PHIRST: A distributed architecture for P2P information retrieval

Recent progress in peer to peer (P2P) search algorithms has presented viable structured and unstructured approaches for full-text search. We posit that these existing approaches are each best suited for different types of queries. We present PHIRST, the first system to facilitate effective full-text search within P2P databases. PHIRST works by effectively leveraging between the relative strengths of these approaches. Similar to structured approaches, agents first publish terms within their stored documents. However, frequent terms are quickly identified and not exhaustively stored, resulting in a significant reduction in the system's storage requirements. During query lookup, agents use unstructured search to compensate for the lack of fully published terms. Additionally, they explicitly weigh between the costs involved in structured and unstructured approaches, allowing for a significant reduction in query costs. Finally, we address how node failures can be effectively addressed through storing multiple copies of selected data. We evaluated the effectiveness of our approach using both real-world and artificial queries. We found that in most situations our approach yields near perfect recall. We discuss the limitations of our system, as well as possible compensatory strategies.     

A timed mobile agent planning approach for distributed information retrieval in dynamic network environments

The number of mobile agents and total execution time are two factors used to represent the system overhead that must be considered as part of mobile agent planning (MAP) for distributed information retrieval. In addition to these two factors, the time constraints at the nodes of an information repository must also be taken into account when attempting to improve the quality of information retrieval. In previous studies, MAP approaches could not consider dynamic network conditions, e.g., variable network bandwidth and disconnection, such as are found in peer-to-peer (P2P) computing. For better performance, mobile agents that are more sensitive to network conditions must be used. In this paper, we propose a new MAP approach that we have named Timed Mobile Agent Planning (Tmap). The proposed approach minimizes the number of mobile agents and total execution time while keeping the turnaround time to a minimum, even if some nodes have a time constraint. It also considers dynamic network conditions to reflect the dynamic network condition more accurately. Moreover, we incorporate a security and fault-tolerance mechanism into the planning approach to better adapt it to real network environments.     

基于本体的智能化知识检索模型

该文简要从信息检索的一般过程出发,分析了基于本体的知识检索的工作原理以及一般模型;着重对现有的知识检索智能性不足的缺陷,引入IGA、多Agent等技术,设计了一个基于本体的智能化知识检索模型。     

基于多Agent的中文智能检索模型

Internet已经成为全球信息系统，如何智能地在这个系统中对信息进行检索一直是热点问题。分布式人工智能的发展和Agent在各个领域的广泛应用，为这个问题的解决提供了技犬上的支持。提出了一种基于多Agent的搜索模型，此模型可以根据不同需求进行信息的智能检索。     

A multi-agent architecture for supporting distributed normality-based intelligent surveillance

Intelligent surveillance involves the use of AI techniques to monitor environments whose analysis is becoming more and more complex because of the large number of sensors used and the need of monitoring multiple events of interest simultaneously. Most of the current surveillance systems provide solutions for particular problems but still suffer from lack of flexibility and scalability when they are used on different or related surveillance problems. To overcome this limitation, two aspects should be addressed: a knowledge-based surveillance model flexible enough to deal with different events of interest and an architecture that gives support to this model when deploying the surveillance system within a particular scenario. This paper discusses the architecture devised to deploy intelligent surveillance systems by means of a set of autonomous agents that are responsible for the management of different surveillance tasks and for cooperating to monitor complex environments. This multi-agent architecture is inspired by a normality-based formal model used to define the knowledge needed to analyze general-purpose surveillance concepts. We use the architecture to deploy a surveillance system to monitor an urban traffic scenario.     

An intelligent agent-based architecture for strategic information system applications

Strategic information systems (SIS) focus on the use of information system (IS) and information technology (IT) in the strategic management process in business organizations. The emphasis is on the strategic view of IS and IT and their impact on organizational strategy. Increased competition and advances in information technologies push for considerable structural changes in SIS. Agents, as autonomous entities which either work on their own or cooperate with others, and agent architectures have enormous potentials to be applied in such critical systems. In this article, first we investigate the very fundamental concepts of strategic information systems and intelligent agent technology. Then, the discussion continues on the specification of the characteristics and implementation issues of a typical SIS. Afterwards, we make use of these concepts and integrate them into a state-of-the-art, intelligent architecture for strategic information systems, called intelligent agent-based SIS. This is a comprehensive framework for a SIS in IT era which may be put into practice by a team of professionals in the near future. The graphical representation of this model is intended to help the reader understand the concept much better. After explaining the suggested model in full details, we introduce some support agents and specify their corresponding roles in an intelligent agent-based SIS architecture. Discussions and concluding remarks regarding the proposed system are provided at the end of the paper.     

