International Business Machines Corporation

Rema Ananthanarayanan

Biplav Srivastava

Diptikalyan Saha

Prasad Manikarao Deshpande

Raghuram Krishnapuram

Sreeram Viswanath Balakrishnan

Vijil Enara Chenthamarakshan

Shajeer K Mohammed

Vinatha Chaturvedi

Manish Anand Bhide

Sameep Mehta

Vibha Singhal Sinha

Sougata Mukherjea

Praveen Jayachandran

Akshat Verma

Kalapriya Kannan

Vikas Agarwal

Florian Graf

Xiaolan Zhang

Balaji Viswanathan

Sumit Mittal

Michael Edward Alexander

Lakshminarayanan Renganarayana

Kamal Bhattacharya

Pranay Kumar Lohia

Debdoot Mukherjee

Gagandeep Singh

Samiulla Zakir Hussain Shaikh

Aniya Aggarwal

Marcel Schlatter

Kristiann J Schultz

Sunil Goyal

Sandeep Hans

Bharat Krishnamurthy

Souptik Datta

Kuntal Dey

Seema Nagar

Mukesh Kumar Mohania

Sachindra Joshi

Roman Vaculin

Juhnyoung Lee

Krishna Kummamuru

Ajay Gupta

Pankaj Dhoolia

Rakesh Mohan

Berthold Reinwald

Anuradha Bhamidipaty

Richard Thomas Goodwin

Pietro Mazzoleni

Natwar Modani

Deepak S Padmanabhan

Calvin Stacy Powers

Aubrey J Rembert

Sweefen Goh

Alok Aggarwal

Senthil K Mani

Gerhard Sigl

Anca Andreea Ivan

Vipul Bansal

Mangala Gowri, Iii

Maharshi H Desai

Kathleen Byrnes

Charbak Chatterjee

Manas R Kumar Singh

Yuen Y Lo

Parul A Mittal

Satuloori Sridhar

Sreerama K Murthy

Atrayee Roychowdhury

Methods, systems, and computer program products for improving trustworthiness of artificial intelligence models in presence of anomalous data are provided herein. A method includes obtaining a machine learning model and a set of training data; determining one or more anomalous data points in said set of training data; for a given one of said anomalous data points, identifying attributes that decrease confidence with respect to at least one output of said machine learning model; determining that a root cause of said decreased confidence corresponds to one of: a class imbalance issue related to said at least one attribute, a confused class issue related to said at least one attribute, a low density issue related to said at least one attribute, and an adversarial issue related to said at least one attribute; and performing step(s) to improve said confidence based at least in part on said determined root cause.

Trustworthiness of artificial intelligence models in presence of anomalous data

Methods, systems, and computer program products for domain aware explainable anomaly and drift detection for multi-variate raw data using a constraint repository are provided herein. A computer-implemented method includes obtaining a set of data and information indicative of a domain of said set of data; obtaining constraints from a domain-indexed constraint repository based on said set of data and said information, wherein the domain-indexed constraint repository comprises a knowledge graph having a plurality of nodes, wherein each node comprises an attribute associated with at least one of a plurality of domains and constraints corresponding to the attribute; detecting anomalies in said set of data based on whether portions of said set of data violate said retrieved constraints; generating an explanation corresponding to each of the anomalies that describe the attributes corresponding to the violated constraints; and outputting an indication of the anomalies and the corresponding explanation.

Domain aware explainable anomaly and drift detection for multi-variate raw data using a constraint repository

Techniques for the automatic semantic analysis and comparison of chatbot capabilities are disclosed. A first chatbot specification associated with a first chatbot is obtained that includes a first plurality of characteristics arranged in a plurality of categories. A second chatbot specification associated with a second chatbot is obtained that includes a second plurality of characteristics arranged in the plurality of categories. One or more differences between the first plurality of characteristics and the second plurality of characteristics for each of the plurality of categories are identified based at least in part on the first plurality of characteristics and the second plurality of characteristics. A natural language expression corresponding to the identified one or more differences is generated and presented to a user via a graphical user interface.

