International Business Machines Corporation

University of Illinois

Ruchi Mahindru

Valentina Salapura

John Alan Bivens

Min Li

Eugen Schenfeld

Harigovind Venkatraj Ramasamy

Yaoping Ruan

Soumitra Sarkar

Yu Deng

Long Wang

Mahesh Viswanathan

Koushik Kumar Das

Rafah A Hosn

Richard Edwin Harper

Ashish Kundu

Norbert George Vogl

Anca Sailer

Michael Man Behrendt

Murthy V Devarakonda

Lingfei Wu

Daniela Rosu

Ajay Mohindra

Andrzej P Kochut

Alfio Massimiliano Gliozzo

Amos Cahan

Awadesh Kumar Tiwari

Shu Tao

Karin Murthy

Lakshminarayanan Renganarayana

Xing Wei

Md Faisal Mahbub Chowdhury

Gautam Kar

Nithya Rajamani

Gaetano Rossiello

Syed Yousaf Shah

Sinem Guven Kaya

Nicolas Rodolfo Fauceglia

Ramshanker Kowta

Rajarshi Haldar

Xin Zhou

Tara Lynn Astigarraga

Alexei A Karve

Charles Otto Schulz

Yixin Diao

Harshit Kumar

Robert K Floyd, Iii

Nandana Sampath Mihindukulasooriya

Atul Kumar

Clifford A Pickover

Michael K Gschwind

Maja Vukovic

Seema Nagar

Jinho Hwang

Richard Harold Boivie

Anbang Xu

Kirk Alan Beaty

Salman Abdul Baset

Sharon Mary Trewin

Chunqiang Tang

Amitkumar Manoharrao Paradkar

Gargi Banerjee Dasgupta

Martin Franz

Kaoutar El Maghraoui

Pooja Aggarwal

Bhavna Agrawal

Atri Mandal

Sarthak Dash

Ian Manning

Rohan R Arora

Simon J Kofkin-Hansen

Matthew Richard James Thornhill

Lu An

Suraj Subramanian

Sahil Bansal

Jayachandran Kizhakoot Ramachandran

Manas R Kumar Singh

Kevin Wahlmeier

Julia Constanze Hockenmaier

Stephen James Hussey

Cuong Manh Pham

Meng Jiang

Qingkai Zeng

Wenhao Yu

Franco Forti

Karan Bhukar

Theodor Razvan Ionescu

Christopher Moss

Richard Christopher Smith

Zhiyu Chen

Abhas Bodas

Techniques are provided for dynamic alert suppression policy management. In one embodiment, the techniques involve receiving an event stream, wherein the event stream includes metric values comprising at least one of: log anomaly data and metric anomaly data, determining an anomalous event based on the event stream, determining a persistent region of the anomalous event, determining a quantum representation of the persistent region, determining X-Y values of the persistent region based on the quantum representation, and generating a policy based on a set of the X-Y values.

Dynamic alert suppression policy management

A system, computer program product, and a computer implemented method are provided for interfacing with a virtual dialog environment to dynamically and optimally collected context for problem diagnosis and resolution. A context model is leveraged to identify context entities, and one or more corresponding context collection mechanisms. The context model is implemented in real-time to facilitate dynamic selection of one or more of the identified context collection mechanisms, which are selectively subject to execution to resolve the problem diagnosis.

Virtual dialog system dynamic context collection

Systems, computer-implemented methods, and/or computer program products facilitating a process to monitor and evaluate the effects of an artificial intelligence (AI) model on enterprise performance metrics are provided. According to an embodiment, a computer implemented method can comprise determining a technical issue of candidate technical issues associated with an artificial intelligence model that correlates to a change associated with a performance metric, wherein the determination is based on using a first data model that defines first relationships between the key performance metrics and candidate technical issues and second relationships between the candidate technical issues and candidate solutions. The method further comprises determining a solution for the technical issue using the data model and recommending or automatically implementing the solution. The method further provides for updating/refining the data model over time using continuous learning based on evaluating whether and how implemented solutions impact the relevant performance metrics.

Evaluating effects of an artificial intelligence model on enterprise performance objectives

Computer-implemented techniques for unsupervised event extraction are provided. In one instance, a computer implemented method can include parsing, by a system operatively coupled to a processor, unstructured text comprising event information to identify candidate event components. The computer implemented method can further include employing, by the system, one or more unsupervised machine learning techniques to generate structured event information defining events represented in the unstructured text based on the candidate event components.

Unsupervised event extraction

Embodiments of the present invention provide a computer system, a computer program product, and a method that comprises analyzing a performed query by identifying a plurality of indicative markers based on a pre-stored classification database associated with the performed query; generating a plurality of facets based on the analysis of the performed query; selecting at least two facets within the generated plurality of facets by determining a quantitative similarity value between each respective facet and the plurality of identified indicative markers associated with the performed query; dynamically ranking the selected facets by prioritizing the selected facets based on a calculated overall score associated with assigned weighted values for each selected facet in the generated plurality of facets using a supervised machine learning algorithm; and displaying the dynamically ranked facets within a user interface of a computing device associated with a user.

