InfoSleuth

Bayardo, Roberto J.; Bohrer, W.; Brice, Richard; Cichocki, Andrzej; Fowler, Jerry; Helal, Abdelsalam; Kashyap, Vipul; Ksiezyk, Tomasz; Martín, Guiomar; Nodine, Marian H.; Rashid, Md. Mamunur; Rusinkiewicz, Marek; Shea, R.; Unnikrishnan, C.; Unruh, Amy; Woelk, Darrell

doi:10.1145/253260.253294

Cited by 221 publications

(3 citation statements)

References 14 publications

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“…Research has provided many automated methods for ontology creation. The first method The primary motivation behind InfoSleuth is to exploit technologies that retrieve and process information in dynamic data sources (Bayardo et al, 1997). Another focus of this system was based on semantics and creating an architecture where the computer could understand the concepts behind the data.…”

Section: Related Workmentioning

confidence: 99%

Integrating Knowledge Sources

Wimmer

Yoon

Rada

2013

International Journal of Knowledge Management

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There has been a plethora of research in the area of knowledge portals, knowledge warehouses, ontologies, ontology creation and mapping, as well as the automatic creation and mapping of ontologies. While research exists in each respective area there is a lack of conceptual models that will integrate ontologies as a tool for disparate data source integration into knowledge portals or enterprise knowledge warehouses. The purpose of this work is to discuss different tools that have been developed in academic research and provide a conceptual model of how to implement these tools in relation to knowledge portals and warehouses.

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Section: Related Workmentioning

confidence: 99%

Integrating Knowledge Sources

Wimmer

Yoon

Rada

2013

International Journal of Knowledge Management

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“…Industrial process control in the monitoring of bioreactor, and military applications are another domain of applications. For detail discussion on the applications of biosensor see [52].…”

Section: Biosensorsmentioning

confidence: 99%

Partially Observable Markov Decision Processes (POMDPs) and Wireless Body Area Networks (WBAN): A Survey

2013

KSII TIIS

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Wireless body area network (WBAN) is a promising candidate for future health monitoring system. Nevertheless, the path to mature solutions is still facing a lot of challenges that need to be overcome. Energy efficient scheduling is one of these challenges given the scarcity of available energy of biosensors and the lack of portability. Therefore, researchers from academia, industry and health sectors are working together to realize practical solutions for these challenges. The main difficulty in WBAN is the uncertainty in the state of the monitored system. Intelligent learning approaches such as a Markov Decision Process (MDP) were proposed to tackle this issue. A Markov Decision Process (MDP) is a form of Markov Chain in which the transition matrix depends on the action taken by the decision maker (agent) at each time step. The agent receives a reward, which depends on the action and the state. The goal is to find a function, called a policy, which specifies which action to take in each state, so as to maximize some utility functions (e.g., the mean or expected discounted sum) of the sequence of rewards. A partially Observable Markov Decision Processes (POMDP) is a generalization of Markov decision processes that allows for the incomplete information regarding the state of the system. In this case, the state is not visible to the agent. This has many applications in operations research and artificial intelligence. Due to incomplete knowledge of the system, this uncertainty makes formulating and solving POMDP models mathematically complex and computationally expensive. Limited progress has been made in terms of applying POMPD to real applications. In this paper, we surveyed the existing methods and algorithms for solving POMDP in the general domain and in particular in Wireless body area network (WBAN). In addition, the papers discussed recent real implementation of POMDP on practical problems of WBAN. We believe that this work will provide valuable insights for the newcomers who would like to pursue related research in the domain of WBAN.

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“…The InfoSleuth project (Bayardo, Bohrer, Brice, Cichocki, Fowler, & Helal, 1997) (successor of the Carnot project [Woelk, Cannata, Huhns, Shen, & Tomlinson, 1993]) presents an approach for information retrieval and processing in a dynamic environment such as the Web. Its functionalities include gathering information from databases and semi-structured sources distributed across the Internet, performing polling and notification for monitoring changes in data, and analyzing gathered information.…”

Section: Related Workmentioning

confidence: 99%

A Scalable Middleware for Web Databases

Bouguettaya

Malik

Rezgui

et al. 2006

Journal of Database Management

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The emergence of Web databases has introduced new challenges related to their organization, access, integration, and interoperability. New approaches and techniques are needed to provide across-the-board transparency for accessing and manipulating Web databases irrespective of their data models, platforms, locations, or systems. In meeting these needs, it is necessary to build a middleware infrastructure to support flexible tools for information space organization, communication facilities, information discovery, content description, and assembly of data from heterogeneous sources. In this paper, we describe a scalable middleware for efficient data and application access that we have built using the available technologies. The resulting system is called WebFINDIT. It is a scalable and uniform infrastructure for locating and accessing heterogeneous and autonomous databases and applications.

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InfoSleuth

Cited by 221 publications

References 14 publications

Integrating Knowledge Sources

Integrating Knowledge Sources

Partially Observable Markov Decision Processes (POMDPs) and Wireless Body Area Networks (WBAN): A Survey

A Scalable Middleware for Web Databases

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