International Business Machines Corporation

Globalfoundries U.S. 2 LLC

Jeffrey Thomas Kreulen

William Scott Spangler

James J Rhodes

Ying Chen

Stephen Kane Boyer

Vikas Krishna

Hovey Raymond Strong

Fatma Ozcan

Dorian B Miller

Justin Thomas Lessler

Tapas Kanungo

Dharmendra S Modha

Gregory Breyta

Hovey R Strong, Jr

Abdul Hussain Quamar

Ana Lelescu

Chuan Lei

W Scott Spangler

Kenneth M Johns

William Cody

Rebecca Geis

Karen Mae Holland

Neelakantan Sundaresan

Robert Lee Angell

Brian Walter O'Krafka

Richard D Hennessy

Robert John Moore

Shivakumar Vaithyanathan

Vahit Hakan Hacigumus

Sanjay Raghunath Deshpande

Matthias Eichstaedt

Linda Ha Kato

Manuel Joseph Alvarez, Ii

David Charles Martin

Clifford V Harris

Rajasekar Krishnamurthy

Prithviraj Sen

Kevin Snow McCurley

Laura Chiticariu

Jacques Labrie

Hovey Ramond Strong, Jr

James William Cooper

Ignacio Gabriel Terrizzano

Sriram Srinivasan Mandyam

Ramanathan Raghavan

Larry Lee Proctor

Shahram Salamian

Herschel J R Weintraub

Michael Arthur Lamb

Sami Nicole Rollins

Amy W Chow

Michael Ponce Sanchez

Christina Runkel

Gregory Alan Hughes

Audrey Davis Romonosky

An offline adaptation method of customizing and incorporating external knowledge domain specific knowledge sources into an existing knowledge base (KB) of a cognitive conversation system, includes obtaining an instance-concept frequency from the existing KB. All the contexts of a domain ontology in which an instance-concept is used are computed. All instance-concepts from the existing KB to an external domain-specific knowledge source are mapped. The existing KB is configured to search for semantically related terms in response to a natural language query received from a conversation system.

Query relaxation using external domain knowledge for query answering

A computer-implemented method for generating an ontology-driven conversational interface includes generating an ontology from a description of a domain schema of a Data Analysis (DA) model, in which the DA model is a defined in terms of quantifiable, qualifying or categorical entities and their relationships as described by the domain schema. Conversational artifacts of a conversation space including a conversational pattern framework are generated by extracting DA-related intents, entities, and a dialog from the generated ontology for the conversational interface. A dialog logic table maps DA-related patterns to intents, extracted quantifiable, qualifying or categorical attributes to entities, and the dialog to user-prompts for one or more parameters in an identified DA pattern. The conversation space is integrated with at least one of an external data source or an analytics platform that stores and processes data.

Ontology-driven conversational interface for data analysis

A system, method, and computer readable medium perform a method of query relaxation. A query output from a conversational system is received. At least one search term in the query is identified. Instance data is output to the conversational system in response to determining that the instance data in a data store matches the at least one search term in the query. The computer device outputs the received query to an external domain-specific knowledge source in response to determining that the at least one search term does not the match instance data in the data store. The computer device receives the relaxed data matches from the external domain-specific knowledge source being semantically-related to at least one search term in the query based on a plurality of criteria associated with the query. The computing device generates a response to the query based on contextual information and structural information.

A method is provided to implement a conversational system with artifact generation. A middleware component receives a user input and determines whether there is sufficient information in the user input and a conversation space in a context storage of the conversational system to identify user intent associated with the user input. Responsive to the middleware component determining there is not sufficient information to identify user intent, a communications handler component sends a natural language query to an external data source via a natural language query (NLQ) interface and receives a natural language response from the external data source. The middleware component updates the conversation space based on the natural language response and returns a user response based on the natural language response.