Dynamic facet ranking

Embodiments are provided that relate to a computer system, a computer program product, and a computer-implemented method for improving performance of a dialog system employing an automated virtual dialog agent. Embodiments involve utilizing an automated virtual agent to receive a natural language request and generate a corresponding response, automatically identifying and resolving a corresponding knowledge gap between the request and response, and refining the automated virtual agent with the resolved knowledge gap.

Natural language enrichment using action explanations

Identifying an log anomaly resolution by generating a knowledge base linking each of a plurality of incidents with historical anomalous log lines, calculating a resolution specificity score for each knowledge base record, identifying a run-time anomalous log line using the knowledge base, predicting a category for the run-time anomalous log line, identifying resolutions according to the category, ranking the resolutions according to the resolution specificity scores, and recommending a resolution according to the ranking.

Identifying log anomaly resolution from anomalous system logs

A method for estimating response relevance with respect to a received query includes receiving a set of user feedback items, a set of historical feedback data, and a set of context data, creating a user profile model according to the set of historical feedback data, wherein the user profile model indicates a weighting attribute based on the set of historical feedback data, weighting the set of user feedback items according to the created user profile model, creating a response relevance estimation model based on the weighted set of user feedback items, the received set of context data, and the received set of historical feedback data, and ranking one or more responses according to the created response relevance estimation model. The method may further include adjusting the user profile model and the response relevance estimation model responsive to receiving additional data.

Query response relevance determination

An approach for a non-factoid question answering framework across tasks and domains may be provided. The approach may include training a multi-task joint learning model in a general domain. The approach may also include initializing the multi-task joint learning model in a specific target domain. The approach may include tuning the joint learning model in the target domain. The approach may include determining which task of the multiple tasks is more difficult for the multi-task joint learning model to learn. The approach may also include dynamically adjusting the weights of the multi-task joint learning model, allowing the model to concentrate on learning the more difficult learning task.

Non-factoid question answering across tasks and domains

Embodiments are provided that relate to a computer system, a computer program product, and a computer-implemented method for improving performance of a virtual dialog agent system employing an automated virtual dialog agent. Embodiments involve generating ground truth (GT) from a user's knowledge base, and leveraging the GT to evaluate how the virtual dialog agent performs with the GT. The evaluation measures quality of a multi-turn virtual dialog, and generates a remediation plan directed at an algorithmic improvement of the virtual dialog agent.

Virtual dialog system performance assessment and enrichment

Embodiments are provided herein for efficient component communication and resource optimization in a disaggregated computing system. A first set of computing elements are used as in line accelerators and a second set of the computing elements are used as block accelerators within the disaggregated computing system. A switching operation is dynamically performed between the first set of computing elements and the second set of computing elements to perform a workload by rewiring one of a plurality of links associated with respective ones of the first set of computing elements and the second set of computing elements.

Efficient component communication through accelerator switching in disaggregated datacenters

Systems, devices, computer-implemented methods, and/or computer program products that facilitate event schema induction from unstructured or semi-structured data. In one example, a system can comprise a processor that executes computer executable components stored in memory. The computer executable components can comprise a schema component and a retrieval component. The schema component can derive an event schema for a document corpus using parsing results obtained from the document corpus. The retrieval component can populate a response to a query with a document of the document corpus using events extracted from the query and the document using the event schema.

Graph-based event schema induction for information retrieval

An example operation may include one or more receiving notifications from one or more monitoring agents, each notification comprising a monitoring agent identifier, one or more configuration changes, and a timestamp corresponding to each configuration change, identifying incremental configuration changes that may require a disaster recovery retest, requesting a partial disaster recovery retest comprising the incremental configuration changes, the partial disaster recovery retest providing test coverage for a subset of a full disaster recovery test plan, and providing a request to a blockchain network to store information for the received notifications to a shared ledger of the blockchain network.

Database optimized disaster recovery orchestrator

One embodiment of the invention provides a method for terminology ranking for use in natural language processing. The method comprises receiving a list of terms extracted from a corpus, where the list comprises a ranking of the terms based on frequencies of the terms across the corpus. The method further comprises accessing a domain ontology associated with the corpus, and re-ranking the list based on the domain ontology. The resulting re-ranked list comprises a different ranking of the terms based on relevance of the terms using knowledge from the domain ontology. The method further comprises generating clusters of terms via a trained model adapted to the corpus, and boosting a rank of at least one term of the re-ranked list based on the clusters to increase a relevance of the at least one term using knowledge from the trained model.

Discovering ranked domain relevant terms using knowledge

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Elmsford, NY, United States of America

Ruchi Mahindru