Abstract: A set of clinical trial information associated with a clinical trial process is monitored. In response to the monitoring, a clinical trial status is generated. The clinical trial status and at least a subset of the set of clinical trial information is aggregated with a plurality of historical clinical trial statuses and information. From the aggregation, a queryable knowledge base describing each clinical trial status and information within the aggregation is generated. In response to the generation of the queryable knowledge base, a user is notified of at least one of the aggregation of clinical trial statuses and information.

Abstract: Methods, systems and computer readable media are provided for accessing data utilizing a multi-level table comprising generating a plurality of levels of the multi-level table, wherein a first level of the multi-level table includes a hyper-table with a plurality of hyper-cells each hyper-cell including information for a group of cells from an initial base table, wherein intermediate levels of the multi-level table each include a plurality of hyper-tables comprising hyper-cells with each hyper-table linked to and providing information for a corresponding hyper-cell of a hyper-table of a prior level, and wherein a plurality of tables of a terminal level includes information from cells of the initial base table with each table linked to and providing information for a corresponding hyper-cell. Data from the multi-level table is accessed by traversing links between the hyper-tables of the plurality of levels to access data within the tables of the terminal level.

Abstract: A method for ranking a relationship between drugs and adverse events includes creating a matrix of associations between a plurality of drugs and a plurality of adverse events and factoring the matrix of associates into a pair of matrix factors. The matrix factors, when multiplied, approximate the matrix of associations, and a product of the matrix factors is a matrix of observed scores. The method further includes determining, for each drug and adverse event pair in the matrix of observed scores, a z-score, an expected score for each drug and adverse event pair, and a standard deviation for each drug and adverse event pair, calculating a probability of a relationship between a drug and adverse event using the z-score for the drug and adverse event pair, and determining that the drug and adverse event are related, when the probability of a relationship is greater than a predetermined magnitude.

Abstract: A method for ranking a relationship between drugs and adverse events includes creating a matrix of associations between a plurality of drugs and a plurality of adverse events and factoring the matrix of associates into a pair of matrix factors. The matrix factors, when multiplied, approximate the matrix of associations, and a product of the matrix factors is a matrix of observed scores. The method further includes determining, for each drug and adverse event pair in the matrix of observed scores, a z-score, an expected score for each drug and adverse event pair, and a standard deviation for each drug and adverse event pair, calculating a probability of a relationship between a drug and adverse event using the z-score for the drug and adverse event pair, and determining that the drug and adverse event are related, when the probability of a relationship is greater than a predetermined magnitude.

Abstract: Techniques for analysis of relationship consistency are provided. A plurality of relationships is extracted from a plurality of documents, and a binary matrix is generated based on the plurality of relationships. A first relationship, of the plurality of relationships, is identified to be verified. A score of the first relationship in the binary matrix is set to a predefined value. Further, a factorization is performed on the binary matrix to produce a first matrix and a second matrix. A first consistency score is calculated for the first relationship by multiplying at least a portion of the first matrix and a second matrix. The first consistency score is ranked as compared to at least one other consistency score associated with at least one other relationship of the plurality of relationships. Finally, an indication of the first relationship is provided, based on the ranking.

Abstract: Methods, systems and computer readable media are provided for accessing data utilizing a multi-level table comprising generating a plurality of levels of the multi-level table, wherein a first level of the multi-level table includes a hyper-table with a plurality of hyper-cells each hyper-cell including information for a group of cells from an initial base table, wherein intermediate levels of the multi-level table each include a plurality of hyper-tables comprising hyper-cells with each hyper-table linked to and providing information for a corresponding hyper-cell of a hyper-table of a prior level, and wherein a plurality of tables of a terminal level includes information from cells of the initial base table with each table linked to and providing information for a corresponding hyper-cell. Data from the multi-level table is accessed by traversing links between the hyper-tables of the plurality of levels to access data within the tables of the terminal level.

