International Business Machines Corporation

Yun Jie Qiu

Min Gong

Junchi Yan

Yao Liang Chen

Sheng Huang

Xiao Min Xu

Ning Duan

Chen Wang

Yu Ying Wang

Xinlin Wang

Ju Wei Shi

Paul Sherwood Taylor

Xiao Yang

James Allen Reimer

Li Mei Jiao

Chao Hua Zhang

Chao Zhang

Wei Shan Dong

Wei Zhao

Ya Ming Zhang

Chao Xue

Xiao Yan Chen

Stephen Mingyu Chu

Jian Dong Ding

Shuo Zhou

Car roof hook

Technical solutions are described to implement a scalable write ahead log using a distributed file system. A general aspect includes a method for providing consistency among metadata replicas and content in an enterprise content management cluster. The method includes recording a transaction log entry in response to receiving a content modification request, the transaction log entry including a version identifier set to a first version value. The method also includes updating the transaction log entry to a second version value in response to successfully modifying content and one of a plurality of metadata replicas containing metadata corresponding to the request. The method also includes updating the transaction log entry to a third version value in response to successfully modifying each of the metadata replicas. The present document further describes examples of other aspects such as methods, computer products.

Scalable enterprise content management

The system, method, and computer program product described herein provide unified real-time rule analytics to users through the use of an analytics logic editor that allows a user to construct an analytic logic rule unit that may be used on both edge and cloud devices. The user may select a data source, transform, rule condition, and action using an interface of the analytics logic editor to construct an analytics logic rule unit that may be deployed to both edge and cloud devices in real-time without the need to separately program each device. The analytics logic rule unit may be installed and executed by the edge and cloud device in real-time.

Unified real time rule analytics using common programming model on both edge and cloud

Sofa

The present invention relates to a method and apparatus for genome compression and decompression. In one embodiment of the present invention, there is a method for genome compression, including: selecting from a reference database a reference genome that matches the genome; building an index based on positions of the reference genome's multiple segments in the reference genome; aligning the genome with the reference genome based on the multiple segments so as to identify difference data between the genome and the reference genome; and generating a compressed genome, the compressed genome including at least the index and the difference data. In other embodiments, there is provided an apparatus for genome compression. Further, there is a method and apparatus for decompressing the genome that has been compressed using the above method and apparatus.

Genome compression and decompression

Processing GPS drifting. A method and system for processing GPS drifting is included. The method includes: determining predicted error information on position correction of a device within a region; obtaining a GPS initial position and a corrected position of the device within the region; and determining GPS drifting of the region based on the predicted error information, the GPS initial position, and the corrected position of at least one device within the region. The method and system of the present application can effectively ameliorate GPS drifting issues.

Processing GPS drifting

A plurality of messages comprising a stream of sensed data is received from an Internet of Things (IoT) device. A plurality of rules is identified. Responsive to a received message of the plurality of messages, the plurality of rules are distributed into a rule index tree based upon a cost model which minimizes a cost for analyzing the plurality of rules to determine whether or not each of the plurality of rules can be applied to the received message. The rule index tree is used to identify a set of rules of the plurality of rules that can be applied to the received message. The set of rules is applied to the received message to generate an outgoing message.

Applying a plurality of rules to a multiplicity of streaming messages to perform intelligent data analytics

A method for determining an object referenced within a set of one or more informal online communications comprises: generating a knowledge graph for a company based at least on formal online communications, the knowledge graph comprising a plurality of node elements, and the knowledge graph further comprising, for each node element of the knowledge graph, a corresponding halo comprising one or more words which are temporally proximate to that node element within the formal online communications; for each node element of the knowledge graph which is determined to be present in a given informal online communication, detecting a halo comprising one or more words which are temporally proximate to that node element within the given informal online communication; and identifying which of the plurality of node elements has a corresponding halo within the knowledge graph most similar to the detected halo, wherein the identified node element is the referenced object.

Determining an object referenced within informal online communications

Location based on call detail record. The method includes: acquiring handover call detail record (HCDR) data and handover (HO) data corresponding to at least one cell transfer during a call; The HCDR data can include a start time, an end time, passed cells during the call; The HO data can include the HO time for each pair of adjacent cells among the passed cells during the call. The method can further include estimating the location of the subscriber based on the HCDR data and the HO data.

Location based on call detail record

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Shanghai, China

Yun Jie Qiu