公开(公告)号：US20150081798A1

公开(公告)日：2015-03-19

申请号：US14489432

申请日：2014-09-17

Applicant: Electronics and Telecommunications Research Institute

Inventor： Yong-Joon LEE ,  Mal-Hee KIM ,  Hyo-Chan BANG

IPC: H04L12/24 ,  H04L29/08

CPC classification number: H04L41/0803 ,  H04L67/10 ,  H04L67/2809

Abstract: Disclosed herein is a process-based inter-thing collaboration apparatus and method in a Web of Things (WoT) environment, which can perform dynamic collaboration between things in a WoT environment. The presented apparatus includes an inter-thing collaboration design tool unit for designing an Inter-Thing Collaboration Process (ITCP) based on information of things including a device, a service, and a process, and an inter-thing collaboration management unit for dynamically configuring an inter-thing collaboration community based on context information of the things, and executing the ITCP designed by the inter-thing collaboration design tool unit.

Abstract translation: 这里公开了一种在物联网（WoT）环境中的基于过程的事物间协作装置和方法，其可以在WoT环境中进行动态协作。 所提出的装置包括用于基于包括设备，服务和过程的事物的信息来设计交互协作过程（ITCP）的事件间协作设计工具单元和用于动态配置的事件间协作管理单元 基于事物的上下文信息的事物间协作社区，以及执行由事件间协作设计工具单元设计的ITCP。

公开(公告)号：US20140207820A1

公开(公告)日：2014-07-24

申请号：US14049963

申请日：2013-10-09

Applicant: ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE

Inventor： Yong-Joon LEE

IPC: G06F17/30

CPC classification number: G06F17/30539

Abstract: Disclosed herein is a method for parallel mining of temporal relations in a large event file using a MapReduce model. In the method for parallel mining of temporal relations in a large even file according to the present invention, an event file is sorted based on customer identification (ID) and event time at which each event has occurred. A set of large event types satisfying a preset support or more is generated from the event file. The event file is converted into a large event sequence including the large event type set. The large event sequence is summarized and then a time interval data file is created. Candidate temporal relations are generated from the time interval data file, and frequent temporal relations satisfying a preset support or more are derived from the candidate temporal relations. A temporal relation rule is generated from the derived frequent temporal relations.

Abstract translation: 这里公开了一种使用MapReduce模型在大型事件文件中并行挖掘时间关系的方法。 在根据本发明的用于并行挖掘大型偶数文件中的时间关系的方法中，基于每个事件已经发生的客户识别（ID）和事件时间对事件文件进行排序。 从事件文件生成满足预设支持或更多的大型事件类型的集合。 将事件文件转换为大型事件序列，其中包含大型事件类型集。 总结大事件序列，然后创建时间间隔数据文件。 从时间间隔数据文件生成候选时间关系，并且从候选时间关系导出满足预设支持或更多的频繁时间关系。 从导出的频繁时间关系产生时间关系规则。