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distributed information retrieval: DEVELOPMENTS AND STRATEGIES

INTERNATIONAL JOURNAL OF ENGINEERING RESEARCH IN AFRICA 2015年 16卷 110-144页

作者： Ghansah, Benjamin Wu, Shengli Jiangsu Univ Sch Comp Sci & Commun Engn 301 Xuefu Rd Zhenjiang 212013 Jiangsu Peoples R China Data Link Inst Sch Comp Sci Tema Ghana

Opposed to centralized search where Websites are crawled and indexed, distributed information retrieval (DIR), also known as Federated Search, is a powerful way to comprehensively search multiple databases in real-time simultaneously. DIR is preferred to centralized search environments in a number of ways, characteristically among them are: 1. the diversity of resources that are made available;2. improving scalability and reducing server load and network traffic;3. the leverage of accessing the hidden or deep Web. There are three major phases/tasks of a DIR (i) resource description or collection representation (ii) resource selection and (iii) result merging. This paper aims at providing a comprehensive review on the various phases of DIR and also some current strategies being recommended in enhancing and improving the smooth implementation of a DIR system.

关键词： Federated Search distributed information retrieval Resource Description Resource Selection Result Merging

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

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information SCIENCES 2006年第22期176卷 3347-3378页

作者： Baek, Jin-Wook Yeom, Heon Y. Seoul Natl Univ Sch Engn & Comp Sci Seoul 151742 South Korea

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, incorporate a security and fault-tolerance mechanism into the planning approach to better adapt it to real network environments. (C) 2006 Elsevier Inc. All rights reserved.

关键词： mobile agents distributed information retrieval Internet and mobile computing distributed computing P2P computing

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Multi-agent-based hybrid peer-to-peer system for distributed information retrieval

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JOURNAL OF information SCIENCE 2023年第2期49卷 529-543页

作者： Pouamoun, Abdel Naser Kocabas, Ilker Ege Univ Int Comp Inst Izmir Turkey

With the increasingly huge amount of data located in various databases and the need for users to access them, distributed information retrieval (DIR) has been at the core of the preoccupations of a number of researchers. Indeed, numerous DIR systems and architectures have been proposed including the broker-based architecture. Moreover, providing DIR with more flexibility and adaptability has led researchers thinking to build DIR with software agents. Thus, this research proposes a design and an implementation of a novel system based on the broker-based architecture and the peer-to-peer (P2P) network called broker-based P2P network. The proposed architecture is implemented with a multi-agent system (MAS) where the main agent playing the role of the broker, receives query from a peer agent and forwards them to other peer agents each with their index and resources. Upon completing retrieval process at each peer agent, results are directly sent to the peer agent that initiated the query without using the broker agent. Java Agent DEvelopment framework (JADE) is used to implement the agents and, for experiments, TERRIER (TERabyte RetRIEveR) is extended and used as the search engine to retrieve the Text retrieval Conference (TREC) collections dataset notably TREC-6. The peer agent that originated the query progressively collects results coming from other peer agents, normalises and merges them and then proceeds with re-ranking. For normalisation, MinMax and Sum that are unsupervised normalisation methods are used.

关键词： Broker-based peer-2-peer network distributed information retrieval multi-agent systems score normalisation

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d-agent:: An approach to mobile agent planning for distributed information retrieval

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IEEE TRANSACTIONS ON CONSUMER ELECTRONICS 2003年第1期49卷 115-122页

作者： Baek, JW Yeom, HY Seoul Natl Univ Sch Comp Sci & Engn Seoul 151742 South Korea

Owing to advances in home networking, Internet, and mobile computing technology, the retrieval of information that is required in a timely manner has increased in importance for both the home and business user. This type of information can usually be delivered to users within the required time. Therefore, a retrieval service needs to be able to supply the required information to users within a specified time given by the user, and at the same time, it needs to have minimum system overheads from network traffic when performing the retrieval task for an anticipated increasing, number of users. In this paper, we propose a new agent-planning algorithm, called d-Agent, for distributed information retrieval. This planning algorithm has two goals: (1) to guarantee a given turn-around time;(2) to schedule mobile agents (the number of agents and each agent's itinerary) optimally while maintaining low system overheads. Although the algorithm tends to slightly increase the planning cost because of these two requirements, a simulation study shows that our algorithm is practical and realistic, and can be directly applied to distributed information retrieval with deadline constrains.

