Abstract: The disclosure provides a method for data instance processing. The method includes obtaining a set of data instances collected from a plurality of organizations. Each of the data instances includes at least one record formed in an organization that stores values of a plurality of attributes of the data instance. The method also includes dividing the set of data instances into groups, wherein data instances with conflicting values for the same attribute are divided into different groups. The method further includes subdividing data instances in each of the groups into clusters.

Abstract: Methods, systems, and computer program products are provided for language entity identification. In one embodiment, a computer-implemented method is disclosed. In the method, respective pinyin codes may be determined for respective Chinese characters comprised in a string that is to be processed. Then, respective pinyin features may be generated from the respective pinyin codes. Next, a candidate language entity may be identified from the string based on the respective pinyin features and a mapping describing an association between pinyin features and language entity. In other embodiments, a computer-implemented system and a computer program product for security management are disclosed.

Abstract: A method is provided for data matching between a set of source data structures and a set of target data structures. The method includes obtaining, using a processor device configured to perform machine learning, source to target matching results with matching scores, based on the sets of source and target data structures. The method further includes calculating, by the processor device, context information for data structure pairs based on a structure similarity and an ontology similarity between constituent data structures thereof. Each of data structure pairs include as the constituent data structures a respective source data structure and a respective target data structure from the sets of source and target data structures. The method also includes updating, by the processor device, the matching scores based on the context information. The method additionally includes controlling, by the processor device, a hardware device responsive to at least one updated matching score.

Abstract: Techniques are described that facilitate automatically providing entities with rephrased versions of standard answers. In one embodiment, a computer-implemented is provided that comprises determining, by a device operatively coupled to a processor, a talking style of a plurality of talking styles that an entity is associated with based on reception of natural language input from the entity proposing a question related to a defined topic. The method further comprises selecting, by the device based on the talking style, an answer rephrasing model from a plurality of answer rephrasing models respectively configured to generate different rephrased versions of a standard answer to the question, and employing, by the device, the answer rephrasing model to generate a rephrased version of the standard that corresponds to the talking style.

Abstract: Techniques are described that facilitate automatically providing entities with rephrased versions of standard answers. In one embodiment, a computer-implemented is provided that comprises determining, by a device operatively coupled to a processor, a talking style of a plurality of talking styles that an entity is associated with based on reception of natural language input from the entity proposing a question related to a defined topic. The method further comprises selecting, by the device based on the talking style, an answer rephrasing model from a plurality of answer rephrasing models respectively configured to generate different rephrased versions of a standard answer to the question, and employing, by the device, the answer rephrasing model to generate a rephrased version of the standard that corresponds to the talking style.

Abstract: Embodiments of the invention provide a computer-implemented method, computing system and computer program product for analyzing a message in a social network. The method comprises identifying an entity from the message; detecting historical popularity of the entity in a social network; identifying a topic from the message; detecting historical popularity of the topic in the social network; and generating an entity-topic correlation factor for the entity and the topic based on the historical popularity of the entity and the historical popularity of the topic. Results obtained with embodiments of the invention may be provided to popularity prediction tools for improving popularity prediction of messages in social networks.

Abstract: Techniques are provided that facilitate determining, by a system operatively coupled to a processor, respective performance scores for a first set of candidate transformation scripts based on a performance criterion, wherein the candidate transformation scripts are related to extract, transform, load (ETL) processing of a new data source to a data target. Techniques are also provided that facilitate generating, by the system, a recommendation of one or more of the first set of candidate transformation scripts based on the respective performance scores for performance of the ETL processing.

Abstract: Systems, computer-implemented methods and/or computer program products that facilitate automatically mapping different data types are provided. In one embodiment, a computer-implemented method comprises: constructing, by a system operatively coupled to a processor, an index from one or more classifier models for one or more data types; scoring and ranking, by the system, one or more candidate pairs for the one or more data types based on confidence score; and analyzing, by the system, how the one or more candidate pairs are scored and automatically generating the one or more classifier models used to construct the index.

Abstract: Techniques are described that facilitate automatically providing entities with rephrased versions of standard answers. In one embodiment, a computer-implemented is provided that comprises determining, by a device operatively coupled to a processor, a talking style of a plurality of talking styles that an entity is associated with based on reception of natural language input from the entity proposing a question related to a defined topic. The method further comprises selecting, by the device based on the talking style, an answer rephrasing model from a plurality of answer rephrasing models respectively configured to generate different rephrased versions of a standard answer to the question, and employing, by the device, the answer rephrasing model to generate a rephrased version of the standard that corresponds to the talking style.

Abstract: A computer-implemented method and a system are proposed. According to the method, in response to receiving a character, a first representation of the character is generated by performing word embedding processing on the character. The first representation is related to context of the character. A second representation of the character is generated by performing convolutional neural network (CNN) processing on the character. The second representation is related to a hieroglyphic feature of the character. A label for the character is determined by performing recurrent neural network (RNN) processing on the first representation and the second representation. The label indicates an attribute of the character related to the context.