Abstract: Methods, systems and computer readable media are provided for accessing data utilizing a multi-level table comprising generating a plurality of levels of the multi-level table, wherein a first level of the multi-level table includes a hyper-table with a plurality of hyper-cells each hyper-cell including information for a group of cells from an initial base table, wherein intermediate levels of the multi-level table each include a plurality of hyper-tables comprising hyper-cells with each hyper-table linked to and providing information for a corresponding hyper-cell of a hyper-table of a prior level, and wherein a plurality of tables of a terminal level includes information from cells of the initial base table with each table linked to and providing information for a corresponding hyper-cell. Data from the multi-level table is accessed by traversing links between the hyper-tables of the plurality of levels to access data within the tables of the terminal level.

Abstract: Methods, systems, and computer program products for correcting existing predictive model outputs with social media features over multiple time scales are provided herein. A method includes examining multiple items of user content derived from one or more social media sources during a given time period to identify one or more items of user content pertaining to a target entity; analyzing the items of user content pertaining to the target entity to determine one or more predictive features in the items of user content related to a target variable associated with the target entity; computing a correlation measure between each of the predictive features and the target variable; and modifying an output of an existing predictive model associated with the target variable via incorporation of the predictive feature with the highest correlation measure into the output of the existing predictive model to generate an updated predictive output.

Abstract: A method, system, and computer program product for event detection using roles and relationships of entities are provided in the illustrative embodiments. A training event and a set of entities participating in the training event are identified in a training data. For a first entity in the set of entities, a first role occupied by the entity in the event is determined. A behavior attribute is assigned to the first role. A relationship of the first role with a second role corresponding to a second entity in the set of entities is determined. An event rule is constructed to detect an event corresponding to the training event in new data and comprising a plurality of roles, behavior attributes, and the relationship. The plurality of roles includes the first role and the second role, and the plurality of behavior attributes includes the behavior attribute assigned to the first role.

Abstract: A new information in a language and relating to a subject matter domain is parsed into a constituent set of complete grammatical constructs. In a subset of the complete grammatical constructs, a set of linguistic styles of the language is identified according to a subset of a set of word-style associations related to the language and independent of the subject matter domain. A first weight is assigned to a first linguistic style and a second weight to a second linguistic style from the set of linguistic styles. A first intention information is mapped to the first style using a first style-intention rule, and a second intention information to the second style using a second style-intention rule. A complete grammatical construct in the subset is tagged with the first intention information responsive to a weight associated with the first intention information exceeding an intention selection threshold.

Abstract: Methods, systems, and articles of manufacture for entity-level technology recommendation are provided herein. A method includes searching a first query against a first corpus of documents to determine a set of documents matching an entity of interest identified in the first query, generating a list of technologies that (i) appear within the content of the set of documents and (ii) are associated to the entity of interest, searching a second query against a second corpus of documents to determine a set of documents representing a technology recommendation for the entity of interest, wherein said second query is based on one or more selected technologies from the list of technologies, and outputting the set of documents representing a technology recommendation to a user and/or a display.

Abstract: An approach is provided to identify important paths in a biological relationship graph for exploration by researchers. In the approach, a biological meaningfulness analysis is performed on the biological relationship graph that has a number of paths through the graph formed by a number of connected nodes. The biological meaningfulness analysis is based on a process similarity calculation of gene ontologies of the nodes in the paths and a contextual similarity calculation of word occurrences from documents in a corpus where a reference to the respective nodes are found. A biological interestingness analysis is also performed on the biological relationship graph. The paths are screened based on the meaningfulness analysis and the interestingness analysis. The screened data is displayed to the user.

Abstract: A new information in a language and relating to a subject matter domain is parsed into a constituent set of complete grammatical constructs. In a subset of the complete grammatical constructs, a set of linguistic styles of the language is identified according to a subset of a set of word-style associations related to the language and independent of the subject matter domain. A first weight is assigned to a first linguistic style and a second weight to a second linguistic style from the set of linguistic styles. A first intention information is mapped to the first style using a first style-intention rule, and a second intention information to the second style using a second style-intention rule. A complete grammatical construct in the subset is tagged with the first intention information responsive to a weight associated with the first intention information exceeding an intention selection threshold.

