Abstract: A method, system and computer program product for assisting users to generate the desired meme in a document. A document is scanned to identify parts of speech, numerical text or numbers and images (collectively the “terms”) that provide positive/negative memes. A score for each of these terms is assigned. A score may then be assigned to each designated primary object (e.g., individual, company) discussed in the document using the scores assigned to the identified terms. Options may then be provided to modify the document to provide the type of meme (e.g., positive or negative meme) desired by the author to be associated with the particular designated primary object. Upon receiving a selection of one or more of these options, the document is modified accordingly to generate the desired meme in the document.

Abstract: Mechanisms are provided for modifying an ontology for use with a natural language processing (NLP) task. A model of the ontology is obtained that comprises nodes representing concepts of the ontology and edges between nodes representing relationships between associated nodes of the ontology. A spreading activation operation is performed on the model of the ontology with the spreading activation operation matching a portion of a textual source to a matching node of the model and identifying related nodes to the matching node through edges of the model associated with the matching node to thereby generate an activation network. The activation network is evaluated with regard to a chosen NLP task to determine a performance metric for the NLP task associated with the nodes of the model. Based on the results, one of the model or a configuration of the activation network may be modified.

Abstract: A method, system and computer program product for assisting users to generate the desired meme in a document. A document is scanned to identify parts of speech, numerical text or numbers and images (collectively the “terms”) that provide positive/negative memes. A score for each of these terms is assigned. A score may then be assigned to each designated primary object (e.g., individual, company) discussed in the document using the scores assigned to the identified terms. Options may then be provided to modify the document to provide the type of meme (e.g., positive or negative meme) desired by the author to be associated with the particular designated primary object. Upon receiving a selection of one or more of these options, the document is modified accordingly to generate the desired meme in the document.

Abstract: A mechanism is provided for optimizing parsing of grammatical prose in a multi-prose electronic document. A received multi-prose electronic document is partitioned into a set of text segments of homogenous prose. A set of predefined Natural Language (NL) parsers is executed on each text segment in order to discern and measure a quality of parses by each NL parser throughout the multi-prose electronic document. A cross-parse analysis of the multi-prose electronic document and an aggregation of adjacent clauses or sentences of poor quality parses are performed. For each text segment, aggregation patterns yielding a best semantic role match are identified from one of the set of predefined NL parsers. Then, a parsed electronic document is generated using the set of predefined NL parsers such that each text segment is parsed by a NL parser that has the best semantic role match to that text segment.

Abstract: Natural language processing is provided. A unigram of a portion of text is determined, wherein the portion of text comprises a plurality of words. An initial confidence level of the unigram is determined, wherein the initial confidence level represents a probability that the unigram is of a semantic type identified by the initial confidence level. An expanded n-gram of the portion of text is determined, based, at least in part, on the unigram. Semantic analysis is performed on the expanded n-gram. At least one part of speech of the expanded n-gram is identified. Based, at least in part, on the initial confidence level, the semantic analysis, and the at least one part of speech, an adjusted confidence level of the expanded n-gram is determined.

Abstract: Mechanisms are provided for modifying an ontology for use with a natural language processing (NLP) task. A model of the ontology is obtained that comprises nodes representing concepts of the ontology and edges between nodes representing relationships between associated nodes of the ontology. A spreading activation operation is performed on the model of the ontology with the spreading activation operation matching a portion of a textual source to a matching node of the model and identifying related nodes to the matching node through edges of the model associated with the matching node to thereby generate an activation network. The activation network is evaluated with regard to a chosen NLP task to determine a performance metric for the NLP task associated with the nodes of the model. Based on the results, one of the model or a configuration of the activation network may be modified.

Abstract: Mechanisms are provided for generating section metadata for an electronic document. These mechanisms receive a document and analyze the document to identify concepts present within textual content of the document. The mechanisms correlate concepts within the textual content with one another to identify concept groups based on the application of one or more rules defining related concepts or concept patterns. The mechanisms determine sections of text within the textual content based on the correlation of concepts within the textual content. Based on results of the determining, the mechanisms generate section metadata for the document and store the section metadata in association with the document for use by a document processing system.

