Abstract: Recommending machine learning models is provided. The method comprises training machine learning models, wherein each machine learning model is trained with a unique respective dataset. Metadata associated with each machine learning model is extracted, wherein the metadata includes properties of the respective dataset used to train the machine learning model. The machine learning models and metadata are stored in a model catalog. Upon receiving a new dataset, similarity scores are calculated between the new dataset and the machine learning models in the model catalog according to the properties of the datasets in the metadata of the machine learning models. A closest match machine learning model is identified from the model catalog for the new dataset according to similarity score. Responsive to a determination that the closest match machine learning model exceeds a similarity threshold, predictions for the new dataset are generated with the closest match machine learning model.

Abstract: A method, computer system, and a computer program product for anomaly detection is provided. The present invention may include converting business process logs into a graphical data structure. The present invention may include generating an optimized graph encoding for anomaly detection using an unsupervised machine learning model. The present invention may include computing an anomaly score for each activity of the business process log using a process aware metric based on feature representation. The present invention may include labeling each of the one or more data points with a high anomaly score.

Abstract: A method, computer system, and a computer program product for anomaly detection is provided. The present invention may include converting business process logs into a graphical data structure. The present invention may include generating an optimized graph encoding for anomaly detection using an unsupervised machine learning model. The present invention may include computing an anomaly score for each activity of the business process log using a process aware metric based on feature representation. The present invention may include labeling each of the one or more data points with a high anomaly score.

Abstract: Embodiments of the present invention provide computer-implemented methods, computer program products and computer systems. Embodiments of the present invention enrich received information based on identified attributes. Embodiments of the present invention can then dynamically generate a recommendation that satisfies a goal based, at least in part on the enriched information. Embodiments of the present invention can then execute at least one dynamically generated goal that satisfies the goal.

Abstract: A method for providing personalized reading assistance using visual modifications. The method includes forecasting a complexity of a text corpus for a user. The text corpus includes a plurality of words. Visual modifications may be provided to at least some words of the plurality of words in the text corpus based on the forecast complexity of the text corpus for the user.

Abstract: In an approach to improve knowledge content query generation, embodiments identify one or more drift points based on implicit user feedback-based assessment and a user experience to generate one or more knowledge content queries of different complexity from a multi-media file. Further, embodiments adjust a threshold for the one or more drift points to generate different variations of the one or more knowledge content queries and perform iterative refinement on the one or more knowledge queries based on one or more previous iteration evaluations. Additionally, embodiments generate the one or more knowledge content queries in different modalities based on the multi-media file and the threshold for the one or more drift points.

Abstract: Provided is a computer-implemented method, system, and computer program product for process mining asynchronous support conversations using attributed directly follows graphing. A processor may collect a plurality of conversation threads from an asynchronous data stream. The processor may label each utterance of a plurality of utterances from the plurality of conversation threads with an event label. The processor may analyze the event label for each utterance of the plurality of utterances. The processor may generate, based on the analyzing of the event label for each utterance, an attributed directly follows graph (DFG).

Abstract: A system may include a memory and a processor in communication with the memory. The processor may be configured to perform operations. The operations may include extracting a first multiple dimensional dataset and a second multiple dimensional dataset and encoding the first multiple dimensional dataset into a first encoded dataset and the second multiple dimensional dataset into a second encoded dataset. The operations may include combining the first encoded dataset and the second encoded dataset into a combined encoded dataset and conveying the combined encoded dataset to a user.

Abstract: Methods, systems, and computer program products for generating organizational goal-oriented and process conformant recommendation models using artificial intelligence techniques are provided herein.

Abstract: A computer system provides haptic feedback based on content analytics. Media data is analyzed using a machine learning model to identify one or more moods for one or more portions of the media data. A haptic feedback response is determined based on the identified one or more moods. Instructions are provided to a haptic feedback device to cause the haptic feedback device to apply the haptic feedback response to a user in synchronization with presentation of the media data to the user. Embodiments of the present invention further include a method and program product for providing haptic feedback based on content analytics in substantially the same manner described above.

Abstract: Mechanisms are provided for automatically generating a user interactable what-is-new feature for an updated application. The mechanisms obtain footprint data from electronic documents generating during a software development lifecycle to generate an update to an application, where the footprint data specifies development requirements and actions performed by at least application developers during the software development lifecycle. The mechanisms further obtain test case generation data from a recording of test case generation interactions with a graphical user interface and execute computer natural language processing on the footprint data and analysis of the recording of the test case generation interactions to automatically generate a what-is-new container for the update to the application.

Abstract: According to one embodiment, a method, computer system, and computer program product for cloud service brokerage. The embodiment may include receiving a data set and user defined contextual parameters relating to a machine learning (ML) problem of a user to be performed on the data set. The embodiment may include identifying a resource requirement of the ML problem and available resources. The embodiment may include enabling user configuration of the contextual parameters in an interactive augmented reality (AR) view. The embodiment may include identifying a set of clusters upon which to execute computing tasks of the ML problem. The set of clusters is identified out of the available resources. The embodiment may include implementing a ML evaluation process to determine an optimized load distribution model for execution of the computing tasks within the set of clusters. The embodiment may include implementing the optimized load distribution model.

Abstract: A method, computer system, and a computer program product for process optimization is provided. The present invention may include analyzing a business process model comprised of one or more activities. The present invention may include extracting one or more key phrases from one or more event logs, wherein the one or more event logs are based on the business process model. The present invention may include determining a corresponding activity for the one or more extracted key phrases. The present invention may include generating an enriched business process model based on the business process model and one or more derived activities.

Abstract: Aspects of the invention include selecting an activity as a selected activity. A method includes designating a subset of the set of activities as classes, collecting a log of inputs and outputs of each encountered activity as a data point each time the process is implemented, and extracting features from each data point that is collected to generate a feature vector from each data point. A teacher model is initialized with a first data point and updated with each data point subsequent to the first data point. A student model is initialized with a set of data points including the first data point such that every one of the classes is encountered at least once. The student model is updated with the teacher model. A set of features is input to the student model to obtain a prediction of the outcome of the selected activity.

Abstract: One embodiment provides a method, including: receiving a technical diagram comprising a plurality of nodes and edges, wherein each edge connects two of the plurality of nodes; extracting, from the technical diagram, entities represented within the technical diagram, wherein the entities are extracted from the nodes and edges; creating groupings of entities from the extracted entities by grouping entities into groups based upon a logical relationship between the entities within a given group; generating, from the groupings, a visual representation of the technical diagram, wherein the visual representation comprises the groupings being represented as text and arranged based upon contextual relationships between the groupings; and providing a natural language summary of the technical diagram, wherein the providing comprises converting the visual representation into natural language text.