165 research outputs found
WaaS—Wisdom as a Service
No full textAn emerging hyper-world encompasses all human activities in a social-cyber-physical space. Its power derives from the Wisdom Web of Things (W2T) cycle, namely, “from things to data, information, knowledge, wisdom, services, humans, and then back to things.” The W2T cycle leads to a harmonious symbiosis among humans, computers and things, which can be constructed by large-scale converging of intelligent information technology applications with an open and interoperable architecture. The recent advances in cloud computing, the Internet/Web of Things, big data and other research fields have provided just such an open system architecture with resource sharing/services. The next step is therefore to develop an open and interoperable content architecture with intelligence sharing/services for the organization and transformation in the “data, information, knowledge and wisdom (DIKW)” hierarchy. This chapter introduces Wisdom as a Service (WaaS) as a content architecture based on the “paying only for what you use” IT business trend. The WaaS infrastructure, WaaS economics, and the main challenges in WaaS research and applications are discussed. A case study is described to demonstrate the usefulness and significance of WaaS. Relying on the clouds (cloud computing), things (Internet of Things) and big data, WaaS provides a practical approach to realize the W2T cycle in the hyper-world for the coming age of ubiquitous intelligent IT applications
A Social-Relationships-Based Service Recommendation System for SIoT Devices
No full textSocial Internet of Things comes as a new paradigm of Internet of Things to solve the problems of network discovery, navigability, and service composition. It aims to socialize the IoT devices and shape the interconnection between them into social interaction just like human beings. In IoT scenarios, a device can offer multiple services and different devices can offer the same services with different parameters and interest factors. The proliferation of offered services led to difficulties during service filtering and customization, this problem is known as services explosion. The selection of a suitable service that fits the requirements of the applications and devices is a challenging task. Several works have addressed service discovery, composition, and selection in IoT. However, these works did not emphasize on the fact that incorporating the users' social features can increase the efficiency of the recommended services and help us to offer context-aware services. In this article, we present a service recommendation system that takes advantage of the social relationships between devices' owners, where the recommendation is based on the different relationships between the service requester and service provider. Experimental results show, in the context of IoT, that incorporating the users' social relationships in service recommendation increases the accuracy and diversity of the offered services
Suitable Route Recommendation Inspired by Cognition
No full textWith the increasing popularity of mobile phones, large amounts of real and reliable mobile phone data are being generated every day. These mobile phone data represent the practical travel routes of users and imply the intelligence of them in selecting a suitable route. Usually, an experienced user knows which route is congested in a specified period of time but unblocked in another period of time. Moreover, a route used frequently and recently by a user is usually the suitable one to satisfy the user’s needs. ACT-R (Adaptive Control of Thought-Rational) is a computational cognitive architecture, which provides a good framework to understand the principles and mechanisms of information organization, retrieval and selection in human memory. In this chapter, we employ ACT-R to model the process of selecting a suitable route of users. We propose a cognition-inspired route recommendation method to mine the intelligence of users in selecting a suitable route, evaluate the suitability of the routes, and recommend an ordered list of routes for subscribers. Experiments show that it is effective and feasible to recommend the suitable routes inspired by cognition
A Monitoring System for the Safety of Building Structure Based on W2T Methodology
No full textWith the development of the Internet of things, monitoring systems for the safety of building structure (SBS) provide people with the important data about the main supporting points in the buildings. More and more data give the engineers an overload work problem, which can be solved by a systematic method making these monitoring systems more reliable, efficient and intelligent. Under the framework of the Wisdom Web of Things (W2T), we design a monitoring system for the SBS, by using the semantic technology. This system establishes a data cycle among the physical world (buildings), the social world (humans) and the cyber world (computers), and provides various services in the monitoring process to alleviate the engineers’ workload. In this system, the sensors which are connected via cable or wireless way, are used to monitor the different parameters of building structure. The semantic data can be obtained and represented by RDF to describe the meanings of sensor data, and can provide the application background for users. LarKC, a platform for scalable semantic data processing, is used for semantic querying about the data. Based on this uniform representation of data and semantic processing, intelligent services can be provided by the effective data analysis. This provides the possibility to integrate all of the monitoring systems for the safety of building structure in urban computing
N-dimensional Data Mining based Evolutionary Customer Behavior Modeling
No full text研究成果の概要 (和文) : 本研究は、消費者により良いサービスを提供するために、n次元データマイニングに基づいて消費者行動をモデル化するためのフレームワークを構築する。この研究の成果は以下の通りである：(1) データマイニングエンジンは、KIDモデルとデータマイニング計画メカニズムに基づいて設計と実装をした。(2) 情報/知識融合のためのアルゴリズムを提案と実装した。（3） データ駆動型消費者行動モデルはCyber-Iの概念に基づいて設計されており、成長と進化することができた。（4） 小売ビジネスサービスと都市交通管理は、提案されたモデル、メカニズム、およびフレームワークのためのテストベッドであった。研究成果の概要 (英文) : This research was proposed to build a framework for modeling customer behavior based on n-dimensional data mining so as to provide customers better services. This research\u27s achievements are as follows. (1) The data mining engine was designed and implemented based on KID model and backward chaining objectives oriented mining planning mechanism. (2) Fusion algorithms built in assimilation and instantiation processes for information/knowledge fusion were proposed and implemented. (3) The data driven customer behavior model was designed based on the concept of Cyber-I and is of the capability of growth and evolution with continuously incoming data. (4) A retail business service and city traffic management were as the testbed for our proposed models, mechanisms, and framework
n次元データマイニングによる進化型消費者行動モデリング
No full text研究分野：人工知能研究成果の概要 (和文) : 本研究は、消費者により良いサービスを提供するために、n次元データマイニングに基づいて消費者行動をモデル化するためのフレームワークを構築する。この研究の成果は以下の通りである：(1) データマイニングエンジンは、KIDモデルとデータマイニング計画メカニズムに基づいて設計と実装をした。(2) 情報/知識融合のためのアルゴリズムを提案と実装した。（3） データ駆動型消費者行動モデルはCyber-Iの概念に基づいて設計されており、成長と進化することができた。（4） 小売ビジネスサービスと都市交通管理は、提案されたモデル、メカニズム、およびフレームワークのためのテストベッドであった。研究成果の概要 (英文) : This research was proposed to build a framework for modeling customer behavior based on n-dimensional data mining so as to provide customers better services. This research's achievements are as follows. (1) The data mining engine was designed and implemented based on KID model and backward chaining objectives oriented mining planning mechanism. (2) Fusion algorithms built in assimilation and instantiation processes for information/knowledge fusion were proposed and implemented. (3) The data driven customer behavior model was designed based on the concept of Cyber-I and is of the capability of growth and evolution with continuously incoming data. (4) A retail business service and city traffic management were as the testbed for our proposed models, mechanisms, and framework
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