Abstract: Mechanisms are provided for generating section metadata for an electronic document. These mechanisms receive a document and analyze the document to identify concepts present within textual content of the document. The mechanisms correlate concepts within the textual content with one another to identify concept groups based on the application of one or more rules defining related concepts or concept patterns. The mechanisms determine sections of text within the textual content based on the correlation of concepts within the textual content. Based on results of the determining, the mechanisms generate section metadata for the document and store the section metadata in association with the document for use by a document processing system.

Abstract: The disclosure is directed to a method and system for accessing textual widgets. A method in accordance with an embodiment includes: entering a string expression into a document; invoking a spell-checker to check a spelling of the string expression; marking the string expression as misspelled; identifying a textual widget based on the misspelling of the string expression; evaluating the misspelled string expression using the identified textual widget, the identified textual widget returning at least one result of the evaluation; displaying the at least one result of the evaluation; selecting a result of the evaluation; and replacing the string expression in the document with the selected result of the evaluation.

Abstract: Socially provided context-based messaging can include receiving a message content in a messaging system from a user, wherein the content includes objects; matching one or more objects of the message content to socially provided context information, which the socially provided context information is information relevant to an object obtained from a social network to which the user belongs; and displaying the socially provided context information with the message content for a recipient user to receive.

Abstract: A method for providing content-level data artifact recommendations can begin with the creation of a semantic library from the textual content of data artifacts by a newsworthy content recommendation engine. A base newsworthiness rating can be calculated using global newsworthiness parameters and behavioral functions that model newsworthy influences for each relationship contained in the semantic library. A user-specific search network can be generated that represents user-entered criteria and/or user task-related criteria. Within the semantic library, potential newsworthy semantic networks can be identified. Newsworthy content from each identified potential newsworthy semantic network can be dynamically determined based upon the base newsworthiness rating and a predefined newsworthiness threshold. The newsworthy content from the identified potential newsworthy semantic network can be related to the user-specific search network at the common node, creating a newsworthy content recommendation graph.

Abstract: A method for providing content-level data artifact recommendations can begin with the creation of a semantic library from the textual content of data artifacts by a newsworthy content recommendation engine. A base newsworthiness rating can be calculated using global newsworthiness parameters and behavioral functions that model newsworthy influences for each relationship contained in the semantic library. A user-specific search network can be generated that represents user-entered criteria and/or user task-related criteria. Within the semantic library, potential newsworthy semantic networks can be identified. Newsworthy content from each identified potential newsworthy semantic network can be dynamically determined based upon the base newsworthiness rating and a predefined newsworthiness threshold. The newsworthy content from the identified potential newsworthy semantic network can be related to the user-specific search network at the common node, creating a newsworthy content recommendation graph.

Abstract: A method, system and computer program product for assisting users to generate the desired meme in a document. A document is scanned to identify parts of speech, numerical text or numbers and images (collectively the “terms”) that provide positive/negative memes. A score for each of these terms is assigned. A score may then be assigned to each designated primary object (e.g., individual, company) discussed in the document using the scores assigned to the identified terms. Options may then be provided to modify the document to provide the type of meme (e.g., positive or negative meme) desired by the author to be associated with the particular designated primary object. Upon receiving a selection of one or more of these options, the document is modified accordingly to generate the desired meme in the document.

Abstract: The disclosure is directed to a method and system for accessing textual widgets. A method in accordance with an embodiment includes: entering a string expression into a document; invoking a spell-checker to check a spelling of the string expression; marking the string expression as misspelled; identifying a textual widget based on the misspelling of the string expression; evaluating the misspelled string expression using the identified textual widget, the identified textual widget returning at least one result of the evaluation; displaying the at least one result of the evaluation; selecting a result of the evaluation; and replacing the string expression in the document with the selected result of the evaluation.