Bigobject Inc.

Ebizprise Inc.

Certis Cisco Security Pte Ltd

Wenwey Hseush

Yi-Cheng Huang

Michael Chih Huong Fong

Yu-Chun Lai

Shih-Chang Hsu

Yi-Chen Hsu

Ya Chu Chen

Hsien Hui Pan

Shyy San Foo

Tyng-Rong Roan

Hsin Hua Cheng

A data exploration apparatus is interactively operated by a user conducting a mission including explorations, T, T, . . . , T, to cross-analyze tabular datasets, D, D, . . . , D, respectively. The apparatus starts with n=1 in response to the initiation of the mission to launch an exploration T, enable the display device to display a working scene Sfor the exploration T, perform a sequence of operations on the working dataset Wcorresponding to the exploration T, and then refresh the working scene S. In response a GUI action, an interrupt operation is performed to escape from the exploration T, launch an exploration Twith the target of interest TOIto explore the related tabular dataset D, and enable the display device to display a working scene Sfor the exploration T.

Data exploration apparatus, cascading data exploration method, and non-transitory computer readable storage medium thereof

The bionic computing system includes a perception subsystem, an attention subsystem, and a temporal-spatial awareness subsystem. The perception subsystem has several perceptual devices for detecting objects from sequences of sensory data and generating an object record for each object. The attention subsystem adjusts the object records by re-identifying the tracking identities across sensory devices, generates several object associations, generate several location associations, and generates several motion implications. The temporal-spatial awareness subsystem organizes and retains the object records in a working memory space. The perception subsystem identifies several basic events from each sensory datum of the same perceptual device, the attention subsystem identifies an episodic event by determining that a portion of the basic events from the same sensory device within a temporal window conform to a pattern, and the temporal-spatial awareness subsystem identifies a complex event according the detected episodic event and the object records in the working memory space.

Bionic computing system and cloud system thereof

A federated data exploration system includes a first and a second interoperable data exploration apparatuses. The first interoperable data exploration apparatus executes a data process engine and has a first data object. The data process engine enables a display screen to display a visualization user interface, which includes a first and second display areas respectively for the first and second data object. The second data object belongs to the second interoperable data exploration apparatus. The data process engine explores the second data object by issuing a sequence of queries in response to a sequence of operations on the second display area to narrow down a target of interest. The data process engine receives a first set of identifiers corresponding to the target of interest from the second data object and produces a target dataset by querying the first data object according to the first set of identifiers.

Federated data exploration systems and interoperable data exploration apparatuses

Data processing apparatus, method, and non-transitory tangible machine-readable medium thereof for recursively structured data are provided. The data processing apparatus accesses a piece of recursively structured data having a Location Independent Structure and arranges the piece of recursively structured data in a one-dimensional memory space according to LIS:=e&#x2218;e&#x2218; . . . &#x2218;e&#x2218;LIS&#x2218;LIS&#x2218; . . . &#x2218;LIS. The notation erepresents an element of the piece of recursively structured data. The notation LISrepresents a sub-LIS of the recursively structured data and corresponds to the element e. The operator '&#x2218;' indicates 'contiguous to' in the one-dimensional memory space. When the elements in all depths are of the element size and the LIS sizes of the sub-LISs within the same depth are the same, the piece of recursively structured data is a complete LIS.

Data processing apparatus, method, and non-transitory tangible machine-readable medium thereof for recursively structured data

Data processing apparatuses and data processing methods are provided. The data processing apparatus includes a storage unit, an interface, and a processor. The storage unit stores a first key-value set including a plurality of first key-value pairs. Each of the first key-value pairs has a first key and a first value. The interface receives an instruction regarding a set operation and a function. The processor generates a plurality of second keys by applying the set operation to the first keys. Each of the second keys includes at least one of the first keys. The processor generates a second value for each of the second keys by applying the function to at least one datum corresponding to the at least one first key comprised in the second key. Each second key and the corresponding second value form a second key-value pair and the second key-value pairs form a second key-value set.

Key-value pairs data processing apparatus and method

A large-scale data processing apparatus, method, and non-transitory tangible machine-readable medium are provided. The large-scale data processing apparatus includes a storage unit, an interface, and a processor. The storage unit is stored with a measure table comprising at least one measure. Each of the at least one measure includes a value corresponding to a key attribute and a piece of data corresponding to a data field. The interface is configured to receive a level order of N attributes, wherein N is a positive integer and the N attributes comprise the key attribute. The processor is configured to create a measure tree object for the measure table by following the level order so that the measure tree object has N levels corresponding to the N attributes in a one-to-one fashion.

Large-scale data processing apparatus, method, and non-transitory tangible machine-readable medium thereof

A large-scale data processing system, a large-scale data processing method, and a non-transitory tangible machine-readable medium are provided. The large-scale data processing system comprises an interface and a processor. The interface accesses a multi-dimensional data model, wherein the multi-dimensional data model comprises a plurality of dimensions, the dimensions form a multi-dimensional space of measures, each dimension is a single space comprising a plurality of members with a common set of attributes, and each measure is a data element organized and accessible through the multi-dimensional space of the cross-product of all dimensions. The processor builds at least one Tree Object (TO), wherein the TO is derived by converting the multi-dimensional data model into an N-level tree data structure according to a level order of N attributes, each tree node in the TO meets all conditions of attributes for all ancestor nodes, and N is a positive integer.

Large-scale data processing system, method, and non-transitory tangible machine-readable medium thereof

An apparatus and method for realizing big data into a Big Object and a non-transitory tangible machine-readable medium are provided. The apparatus comprises an interface and a processor. The interface is configured to access big data stored in a storage device. The processor is configured to create the Big Object from the big data using memory mapped files. The processor further lays out a content of the Big Object, wherein the content comprises a meta information section, a tree section, and a data section. The processor further lays out a content of the tree section by using LIS and describes a structure of the Big Object in the meta information section.

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Taipei, Taiwan

Wenwey Hseush