关键词： distributed information retrieval Internet and mobile computing mobile agents mobile agent planning

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Collection-integral source selection for uncooperative distributed information retrieval environments

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information SCIENCES 2010年第14期180卷 2763-2776页

作者： Paltoglou, Georgios Salampasis, Michail Satratzemi, Maria Univ Macedonia Thessaloniki Greece Alexander Technol Educ Inst Thessaloniki Thessaloniki 57400 Greece

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. (C) 2010 Elsevier Inc. All rights reserved.

关键词： Source selection distributed information retrieval Federated search

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Using query logs to establish vocabularies in distributed information retrieval

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information PROCESSING & MANAGEMENT 2007年第1期43卷 169-180页

作者： Shokouhi, Milad Zobel, Justin Tahaghoghi, Saied Scholer, Falk RMIT Univ Sch Comp Sci & Informat Technol Melbourne Vic 3001 Australia

Users of search engines express their needs as queries, typically consisting of a small number of terms. The resulting search engine query logs are valuable resources that can be used to predict how people interact with the search system. In this paper, we introduce two novel applications of query logs, in the context of distributed information retrieval. First, we use query log terms to guide sampling from uncooperative distributed collections. We show that while our sampling strategy is at least as efficient as current methods, it consistently performs better. Second, we propose and evaluate a pruning strategy that uses query log information to eliminate terms. Our experiments show that our proposed pruning method maintains the accuracy achieved by complete indexes, while decreasing the index size by up to 60%. While such pruning may not always be desirable in practice, it provides a useful benchmark against which other pruning strategies can be measured. (c) 2006 Elsevier Ltd. All rights reserved.

关键词： distributed information retrieval uncooperative environments indexing query logs

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Knowledge based collection selection for distributed information retrieval

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information PROCESSING & MANAGEMENT 2018年第1期54卷 116-128页

作者： Han Baoli Chen Ling Tian Xiaoxue Zhejiang Univ Coll Comp Sci & Technol Hangzhou 310027 Zhejiang Peoples R China

Recent years have seen a great deal of work on collection selection. Most collection selection methods use central sample index (CSI) that consists of some documents sampled from each collection as collection description. The limitations of these methods are the usage of 'flat' meaning representations that ignore structure and relationships among words in CSI, and the calculation of query-collection similarity metric that ignore semantic distance between query words and indexed words. In this paper, we propose a knowledge based collection selection method (KBCS) to improve collection representation and query-collection similarity metric. KBCS models a collection as a weighted entity set and applies a novel query-collection similarity metric to select highly scored collections. Specifically, in the part of collection representation, context and structure-based measures are employed to weight the semantic distance between two entities extracted from the sampled documents of a collection. In addition, the novel query-collection similarity metric takes the entity weight, collection size, and other factors into account. To enrich concepts contained in a query, DBpedia based query expansion is integrated. Finally, extensive experiments were conducted on a large webpage dataset, and DBpedia was chosen as the graph knowledge base. Experimental results demonstrate the effectiveness of KBCS.

关键词： Collection selection distributed information retrieval Knowledge base Query expansion

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A results merging algorithm for distributed information retrieval environments that combines regression methodologies with a selective download phase

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information PROCESSING & MANAGEMENT 2008年第4期44卷 1580-1599页

作者： Paltoglou, Georgios Salampasis, Michail Satratzemi, Maria Univ Macedonia Thessaloniki 54006 Greece Alexandcr Technol Educ Inst Thessaloniki Thessaloniki 57400 Greece