Abstract: A computer-implemented method and a system are proposed. According to the method, in response to receiving a character, a first representation of the character is generated by performing word embedding processing on the character. The first representation is related to context of the character. A second representation of the character is generated by performing convolutional neural network (CNN) processing on the character. The second representation is related to a hieroglyphic feature of the character. A label for the character is determined by performing recurrent neural network (RNN) processing on the first representation and the second representation. The label indicates an attribute of the character related to the context.

Abstract: A computer-implemented method and a system are proposed. According to the method, in response to receiving a character, a first representation of the character is generated by performing word embedding processing on the character. The first representation is related to context of the character. A second representation of the character is generated by performing convolutional neural network (CNN) processing on the character. The second representation is related to a hieroglyphic feature of the character. A label for the character is determined by performing recurrent neural network (RNN) processing on the first representation and the second representation. The label indicates an attribute of the character related to the context.

Abstract: A computer-implemented method and a system are proposed. According to the method, in response to receiving a character, a first representation of the character is generated by performing word embedding processing on the character. The first representation is related to context of the character. A second representation of the character is generated by performing convolutional neural network (CNN) processing on the character. The second representation is related to a hieroglyphic feature of the character. A label for the character is determined by performing recurrent neural network (RNN) processing on the first representation and the second representation. The label indicates an attribute of the character related to the context.

Abstract: A computer implemented method identifies guidelines through use of a neural network by a remote guideline server. A client computer transmits instructions to the remote guideline server to retrieve and evaluate multiple candidate guidelines. The remote guideline server utilizes a neural network to identify a string of terms found in each of the multiple candidate guidelines that match one or more strings of terms from a model guideline; to identify a semantic concept of each of the multiple candidate guidelines that matches one or more semantic concepts from the model guideline; and to identify a structural pattern of each of the multiple candidate guidelines that matches one or more structural patterns of the model guideline. The candidate guidelines that match the model guideline are then sent from the remote guideline server to the client computer.

Abstract: Embodiments of the invention provide a computer-implemented method, computing system and computer program product for analyzing a message in a social network. The method comprises identifying an entity from the message; detecting historical popularity of the entity in a social network; identifying a topic from the message; detecting historical popularity of the topic in the social network; and generating an entity-topic correlation factor for the entity and the topic based on the historical popularity of the entity and the historical popularity of the topic. Results obtained with embodiments of the invention may be provided to popularity prediction tools for improving popularity prediction of messages in social networks.

Abstract: The methods, systems, and computer program products described herein provide ways to generate an informative training corpus of samples for use in machine training a high-quality sentiment analysis computer model. In some aspects, a method is disclosed including receiving a plurality of training samples, extracting semantic and sentiment elements of one or more of the training samples, generalizing the semantic and sentiment elements of the one or more of the training samples, generating an informative ranking score for one or more of the training samples based on the generalized semantic and sentiment elements, selecting informative training samples from the plurality of training samples based at least in part on the generated informative ranking scores, and adding the selected informative training samples to an informative training corpus.

Abstract: Technical solutions are described for displaying product labels for a product to a user, where the product is associated with a first category. An example method includes analyzing product reviews posted by the user for a set of other products, which includes a second product from a second category, distinct from the first category. The method also includes identifying a set of product labels personalized for the user based on the analysis of the product reviews for other products, including the second product from the second category. The method also includes obtaining a plurality of product labels associated with the product that is being displayed to the user, based on product labels common to the set of product labels for the user and the plurality of product labels of the product. The method also includes displaying the subset of product labels as part of the information of the product.

Abstract: Technical solutions are described for displaying product labels for a product to a user, where the product is associated with a first category. An example method includes analyzing product reviews posted by the user for a set of other products, which includes a second product from a second category, distinct from the first category. The method also includes identifying a set of product labels personalized for the user based on the analysis of the product reviews for other products, including the second product from the second category. The method also includes obtaining a plurality of product labels associated with the product that is being displayed to the user, based on product labels common to the set of product labels for the user and the plurality of product labels of the product. The method also includes displaying the subset of product labels as part of the information of the product.

Abstract: A method for achieving interactive browsing includes steps performed by a computer coupled to a knowledge base and a document database. The knowledge base stores a plurality of terms and information relating to each term, and the document database stores a plurality of documents. The steps include acquiring terms in which a user has interest; extracting information relating to the terms in which the user has interest from the knowledge base in order to display the information in a first display part of a user interface; and extracting documents containing the terms in which the user has interest from the document database in order to display a list of extracted documents in a second display part of the user interface.

Abstract: A method for achieving interactive browsing includes steps performed by a computer coupled to a knowledge base and a document database. The knowledge base stores a plurality of terms and information relating to each term, and the document database stores a plurality of documents. The steps include acquiring terms in which a user has interest; extracting information relating to the terms in which the user has interest from the knowledge base in order to display the information in a first display part of a user interface; and extracting documents containing the terms in which the user has interest from the document database in order to display a list of extracted documents in a second display part of the user interface.