Abstract: A method, system, and computer program product for event detection using roles and relationships of entities are provided in the illustrative embodiments. A training event and a set of entities participating in the training event are identified in a training data. For a first entity in the set of entities, a first role occupied by the entity in the event is determined. A behavior attribute is assigned to the first role. A relationship of the first role with a second role corresponding to a second entity in the set of entities is determined. An event rule is constructed to detect an event corresponding to the training event in new data and comprising a plurality of roles, behavior attributes, and the relationship. The plurality of roles includes the first role and the second role, and the plurality of behavior attributes includes the behavior attribute assigned to the first role.

Abstract: A new information in a language and relating to a subject matter domain is parsed into a constituent set of complete grammatical constructs. In a subset of the complete grammatical constructs, a set of linguistic styles of the language is identified according to a subset of a set of word-style associations related to the language and independent of the subject matter domain. A first weight is assigned to a first linguistic style and a second weight to a second linguistic style from the set of linguistic styles. A first intention information is mapped to the first style using a first style-intention rule, and a second intention information to the second style using a second style-intention rule. A complete grammatical construct in the subset is tagged with the first intention information responsive to a weight associated with the first intention information exceeding an intention selection threshold.

Abstract: A new information in a language and relating to a subject matter domain is parsed into a constituent set of complete grammatical constructs. In a subset of the complete grammatical constructs, a set of linguistic styles of the language is identified according to a subset of a set of word-style associations related to the language and independent of the subject matter domain. A first weight is assigned to a first linguistic style and a second weight to a second linguistic style from the set of linguistic styles. A first intention information is mapped to the first style using a first style-intention rule, and a second intention information to the second style using a second style-intention rule. A complete grammatical construct in the subset is tagged with the first intention information responsive to a weight associated with the first intention information exceeding an intention selection threshold.

Abstract: A method for analyzing predefined subject matter in a patent database being for use with a set of target patents, each target patent related to the predefined subject matter, the method comprising: creating a feature space based on frequently occurring terms found in the set of target patents; creating a partition taxonomy based on a clustered configuration of the feature space; editing the partition taxonomy using domain expertise to produce an edited partition taxonomy; creating a classification taxonomy based on structured features present in the edited partition taxonomy; creating a contingency table by comparing the edited partition taxonomy and the classification taxonomy to provide entries in the contingency table; and identifying all significant relationships in the contingency table to help determine the presence of any white space.

Abstract: Methods, systems, and computer program products for correcting existing predictive model outputs with social media features over multiple time scales are provided herein. A method includes examining multiple items of user content derived from one or more social media sources during a given time period to identify one or more items of user content pertaining to a target entity; analyzing the items of user content pertaining to the target entity to determine one or more predictive features in the items of user content related to a target variable associated with the target entity; computing a correlation measure between each of the predictive features and the target variable; and modifying an output of an existing predictive model associated with the target variable via incorporation of the predictive feature with the highest correlation measure into the output of the existing predictive model to generate an updated predictive output.

Abstract: Methods, systems, and articles of manufacture for entity-level technology recommendation are provided herein. A method includes searching a first query against a first corpus of documents to determine a set of documents matching an entity of interest identified in the first query, generating a list of technologies that (i) appear within the content of the set of documents and (ii) are associated to the entity of interest, searching a second query against a second corpus of documents to determine a set of documents representing a technology recommendation for the entity of interest, wherein said second query is based on one or more selected technologies from the list of technologies, and outputting the set of documents representing a technology recommendation to a user and/or a display.

Abstract: A method and analytics tools for information mining incorporating domain specific knowledge and conceptual structures are disclosed, the method including: providing a first set of documents related to a first topic of interest; using a first taxonomy to categorize the first set of documents into a set of categories; providing a second set of documents related to a second topic of interest; categorizing the second set of documents according to the set of categories of the first set of documents; using an element of domain knowledge to re-categorize the first set of documents; and examining a category to identify a document of interest.