Applying an intelligent notification mechanism to blogging systems utilizing a genetic-based information retrieval approach

Blogging systems have received a lot of attention in recent years due to their wide spectrum of applications. The comment function is a significant part of a blog application, which can be used to gather the readers’ feedback and produce social interactions with them. However, most of the existing blogging systems only provide simple comment notification mechanisms for bloggers. Since a popular blog may receive thousands of comments in a short period of time, it is almost impossible for the notification mechanism to inform the blogger about every comment, even meaningful ones. In this paper, we propose a Two-stage Intelligent Notification Mechanism (TINM) for blogging systems to carry out intelligent comment notification, so that the blogger only receives meaningful comments. To reduce the computation cost in the keyword retrieval, a Genetic-based Information Retrieval Approach (GIRA) was designed. Experimental results show that the proposed approach reduces the computation cost during keyword retrieval, and still leads to near optimal results.     

Agents for information retrieval: Issues of mobility and coordination

This paper focuses on agent-based applications for information retrieval on the Web, by specifically analysing mobility and coordination issues. On the one hand, mobile agents well suit the requirements of information retrieval in the new dynamic scenario derived from the Internet. This is due to their capability of moving to the place where the information is stored – therefore saving bandwidth – and to their robustness in the presence of unreliable connections. On the other hand, the search for information by several mobile active agents calls for suitable models to rule the interactions among agents and between agents and execution environments. The paper surveys different coordination approaches and evaluates their impact in information retrieval applications based on mobile agents. The survey outlines the advantages of uncoupled coordination models and points out the suitability of a coordination model based on reactive and programmable tuple spaces: they may increase the safety and the security of the environment while simplifying the task of programming distributed mobile agent applications.     

Consensus-based evaluation framework for distributed information retrieval systems

Multi-agent systems have been attacking the challenges of information retrieval tasks on distributed environment. In this paper, we propose a consensus choice selection method based framework to evaluate the performance of cooperative information retrieval tasks of the multiple agents. Thereby, two well-known measurements, precision and recall, are extended to handle consensual closeness (i.e., local and global consensus) between the sets of retrieved results. We show that in a motivating example the proposed criteria are prone to solve the rigidity problem of classical precision and recall. More importantly, the retrieved results can be ranked with respect to the consensual score, and the ranking mechanism has been verified to be more reasonable.

Collection-integral source selection for uncooperative distributed information retrieval environments

We propose a new integral-based source selection algorithm for uncooperative distributed information retrieval environments. The algorithm functions by modeling each source as a plot, using the relevance score and the intra-collection position of its sampled documents in reference to a centralized sample index. Based on the above modeling, the algorithm locates the collections that contain the most relevant documents. A number of transformations are applied to the original plot, in order to reward collections that have higher scoring documents and dampen the effect of collections returning an excessive number of documents. The family of linear interpolant functions that pass through the points of the modified plot is computed for each available source and the area that they cover in the rank-relevance space is calculated. Information sources are ranked based on the area that they cover. Based on this novel metric for collection relevance, the algorithm is tested in a variety of testbeds in both recall and precision oriented settings and its performance is found to be better or at least equal to previous state-of-the-art approaches, overall constituting a very effective and robust solution.     

A content-search information retrieval process based on conceptual graphs

An intelligent information retrieval system is presented in this paper. In our approach, which complies with the logical view of information retrieval, queries, document contents and other knowledge are represented by expressions in a knowledge representation language based on the conceptual graphs introduced by Sowa. In order to take the intrinsic vagueness of information retrieval into account, i.e. to search documents imprecisely and incompletely represented in order to answer a vague query, different kinds of probabilistic logic are often used. The search process described in this paper uses graph transformations instead of probabilistic notions. This paper is focused on the content-based retrieval process, and the cognitive facet of information retrieval is not directly addressed. However, our approach, involving the use of a knowledge representation language for representing data and a search process based on a combinatorial implementation of van Rijsbergen’s logical uncertainty principle, also allows the representation of retrieval situations. Hence, we believe that it could be implemented at the core of an operational information retrieval system. Two applications, one dealing with academic libraries and the other concerning audiovisual documents, are briefly presented.     

A communication model based on the 2-tuple fuzzy linguistic representation for a distributed intelligent agent system on Internet

 Internet users are assisted by means of distributed intelligent agents in the information gathering process to find the fittest information to their needs. In this paper we present a distributed intelligent agent model where the communication of the evaluation of the retrieved information among the agents is carried out by using linguistic operators based on the 2-tuple fuzzy linguistic representation as a way to endow the retrieval process with a higher flexibility, uniformity and precision. The 2-tuple fuzzy linguistic representation model allows to make processes of computing with words without loss of information.     

