公开(公告)号：US10331787B2

公开(公告)日：2019-06-25

申请号：US15092020

申请日：2016-04-06

Applicant: Omniscience Corporation

Inventor： Manu Shukla

IPC: G06F17/27 ,  G06F17/30 ,  H04L12/58 ,  G06F16/34

Abstract: Aspects of the present disclosure relate to a distributed storytelling framework. A server receives an adjacency list comprising a set of nodes linked together by edges. The server converts the adjacency list to a set of generated storylines, each storyline being represented as a key-value pair. A key represents a first node and a value represents a second node linked to the first node by an edge. The server combines first and second storylines, of the set of generated storylines, to generate an additional storyline in response to a value from a first storyline matching a key from a second storyline. The additional storyline includes a single key and multiple values, and is added to the set of generated storylines. The server repeats combining storylines, of the set of generated storylines, to generate additional storylines. The server provides an output corresponding to at least one of the generated storylines.

公开(公告)号：US10035593B2

公开(公告)日：2018-07-31

申请号：US15092004

申请日：2016-04-06

Applicant: Omniscience Corporation

Inventor： Manu Shukla

IPC: G01C23/00 ,  B64C39/02 ,  G08G5/00

CPC classification number: B64C39/024 ,  B64C2201/12 ,  B64C2201/141 ,  G08G5/0013 ,  G08G5/0026 ,  G08G5/0034 ,  G08G5/006 ,  G08G5/0069

Abstract: Drones have become ubiquitous in performing risky and labor intensive areal tasks cheaply and safely. To allow them to be autonomous, their flight plan needs to be pre-built for them. Existing works do not precalculate flight paths but instead focus on navigation through camera based image processing techniques, genetic or geometric algorithms to guide the drone during flight. That makes flight navigation complex and risky. We present automated flight plan builder DIFPL which pre-builds flight plans for drones to survey a large area. The flight plans are built for subregions and fed into drones which allow them to navigate autonomously. DIFPL employs distributed paradigm on Hadoop MapReduce framework. Distribution is achieved by processing sections or subregions in parallel. Experiments performed with network and elevation datasets validate the efficiency of DIFPL in building optimal flight plans.

公开(公告)号：US11497988B2

公开(公告)日：2022-11-15

申请号：US15253008

申请日：2016-08-31

Applicant: Omniscience Corporation

Inventor： Manu Shukla

IPC: G06N20/00 ,  A63F13/25 ,  G06N20/10 ,  H04L51/52 ,  H04L51/222 ,  H04L67/131 ,  H04L67/50

Abstract: Aspects of the subject technology include an event processing and prospect identifying platform. It accepts as input a set of storylines (a sequence of entities and their relationships) and processes them as follows: (1) uses different algorithms (LDA, SVM, information gain, rule sets) to identify themes from storylines; (2) identifies top locations and times in storylines and combines with themes to generate events that are meaningful in a specific scenario for categorizing storylines; and (3) extracts top prospects as people and organizations from data elements contained in storylines. The output comprises sets of events in different categories and storylines under them along with top prospects identified. Aspects use in-memory distributed processing that scales to high data volumes and categorizes generated storylines in near real-time.

公开(公告)号：US20170056764A1

公开(公告)日：2017-03-02

申请号：US15253008

申请日：2016-08-31

Applicant: Omniscience Corporation

Inventor： Manu Shukla

IPC: A63F13/25 ,  H04L29/08 ,  G06N99/00

CPC classification number: A63F13/25 ,  A63F2300/8082 ,  G06N20/00 ,  H04L51/20 ,  H04L51/32 ,  H04L67/22 ,  H04L67/38

Abstract: Aspects of the subject technology include an event processing and prospect identifying platform. It accepts as input a set of storylines (a sequence of entities and their relationships) and processes them as follows: (1) uses different algorithms (LDA, SVM, information gain, rule sets) to identify themes from storylines; (2) identifies top locations and times in storylines and combines with themes to generate events that are meaningful in a specific scenario for categorizing storylines; and (3) extracts top prospects as people and organizations from data elements contained in storylines. The output comprises sets of events in different categories and storylines under them along with top prospects identified. Aspects use in-memory distributed processing that scales to high data volumes and categorizes generated storylines in near real-time.

Abstract translation: 主题技术方面包括事件处理和潜在客户识别平台。 它接受一组故事情节（一系列实体及其关系），并将其处理如下：（1）使用不同的算法（LDA，SVM，信息增益，规则集）来识别故事情节中的主题; （2）识别故事情节中的顶级位置和时间，并与主题相结合，以生成在特定场景中有意义的事件，用于分类故事情节; 和（3）从故事情节中包含的数据元素中提取人物和组织的顶级前景。 产出包括不同类别的事件集和其下的故事情节以及确定的顶级前景。 方面使用内存分布式处理，可扩展到高数据量，并将近似实时的故事情节分类。