-
公开(公告)号：US20220405487A1
公开(公告)日：2022-12-22
申请号：US17354171
申请日：2021-06-22
发明人： Manik Bhandari , Oktie Hassanzadeh , Mark David Feblowitz , Kavitha Srinivas , Shirin Sohrabi Araghi
摘要： A computer-implemented method is provided that includes accessing candidate text and a candidate pair including first and second phrases, substituting the first and second phrases into cause-effect patterns to generate variant sentences. An artificial intelligence model is leveraged to determine respective probabilities that the variant sentences are inferred from the candidate text, calculate a statistical measure of the respective probabilities, and assess the calculated statistical measure to ascertain whether the first and second phrases possess a causal relationship or non-causal relationship to one another. A knowledge base including one or more pairs of cause-effect phrase pairs is populated with the first and second phrases possessing the causal relationship. A computer system and a computer program product are also provided.
-
公开(公告)号：US20220300852A1
公开(公告)日：2022-09-22
申请号：US17207805
申请日：2021-03-22
发明人： Octavian Udrea , Shirin Sohrabi Araghi , Michael Katz , Mark David Feblowitz , Kavitha Srinivas , Oktie Hassanzadeh
IPC分类号： G06N20/00 , G06F40/289
摘要： Embodiments are provided that relate to a computer system, a computer program product, and a computer-implemented method for automating scenario planning. Embodiments involve machine learning (ML) and an artificial intelligence (AI) planner to capture a general scenario planning (GSP) problem and provide a solution to the GSP problem in the form of trajectories.
-
公开(公告)号：US11204960B2
公开(公告)日：2021-12-21
申请号：US16399535
申请日：2019-04-30
IPC分类号： G06F16/901 , G06F16/36
摘要： A method, system, and recording medium for knowledge graph augmentation using data based on a statistical analysis of attributes in the data, including a ranking device configured to rank semantically similar input data elements to create a ranked list of attributes to augment an input of structured data and populate with a data string corresponding to the instances, where the ranking device further combines a set of filters to refine the ranked list of attributes, the set of filters including a first filter according to column ranges of columns, a second filter according to a column uniqueness of the columns, a third filter according to a type of data in a column of the columns, and a fourth filter according to a distribution of values in the columns.
-
公开(公告)号：US11188828B2
公开(公告)日：2021-11-30
申请号：US15420971
申请日：2017-01-31
发明人： Gonzalo Ignacio Diaz Caceres , Achille Belly Fokoue-Nkoutche , Mohammad Sadoghi Hamedani , Oktie Hassanzadeh , Mariano Rodriguez Muro
IPC分类号： G06N5/02
摘要： A semantic embedding model using geometrical set-centric approach to capture both ABox and TBox representational models is disclosed. The model transforms a semantic-rich knowledge graph into a set of overlapping, disjoint, and/or subsumed n-dimensional spheres that captures and represents semantics embedded in the knowledge graph.
-
公开(公告)号：US20210216904A1
公开(公告)日：2021-07-15
申请号：US16741084
申请日：2020-01-13
发明人： Udayan Khurana , Sainyam Galhotra , Oktie Hassanzadeh , Kavitha Srinivas , Horst Cornelius Samulowitz
摘要： Embodiments relate to a system, program product, and method for employing feature engineering to improve classifier performance. A first machine learning (ML) model with a first learning program is selected. The first selected ML model is operatively associated with a first structured dataset. First features in the first dataset directed at performance of the selected ML model are identified. A second structured dataset is assessed with respect to the identified features in the first dataset, and new features in the second dataset are identified, where the new feature is semantically related to the identified features in the first dataset. The first dataset is dynamically augmented with the identified new features in the second dataset. The dynamically augmented first dataset is applied to the selected ML model to subject an embedded learning algorithm of the selected ML model to training using the augmented first dataset.