Conversation space artifact generation using natural language processing, machine learning, and ontology-based techniques

The present invention relates to a method and system for associating gene expression data with a disease name. A first data set associated with a plurality of genetic probes for a plurality of biological samples may be received. The first data set may be sorted based on a normalized gene expression values for the plurality of genetic probes. A largest value gap of the normalized gene expression values may be identified. A set of expressed genes within the first data set may be identified. An indexable document may be generated for a biological sample of the plurality of biological samples comprising data associated with the set of expressed genes. A second data set associated with an expressed gene of the set of expressed genes may be searched. A disease name may be associated with an expressed gene based on a threshold correlation between the disease name and the expressed gene.

Associating gene expression data with a disease name

One embodiment provides a method for developing a text analytics program for extracting at least one target concept including: utilizing at least one processor to execute computer code that performs the steps of: initiating a development tool that accepts user input to develop rules for extraction of features of the at least one target concept within a dataset comprising textual information; developing, using the rules for feature extraction, an evaluation dataset comprising at least one document annotated with the at least one target concept to be extracted by the text analytics program; creating, using the rules for feature extraction, a rule-based annotator to extract the at least one target concept; training, using the evaluation dataset, a machine-learning annotator to extract the at least one target concept within the dataset; combining the rule-based annotator and the machine learning annotator to form a combined annotator; evaluating, using the evaluation dataset, extraction performance of the combined annotator against a predetermined threshold; and publishing, when the extraction performance of the combined annotator exceeds the predetermined threshold, the combined annotator for use in an application that extracts the at least one target concept from a plurality of datasets.

Unified text analytics annotator development life cycle combining rule-based and machine learning based techniques

A system and method for processing a document to generate a set of related documents. A system is provided that includes a textual analytics system that analyzes unstructured data contained in a source document and extracts a set of structured information about the source document; and a compare system that identifies a set of related documents by comparing the set of structured information with metadata indexed from a set of publications.

System and method for using text analytics to identify a set of related documents from a source document

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.

Methodologies and analytics tools for identifying white space opportunities in a given industry

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.

Information mining using domain specific conceptual structures

A method and analytics tools for locating experts with specific sets of expertise are disclosed, the method including providing a collection of documents P; generating categories representing fields of expertise derived from the collection of documents P; refining the taxonomy of the categories by applying user domain knowledge; extracting structured fields from the collection of documents P; constructing a contingency table having a first axis defined by the extracted structured fields and a second axis defined by the categories; and using the contingency table to identify a set of experts having a related expertise. The method may also include a network graph analysis that aids visualization of the relationship between people and expertise.

Methodologies and analytics tools for locating experts with specific sets of expertise

A vectorization process is employed in which chemical identifier strings are converted into respective vectors. These vectors may then be searched to identify molecules that are identical or similar to each other. The dimensions of the vector space can be defined by sequences of symbols that make up the chemical identifier strings. The International Chemical Identifier (InChI) string defined by the International Union of Pure and Applied Chemistry (IUPAC) is particularly well suited for these methods.

System and method for identifying similar molecules

A data warehouse is created using an input file that can contain sub-documents of different formats. A root document model including path names to all nodes among the sub-documents is generated, and a table is generated with columns being derived from the path names of the root model. The sub-documents are shredded to populate the table. Then, the dimensions of the data warehouse are defined by selecting respective columns. A routine such as a DDL may then be generated to populate the data warehouse with data.

Method and system for creating and loading data warehouse from semi-structured document

Methods, systems and computer program products for simplifying complex data stream problems involving feature extraction from noisy data. Exemplary embodiments include a method for processing a data stream, including applying multiple operators to the data stream, wherein an operation by each of the multiple operators includes retrieving the next chunk for each of set of input parameters, performing digital processing operations on a respective next chunk, producing sets of output parameters and adding data to one or more internal data stores, each internal data store acting as a data stream source.

Simplifying complex data stream problems involving feature extraction from noisy data

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San Jose, CA, United States of America

Jeffrey Thomas Kreulen