Challenges, approaches and architecture for distributed process integration in heterogeneous environments

Integration and coordination of distributed processes remains a central challenge of construction information technology research. Extant technologies, while capable, are not yet scalable enough to enable rapid customization and instantiation for specific projects. Specifically, the heterogeneity of existing legacy sources together with firms’ range of approaches to process management makes deployment of integrated information technologies impractical. This paper reports on an architecture for distributed process integration named process connectors that addresses heterogeneity in a scalable manner. The process connectors architecture incorporates two key approaches that address heterogeneity over varying time scales. The SEEK: Scalable Extraction of Enterprise Knowledge toolkit is reviewed as a mechanism to discover semantically heterogeneous source data. The SEEK approach complements existing data integration methods for persistent sharing of information. To make use of shared data on a per project basis, a schedule mapping approach is presented that integrates firms’ diverse individual schedules in a unified representation. The schedule mapping approach allows integration of process views that have different levels of detail, while allowing participants to maintain their own view of the process. Collectively, SEEK and the schedule mapping approach facilitate a broad range of analyses to support coordination of distributed schedules. While this paper focuses primarily on schedule process integration, the process connectors architecture is viewed as providing a broad solution to discovery and integration of firms’ process data.     

智能检索引擎中的网络数据挖掘技术优化研究

随着计算机网络技术的不断发展,对于Web Service检索技术的要求也越来越大。并且现在网络环境当中数据信息流量十分庞大,对于信息可以做到深入搜索,实现全方位信息查询是非常有必要的。为此,利用网络数据挖掘技术在智能检索引擎中的应用,以文本描述为信息作为本文的研究对象,为用户提供运用查询要求实现概念检索功能。其中强调在智能搜索引擎当中的网络数据挖掘技术进行优化研究,从结构设计以及算法分析上总结出当前网络数据挖掘应用智能检索的可能性。最终设计出一种利用数据挖掘技术的智能检索模型,实现在众多网络数据中可以准确快速的进行详细的信息检索功能。     

Scheduling in a dynamic heterogeneous distributed system using estimation error

In real-world dynamic heterogeneous distributed systems, allocating tasks to processors can be an inefficient process, due to the dynamic nature of the resources, and the tasks to be processed. The information about these tasks and resources is not known a priori, and thus must be estimated online. We utilize the accuracy of these estimates, and when combined with different objectives, such as minimizing makespan and evenly distributing load, naturally gives rise to a family of four different scheduling algorithms. The algorithms have been implemented on a real-world heterogeneous distributed system with up to 90 processors. A set of real-world problems from the areas of cryptography, bioinformatics, and biomedical engineering were used as a test-set to measure the effectiveness of the scheduling algorithms. We have found that considering estimation error when allocating tasks to processors can provide more efficient solutions, than when estimation error is not considered. We have found that using a simple heuristic, combined with estimation error, can in some cases provide solutions approaching the efficiency of complicated well-known evolutionary algorithms.     

An architecture for real-time distributed artificial intelligent systems

This paper introduces a new architecture for a real-time distributed artificial intelligence system: DENIS—a Dynamic Embedded Noticeboard Information System. The fundamental idea underlying the architecture draws heavily upon a distributed human system analogy, as seen, for example, in the workplace. The aim of DENIS is to provide a simple, meaningful means by which autonomous intelligent agents can cooperate and coordinate their actions in order to enhance the reliability and effectiveness of a real-time distributed control system. Based on a human paradigm, the architecture inherently allows for the control of an intelligent agent to be taken over by a human operator, yet still to maintain consistency in the distributed system. The key to the thinking in this new approach is to try to model how humans work together, and to implement this in a distributed architecture. One of the main issues raised is that humans owe much of their flexibility to their ability to reason, not only logically, but also in terms of time.     

An agent-based service-oriented integration architecture for collaborative intelligent manufacturing

The rapidly changing needs and opportunities of today's global market require unprecedented levels of interoperability to integrate diverse information systems to share knowledge and collaborate among organizations. The combination of Web services and software agents provides a promising computing paradigm for efficient service selection and integration of inter-organizational business processes. This paper proposes an agent-based service-oriented integration architecture to leverage manufacturing scheduling services on a network of virtual enterprises. A unique property of this approach is that the scheduling process of an order is orchestrated on the Internet through the negotiation among agent-based Web services. A software prototype system has been implemented for inter-enterprise manufacturing resource sharing. It demonstrates how the proposed service-oriented integration architecture can be used to establish a collaborative environment that provides dynamic resource scheduling services.     

A uniform approach for programming distributed heterogeneous computing systems

Large-scale compute clusters of heterogeneous nodes equipped with multi-core CPUs and GPUs are getting increasingly popular in the scientific community. However, such systems require a combination of different programming paradigms making application development very challenging.In this article we introduce libWater, a library-based extension of the OpenCL programming model that simplifies the development of heterogeneous distributed applications. libWater consists of a simple interface, which is a transparent abstraction of the underlying distributed architecture, offering advanced features such as inter-context and inter-node device synchronization. It provides a runtime system which tracks dependency information enforced by event synchronization to dynamically build a DAG of commands, on which we automatically apply two optimizations: collective communication pattern detection and device-host-device copy removal.We assess libWater’s performance in three compute clusters available from the Vienna Scientific Cluster, the Barcelona Supercomputing Center and the University of Innsbruck, demonstrating improved performance and scaling with different test applications and configurations.