-
公开(公告)号：US10783997B2
公开(公告)日：2020-09-22
申请号：US15248734
申请日：2016-08-26
发明人： Achille B. Fokoue-Nkoutche , Oktie Hassanzadeh , Mohammad S. Hamedani , Meinolf Sellmann , Ping Zhang
摘要： Embodiments include method, systems and computer program products for predicting adverse drug events on a computational system. Aspects include receiving a personalized data set including a plurality of real-time drug doses for a first drug or drug combination and a plurality of corresponding real-time adverse drug reaction tolerance data for the first drug or drug combination for a patient. Aspects also include receiving known drug data for a candidate drug or drug pair. Aspects also include calculating, based upon the known drug data and the personalized data set, a predicted adverse drug reaction tolerance for the candidate drug or drug pair at a candidate dosage, wherein the predicted adverse drug reaction tolerance is personalized to the patient.
-
公开(公告)号：US10599732B2
公开(公告)日：2020-03-24
申请号：US15440372
申请日：2017-02-23
IPC分类号： G06F16/25 , G06F16/9535 , G06F16/27 , G06F16/2457
摘要： Data records are linked across a plurality of datasets. Each dataset contains at least one data record, and each data record is associated with an entity and includes one or more attributes of that entity and a value for each attribute. Values associated with attributes are compared across datasets, and matching attributes having values that satisfy a predetermined similarity threshold are identified. In addition, linkage points between pairs of datasets are identified. Each linkage point links one or more pairs of data records. Each data record in the pair of data records is contained in one of a given pair of datasets, and each pair of data records is associated with a common entity having matching attributes in the given pair of datasets. Data records associated with the common entities are linked across datasets using the identified linkage points.
-
38.发明授权公开(公告)号：US10380187B2
公开(公告)日：2019-08-13
申请号：US14927712
申请日：2015-10-30
IPC分类号： G06F16/36 , G06F16/901
摘要： A method, system, and recording medium for knowledge graph augmentation using data based on a statistical analysis of attributes in the data, including mapping classes, attributes, and instances of the classes of the data, indexing semantically similar input data elements based on the mapped data using at least one of a label-based analysis, a content-based analysis, and an attribute-based clustering, and ranking the semantically similar input data elements to create a ranked list.
-
公开(公告)号：US20180137404A1
公开(公告)日：2018-05-17
申请号：US15351897
申请日：2016-11-15
发明人： Nicolas R. Fauceglia , Alfio M. Gliozzo , Oktie Hassanzadeh , Thien H. Nguyen , Mariano Rodriguez Muro , Mohammad Sadoghi Hamedani
CPC分类号： G06N3/0454 , G06N3/0445 , G06N3/084
摘要： A system, method and computer program product for disambiguating one or more entity mentions in one or more documents. The method facilitates the simultaneous linking entity mentions in a document based on convolution neural networks and recurrent neural networks that model both the local and global features for entity linking. The framework uses the capacity of convolution neural networks to induce the underlying representations for local contexts and the advantage of recurrent neural networks to adaptively compress variable length sequences of predictions for global constraints. The RNN functions to accumulate information about the previous entity mentions and/or target entities, and provide them as the global constraints for the linking process of a current entity mention.
-
公开(公告)号：US09740978B2
公开(公告)日：2017-08-22
申请号：US14525790
申请日：2014-10-28
CPC分类号： G06N5/022 , G06F17/30598 , G06N99/005
摘要： A mechanism is provided for identifying a set of top-m clusters from a set of top-k plans. A planning problem and an integer value k indicating a number of top plans to be identified are received. A set of top-k plans are generated with at most size k, where the set of top-k plans is with respect to a given measure of plan quality. Each plan in the set of top-k plans is clustered based on a similarity between plans such that each cluster contains similar plans and each plan is grouped only into one cluster thereby forming the set of top-m clusters. A representative plan from each top-m cluster is presented to the user.
-
-
-
-
-
-
-
-
-
搜索结果
43 条记录 (耗时 0.032 秒)
