Microsoft Technology Licensing, LLC

Future Wei Technologies, Inc.

Luhui Hu

Navendu Jain

Rahul Potharaju

Vitaly Voloshin

Liyuan Zhang

Mingshi Wang

Hui Zang

Ziang Hu

Joseph K W Chan

Joseph Kw Chan

Laura M Cruz

Joseph KW Chan

An apparatus and method are provided for review-based machine learning. Included are a non-transitory memory storing instructions and one or more processors in communication with the non-transitory memory. The one or more processors execute the instructions to receive first data, generate a plurality of first features based on the first data, and identify a first set of labels for the first data. A first model is trained using the first features and the first set of labels. The first model is reviewed to generate a second model, by receiving a second set of labels for the first data, and reusing the first features with the second set of labels in connection with training the second model.

Review machine learning system

An apparatus and method are provided for a managed knowledge network platform (KNP). Model dissimilarity values for model pairs are obtained, each model pair including a first model of a plurality of models in a KNP and a different model in the plurality of models. Path lengths between a first model node of a plurality of model nodes in the KNP and each one of other model nodes are computed, where the first model node represents the first model and the first model node is connected to a first user node of a plurality of user nodes representing users of the KNP. At least one of the different models is selected based on the model dissimilarity values and the path lengths. A recommendation that includes the at least one model is generated for a first user represented by the first user node.

Knowledge network platform

Disclosed herein is a system and method for generating an enhanced index for documents contained in a knowledge base. Documents or configuration snapshots are tokenized and then passed through a number of filters. The filters modify the token stream to generate an enhanced token stream for the document by removing words from the stream and adding domain level knowledge to the tokens in the stream. The token stream is then added to the index for the document so that searches can be completed against the knowledge base when searches are generated from configuration snapshots or from inputted search queries.

Building features and indexing for knowledge-based matching

A performance-based storage service level agreement (SLA) can be established that specifies one or more storage performance parameters. A storage allocation process can include receiving a request for a storage SLA that specifies one or more storage performance parameters, determining, for a virtual machine (VM) and based at least in part on the one or more storage performance parameters in the storage SLA: (i) a storage location among a set of candidate storage locations, and (ii) an amount of storage to allocate. The amount of storage can then be allocated at the storage location for the VM to use in making storage requests. Runtime enforcement of the storage SLA can utilize a scheduling mechanism that buffers individual storage requests into different queues that are used for meeting one or more storage performance requirements specified in storage SLA.

Cloud storage platform providing performance-based service level agreements

A system, computer readable medium, and method are provided for a resource management in a cloud architecture. The method includes the steps of collecting a first time stamped data (TSD), and a second TSD, and generating a prediction model based on the first TSD and the second TSD. The method further includes collecting a third TSD, and predicting a fourth TSD based on the prediction model and the third TSD. With more data are obtained via the prediction, the resource management is more efficient and accurate.

Quasi-agentless cloud resource management

Disclosed herein is a system and method for searching or processing queries for searching for documents contained in a domain specific knowledge base. The system takes a query and generates from the query a modified version of the query by passing the query through one or more filters in a query processor. The query processor adds or removes terms from the query. The query processor can add or recognize that two words that appear to be separate words actually identify a specific software entity or can determine that a number appearing in a query is not just a number but refers to a specific version or a number relevant to the specific problem.

Query techniques and ranking results for knowledge-based matching

Disclosed herein is a system and method for taking a snapshot or input from a source and identifying appropriate documents in a knowledge base that are applicable to the input. The system identifies documents that are applicable to the query by identifying comparative features/statements found in the natural language text documents and evaluating those comparative features with the conditions of the input. When the conditions of the comparative features evaluate with the input conditions the document is considered a match. The system processes the documents through a value type filter to understand the mathematical equivalent of the comparative feature and uses this mathematical equivalent in the evaluation of the document and input.

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Bellevue, WA, United States of America

Luhui Hu