmitted by a source entity. The one or more computer processors select a selected evacuation message of the received evacuation messages according to the hop number of the received evacuation messages. The one or more computer processors subscribe to a directed exit being set to the origin exit of the selected evacuation message.

Abstract: Embodiments of the present disclosure describe selective discovery, management, and deletion of personal data. The method accesses a set of data on a networked resource. The data is formed of a plurality of data elements which are arranged in at least one data table. The method identifies one or more sensitive data elements within the set of data related to one or more individuals. The method determines a sensitivity level of the one or more sensitive data elements and generates a catalogue including at least one new data element representative of the one or more sensitive data elements and based on the sensitivity level of the one or more sensitive data elements. The method tags the one or more sensitive data elements within the catalogue based on the sensitivity level of the one or more sensitive data elements corresponding to the new data element.

Abstract: In an electronic data processing method, a first column and a second column of at least one table are identified which have a one-to-one or one-to-many relationship with fewer than a threshold number of violations of the one-to-one or one-to-many relationship. On a display, possible data errors in the at least one table corresponding to the violations of the one-to-one or one-to-many relationship are indicated. The identifying of the violations may include generating a weighted bipartite graph representing the first and second columns, and detecting the violations using the bipartite graph. The method may further include displaying, on the display, a user interface whereby a user accepts or rejects each indicated violation of the one-to-one or one-to-many relationship.

Abstract: A solution is proposed for monitoring usage of bundles in the OSGi environment. For this purpose, an event notification interface of the OSGi environment is exploited. Particularly, each event relating to a change of state of a bundle (such as its addition, removal, starting and stopping) is detected by an auxiliary bundle—which previously subscribed to the event notification interface. The auxiliary bundle can then forward the detected events to a licensing agent, which identifies the bundle by means of a software catalogue. In this way, the desired result is achieved without requiring any instrumentation of the bundles to be monitored.

Abstract: A solution is proposed for ranking a plurality of documents in a computing system, each of the documents comprising a plurality of document terms. A corresponding method comprises receiving a query comprising one or more query terms for selecting the documents, calculating corresponding similarity indexes between the query and the documents, each of the similarity indexes being calculated according to a comparison between the query terms and the document terms of the corresponding document, determining corresponding semantic richness indicators of the documents, adjusting the similarity indexes according to the corresponding semantic richness indicators, and ranking at least part of the documents for selection thereof according to the corresponding similarity indexes being adjusted.

Abstract: An image captured at a first moment in time is received. A user is identified by comparing at least one facial feature extracted from the image with user information stored in a database. It is determined whether the user observed a visual display by determining whether the visual display was within the visual field of the user. Upon determining that the user observed the visual display, the image is processed with a sentiment analysis module to determine a sentiment of the user. Further, it is determined, based on a record stored in a transaction database, that the user purchased the first product at a second moment in time, and an engagement index is generated for the visual display based on processing the determined sentiment of the user and a period of elapsed time between the second moment in time and the first moment in time.

Abstract: An image captured at a first moment in time is received. A user is identified by comparing at least one facial feature extracted from the image with user information stored in a database. It is determined whether the user observed a visual display by determining whether the visual display was within the visual field of the user. Upon determining that the user observed the visual display, the image is processed with a sentiment analysis module to determine a sentiment of the user. Further, it is determined, based on a record stored in a transaction database, that the user purchased the first product at a second moment in time, and an engagement index is generated for the visual display based on processing the determined sentiment of the user and a period of elapsed time between the second moment in time and the first moment in time.

Abstract: Embodiments of a computer-implemented method, system, and computer program product for analysis of news for veracity are presented. A computer can receive a document and classify the document. Using the results of the classifying, the computer can identify a plurality of techniques for testing veracity of documents. The computer can determine one or more of the plurality of techniques to use for testing the document. The computer can perform testing of the document using the determined one or more of the plurality of techniques. The computer can output results of the testing to a user.

Abstract: A solution is proposed for managing a plurality of computing machines. A corresponding method comprises causing each computing machine of at least part of the computing machines to execute a management activity on the computing machine; receiving a corresponding result of the execution of the management activity on each computing machine; determining a success fingerprint according to one or more characteristics of each of at least part of one or more wherein the corresponding result is indicative of a success of the execution of the management activity thereon; calculating a similarity index for each of one or more failure ones of the computing machines wherein the corresponding result is indicative of a failure of the execution of the management activity thereon; and prioritizing the computing machines which failed to accept a policy according to the corresponding similarity indexes.

Abstract: Embodiments of the present disclosure describe selective discovery, management, and deletion of personal data. The method accesses a set of data on a networked resource. The data is formed of a plurality of data elements which are arranged in at least one data table. The method identifies one or more sensitive data elements within the set of data related to one or more individuals. The method determines a sensitivity level of the one or more sensitive data elements and generates a catalogue including at least one new data element representative of the one or more sensitive data elements and based on the sensitivity level of the one or more sensitive data elements. The method tags the one or more sensitive data elements within the catalogue based on the sensitivity level of the one or more sensitive data elements corresponding to the new data element.