The problem of results merging in distributed information retrieval environments has gained significant attention the last years. Two generic approaches have been introduced in research. The first approach aims at estimating the relevance of the documents returned from the remote collections through ad hoc methodologies (such as weighted score merging, regression etc.) while the other is based on downloading all the documents locally, completely or partially, in order to calculate their relevance. Both approaches have advantages and disadvantages. Download methodologies are more effective but they pose a significant overhead on the process in terms of time and bandwidth. Approaches that rely solely on estimation on the other hand, usually depend on document relevance scores being reported by the remote collections in order to achieve maximum performance. In addition to that, regression algorithms, which have proved to be more effective than weighted scores merging algorithms, need a significant number of overlap documents in order to function effectively, practically requiring multiple interactions with the remote collections. The new algorithm that is introduced is based on adaptively downloading a limited, selected number of documents from the remote collections and estimating the relevance of the rest through regression methodologies. Thus it reconciles the above two approaches, combining their strengths, while minimizing their drawbacks, achieving the limited time and bandwidth overhead of the estimation approaches and the increased effectiveness of the download. The proposed algorithm is tested in a variety of settings and its performance is found to be significantly better than the former, while approximating that of the latter. (C) 2008 Elsevier Ltd. All rights reserved.

关键词： results merging distributed information retrieval federated search

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Testing the cluster hypothesis in distributed information retrieval

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information PROCESSING & MANAGEMENT 2006年第5期42卷 1137-1150页

作者： Crestani, Fabio Wu, Shengli Univ Strathclyde Dept Informat & Comp Sci Glasgow G1 1XH Lanark Scotland Univ Ulster Sch Comp & Math Belfast Antrim North Ireland

How to merge and organise query results retrieved from different resources is one of the key issues in distributed information retrieval. Some previous research and experiments suggest that cluster-based document browsing is more effective than a single merged list. Cluster-based retrieval results presentation is based on the cluster hypothesis, which states that documents that cluster together have a similar relevance to a given query. However, while this hypothesis has been demonstrated to hold in classical information retrieval environments, it has never been fully tested in heterogeneous distributed information retrieval environments. Heterogeneous document representations, the presence of document duplicates, and disparate qualities of retrieval results, are major features of an heterogeneous distributed information retrieval environment that might disrupt the effectiveness of the cluster hypothesis. In this paper we report on an experimental investigation into the validity and effectiveness of the cluster hypothesis in highly heterogeneous distributed information retrieval environments. The results show that although clustering is affected by different retrieval results representations and quality, the cluster hypothesis still holds and that generating hierarchical clusters in highly heterogeneous distributed information retrieval environments is still a very effective way of presenting retrieval results to users. (c) 2005 Elsevier Ltd. All rights reserved.

关键词： information retrieval retrieval results presentation clustering experimental study distributed information retrieval

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Performance analysis of distributed information retrieval architectures using an improved network simulation model

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information PROCESSING & MANAGEMENT 2007年第1期43卷 204-224页

作者： Cacheda, Fidel Carneiro, Victor Plachouras, Vassilis Ounis, Iadh Univ A Coruna Dept Informat & Commun Technol Fac Informat La Coruna 15071 Spain Univ Glasgow Dept Comp Sci Glasgow G12 8QQ Lanark Scotland

The increasing number of documents that have to be indexed in different environments, particularly on the Web, and the lack of scalability of a single centralised index lead to the use of distributed information retrieval systems to effectively search for and locate the required information. In this study, we present several improvements over the two main bottlenecks in a distributed information retrieval system (the network and the brokers). We extend a simulation network model in order to represent a switched network. The new simulation model is validated by comparing the estimated response times with those obtained using a real system. We show that the use of a switched network reduces the saturation of the interconnection network, especially in a replicated system, and some improvements may be achieved using multicast messages and faster connections with the brokers. We also demonstrate that reducing the partial results sets will improve the response time of a distributed system by 53%, with a negligible probability of changing the system's precision and recall values. Finally, we present a simple hierarchical distributed broker model that will reduce the response times for a distributed system by 55%. (c) 2006 Elsevier Ltd. All rights reserved.

关键词： distributed information retrieval performance simulation network model

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