Automatic semantic analysis and comparison of chatbot capabilities

An approach is provided that detect a section of a document that is currently being read by a user on a display device as well as the user's current emotional state. In response to determining, based on the detected current emotional state, that reading assistance would be helpful to the user, the approach identifies terminology within the section of the document that is currently being read by the user, retrieves assistive texts related to the identified terminology, and provides the assistive texts to the user at the display screen.

Assisting learners based on analytics of in-session cognition

Methods, systems, and computer program products for assessing value of one or more data sets in the context of a set of applications are provided herein. A computer-implemented method includes selecting analytic applications of interest based on a characterization of data attributes of each of the available data sets; automatically determining an impact of each of the data attributes of each of the available data sets on an end value of each of the analytic applications of interest; automatically computing an amount of improvement to the end value of each of the analytic applications of interest based on inclusion of an additional data set; and automatically determining a value attributed to the additional data set based on a comparison of (i) the cost of adding the additional data set to the available data sets to (ii) the computed amount of improvement based on the inclusion of the additional data set.

Assessing value of one or more data sets in the context of a set of applications

Methods and arrangements for document quality assessment. Documents are accepted and a quality specification containing predetermined quality criteria is assimilated. Each document is assessed based on the predetermined quality criteria, and a quality score is assigned to each document, the quality score being a function of positive and negative attributes assessed for each document.

Automatically assessing document quality for domain-specific documentation

An arbitrary customer instance is transferred from a customer environment to a target managed-infrastructure-as-a-service cloud environment as a transferred image. An image adjustment plan, capturing at least one adjustment required to render the transferred image compliant with standards of the target managed-infrastructure-as-a-service cloud environment, is formulated. The image adjustment plan is executed to adjust the transferred image to obtain an adjusted image compliant with standards of the target managed-infrastructure-as-a-service cloud environment. The adjusted image is on-boarded into the managed-infrastructure-as-a-service cloud environment as a standard image thereof.

Adjustment to managed-infrastructure-as-a-service cloud standard

Systems and associated methods for automated and semi-automated building of domain models for documents are described. Embodiments provide an approach to discover an information model by mining documentation about a particular domain captured in the documents. Embodiments classify the documents into one or more types corresponding to concepts using indicative words, identify candidate model elements (concepts) for document types, identify relationships both within and across document types, and consolidate and learn a global model for the domain.

System and method to extract models from semi-structured documents

Methods and arrangements for automatically finding the dependency of a software product on other software products or components. From an install image or directory, a signature is found by deriving the same from a directory structure of the software. Further, a directory tree structure is built and an approximate sub-tree matching algorithm is applied to find commonalities across software products.

Mining dependencies from disk images

Methods and arrangements for automatically finding the dependency of a software product on other software products or components. From an install image or directory, a signature is found by deriving the same from a directory structure of the software. Further, a directory tree structure is built and an approximate sub-tree matching algorithm is applied to find commonalties across software products.

Methods and arrangements for reconfiguring an analytics model without retraining the analytics model. A contemplated method includes: providing a cloud-based classifier which performs analytics on input data, the classifier including an analytics model; receiving a first data set at the classifier, wherein the first data set is a training data set; via the analytics model, discovering features in the first data set; receiving a second input data set at the classifier; via the analytics model, discovering one or more new features in the second input data set; and reconfiguring the analytics model, without retraining the analytics model, based on one or more new features discovered in the second input data set. Other variants and embodiments are broadly contemplated herein.

Self-adaptive classifiers

Methods and arrangements for on-boarding an application to a cloud. An application for hosting in a cloud environment is provided. Metadata related to the application is provided, and metadata related to the cloud is obtained. The application metadata and cloud metadata are compared, and the compatibility of the application with existing offerings of the cloud is ascertained. The application is on-boarded to the cloud.

On-boarding applications to a cloud

Methods and systems for on-boarding applications to a cloud

Product data pertaining to a plurality of products is gathered from a plurality of sources. Dependency information for the plurality of products is extracted from the product data. The dependency information is analyzed to determine dependencies for each product of the plurality of products. The dependencies for each product of the plurality of products are displayed to a user.

Discovery, analysis, and visualization of dependencies

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New Delhi, India

Rema Ananthanarayanan