Approaches to collection selection and results merging for distributed information retrieval

Rasolofo, Yves; Abbaci, Faïza; Savoy, Jacques

doi:10.1145/502585.502618

Cited by 41 publications

(35 citation statements)

References 14 publications

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“…The output and analysis showed that the technique developed the search effectively of the database and fixed search quality was also developed. In [7], the idea of exploiting the scores of each search engine was proposed, where the main information was the relative rank of each result. In [7], different ranking methods were analyzed, for example Borda-fuse which was based on democratic voting, the Borda count, or the weighted borda-fuse, in which search engines were not treated equally [11].…”

Section: Fig 1: Catalogs Per Countrymentioning

confidence: 99%

An Agent-based Meta-Search Engine Architecture for Open Government Datasets Search

Hasan¹,

Fazle²,

Ntikurako³

2016

CAE

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Recently, Most of the countries are publishing their government data in the Web as datasets. A large number of datasets (HTML, CSV, RDF, XML, JSON, Excel, and PDF etc), catalogs and portals (data.gov, data.gov.uk, data.gov.au etc) are emerging in the Science and Government sector. Open Government Data drives in the US, UK and elsewhere have created hung amounts of government data available to the public on the web. A large number of datasets are published on government data portals, the question arises how to get datasets satisfying from government data portals with the least effort. However in many cases, a single search result is not sufficient to meet the user's query and it is necessary to create a new service platform by combining existing government catalogs search. In this paper we proposed a meta-search architecture that will integrate different dataset catalogs search interface and collected datasets from different open government data catalogs and display higher results. In this proposed architecture have search interface provides a scalable and recognizable solution for finding Open Government datasets from open government data catalogs. Thus, the propose meta-search architecture improves the usability and effectively of open government datasets search.

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Section: Fig 1: Catalogs Per Countrymentioning

confidence: 99%

An Agent-based Meta-Search Engine Architecture for Open Government Datasets Search

Hasan¹,

Fazle²,

Ntikurako³

2016

CAE

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“…Aggregated search can be compared to federated search [12], metasearch [7] and distributed information retrieval [5], which are all concerned with the retrieval of documents from several sources (e.g. digital libraries, search engines, specialist collections, etc.).…”

Section: Related Workmentioning

confidence: 99%

Factors affecting click-through behavior in aggregated search interfaces

Sushmita

Joho

Lalmas

et al. 2010

Proceedings of the 19th ACM International Conference on Information and Knowledge Management

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An aggregated search interface is designed to integrate search results from different sources (web, image, video, blog, etc) into a single result page. This paper presents two user studies investigating factors affecting users click-through behavior on aggregated search interfaces. We tested two aggregated search interfaces: one where results from the different sources are blended into a single list (called blended ), and another, where results from each source are presented in a separate panel (called non-blended ). A total of 1,296 search sessions performed by 48 participants were analysed in our study. Our results suggest that 1) the position of search results is significant only in the blended and not in the nonblended design; 2) participants' click-through behavior on videos is different from other sources; and finally 3) capturing a task's orientation towards particular sources is an important factor for further investigation and research.

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“…Parallel query processing is required in the search system due to the distributed index and processors. Rasolofo et al [15] propose a collection selection and result merging strategy for distributed Web search system. Orlando et al [16] have developed a distributed Web search engine, MOSE, which utilizes two types of parallelism, task parallelism and data parallelism, in processing queries.…”

Section: Related Workmentioning

confidence: 99%

Exploiting Parallelism to Accelerate Keyword Search on Deep-Web Sources

Liu

Wang

Agrawal

2009

Lecture Notes in Computer Science

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Abstract. Increasingly, biological data is being shared over the deep web. Many biological queries can only be answered by successively searching a number of distinct web-sites. This paper introduces a system that exploits parallelization for accelerating search over multiple deep web data sources. An interactive, two-stage multi-threading system is developed to achieve task parallelization, thread parallelization, and pipelined parallelization. We show the effectiveness of our system by considering a number of queries involving SNP datasets. We show that most of the queries can be accelerated significantly by exploiting these three forms of parallelism.

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Approaches to collection selection and results merging for distributed information retrieval

Cited by 41 publications

References 14 publications

An Agent-based Meta-Search Engine Architecture for Open Government Datasets Search

An Agent-based Meta-Search Engine Architecture for Open Government Datasets Search

Factors affecting click-through behavior in aggregated search interfaces

Exploiting Parallelism to Accelerate Keyword Search on Deep-Web Sources

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