Abstract: The invention relates to a computer-implemented method for predicting a work progress figure for a user using an assignment test. Receiving an input activity record; receiving an input sequence of activity records; generating a test sequence comprising the input activity record appended to the input sequence; providing the test sequence to an input of a machine learning model; in response to the provision of the test sequence, receiving a metric from an output of the machine learning model, the metric comprising a work progress figure assigned to the test sequence; and providing the metric, the method further comprising: receiving an unassigned activity record specific to the user; receiving a task specific to the user, the task comprising a sequence of assigned activity records; and executing the assignment test with the input activity record being the unassigned activity record and the input sequence being the sequence.

Abstract: A computer-implemented method for training a natural language classifier associated with a chat interface of a computer system is provided. The method may include receiving a training dataset comprising an initial set of expressions corresponding to an intent. Additional expressions corresponding to the intent may be generated, wherein the additional expressions are generated based on the initial set of expressions corresponding to the intent. The natural language classifier may be trained based on the initial set of expressions and the additional expressions corresponding to the intent. The trained natural language classifier may be implemented to determine an intent expressed by a detected query based on the initial set of expressions and the additional expressions by which the natural language classifier was trained.

Abstract: A mechanism is provided updating a knowledge base of a sentiment analysis system, the knowledge base being operable for storing natural language terms and a score value related to each natural language term, the score value characterizing the sentiment of the natural language term. Messages comprising natural language are received. Using content of the knowledge base, a decision is made as to whether at least one message of the received messages has a positive sentiment or a negative sentiment. A term is extracted from the message that is not present in the knowledge base. Based on a frequency of occurrence of the term in the received messages and the sentiment of the messages in which the term occurs, a score value of the term is calculated, and the term and the calculated score value are stored into the knowledge base.

Abstract: A mechanism is provided for updating a knowledge base of a spam detection system for email messages. A first and a second email set of email messages related to a time window are created. The first email set comprises email messages currently classified as spam messages, the second email set email messages currently classified as non-spam messages. A natural language term that is not present in the knowledge base is extracted from one of the email messages contained in one of the two email sets. Based on a frequency of occurrence of the extracted term in email messages contained in one or more of the two email sets and based on whether the respective email messages are spam messages or non-spam messages, a score value of the extracted term is calculated. The extracted term and the calculated score value are stored into the knowledge base.

Abstract: A mechanism is provided updating a knowledge base of a sentiment analysis system, the knowledge base being operable for storing natural language terms and a score value related to each natural language term, the score value characterizing the sentiment of the natural language term. Messages comprising natural language are received. Using content of the knowledge base, a decision is made as to whether at least one message of the received messages has a positive sentiment or a negative sentiment. A term is extracted from the message that is not present in the knowledge base. Based on a frequency of occurrence of the term in the received messages and the sentiment of the messages in which the term occurs, a score value of the term is calculated, and the term and the calculated score value are stored into the knowledge base.

Abstract: A computer-implemented method for training a natural language classifier associated with a chat interface of a computer system is provided. The method may include receiving a training dataset comprising an initial set of expressions corresponding to an intent. Additional expressions corresponding to the intent may be generated, wherein the additional expressions are generated based on the initial set of expressions corresponding to the intent. The natural language classifier may be trained based on the initial set of expressions and the additional expressions corresponding to the intent. The trained natural language classifier may be implemented to determine an intent expressed by a detected query based on the initial set of expressions and the additional expressions by which the natural language classifier was trained.

Abstract: An image captured at a first moment in time is received. A user is identified by comparing at least one facial feature extracted from the image with user information stored in a database. It is determined whether the user observed a visual display by determining whether the visual display was within the visual field of the user. Upon determining that the user observed the visual display, the image is processed with a sentiment analysis module to determine a sentiment of the user. Further, it is determined, based on a record stored in a transaction database, that the user purchased the first product at a second moment in time, and an engagement index is generated for the visual display based on processing the determined sentiment of the user and a period of elapsed time between the second moment in time and the first moment in time.

Abstract: An image captured at a first moment in time is received. A user is identified by comparing at least one facial feature extracted from the image with user information stored in a database. It is determined whether the user observed a visual display by determining whether the visual display was within the visual field of the user. Upon determining that the user observed the visual display, the image is processed with a sentiment analysis module to determine a sentiment of the user. Further, it is determined, based on a record stored in a transaction database, that the user purchased the first product at a second moment in time, and an engagement index is generated for the visual display based on processing the determined sentiment of the user and a period of elapsed time between the second moment in time and the first moment in time.