A Visual Exploratory Search Engine Solution Based on Cloud Computing

Tang, Jiyu; Tang, Xinhuai; Chen, Delai

doi:10.1109/cgc.2012.97

Cited by 3 publications

(4 citation statements)

References 12 publications

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“…Search engines comprise of five parts namely: fetcher, parser, indexer, retriever and the user interface. The classical search engines operate in a more focused manner such that they cannot perform parallel operations efficiently and give the users timely searches [17].…”

Section: Literature Reviewmentioning

confidence: 99%

A Visual Exploratory Meta Data Search Engine Solution based on Cloud Computing

NajahMahdi¹,

Ahmad²,

Ismail³

2014

IJCA

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With the rapid upsurge of web use and internet connectivity (Access), the traditional search engines face significant challenges in the contemporary searches, response speed and the storage of bulk pages. The search engine contained in the cloud can help alleviate the identified shortcomings. This is simply because cloud computing is advantageous in mass data processing and storage. Through an analysis of a visual exploratory Meta data search engine on a cloud platform, there will be strategies adopted to optimize the search engine in order to improve the overall performance and effectiveness of search.

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Section: Literature Reviewmentioning

confidence: 99%

A Visual Exploratory Meta Data Search Engine Solution based on Cloud Computing

NajahMahdi¹,

Ahmad²,

Ismail³

2014

IJCA

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“…There are also some researchers proposed the combination of search engine and cloud computing platform [9]- [13], which can solve the problem of resources and efficiency and sharply reduce the user retrieval time. The feasibility and advantages of the combination of cloud computing and search engine are analyzed in [9] and [10], but they only give the theoretical analysis results. [11] elaborates how to realize the classic inverted index algorithm through MapReduce, but does not realize it.…”

Section: Introductionmentioning

confidence: 99%

The realization of the distributed search engine on cloud platform

Yuan

Xiaozhen

et al. 2013

Proceedings of 2013 2nd International Conference on Measurement, Information and Control

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With the rapid development of the Internet and websites, the amount of web data increases exponentially, which leads to great challenges of the traditional centralized search engine in the real-time search, response speed and the storage of mass pages. Cloud computer, which can integrate resources of many PCs to provide distributed storage and parallel computing, has many advantages in dealing with mass data. As a result, a distributed search engine on cloud platform is proposed in this paper. It consists of three main modules: crawling, indexing and retrieving. Furthermore, it also presents visual user interaction interfaces. The search engine is implemented on Hadoop, with Hadoop Distributed File System (HDFS) for storage and parallel programming model MapReduce to realize indexing and retrieving functions. The search engine on Hadoop can store mass pages with many cheap machines, retrieve the wanted information from mass data as shown in function test and reduce query time as shown in performance test, so it is economical, accurate and efficient.The search engine is a system based on certain strategies that uses specific computer programs to collect infonnation from Internet and organizes the information to provide retrieval services for users. With the rapid development of the Internet, the search engine becomes more and more important for Internet users to retrieve useful infonnation. In order to improve the speed and the accuracy of the search engine, many optimization techniques are put forward by the researchers, such as intelligent agent technology, natural language processing technology [1], semantic search [2] and so on. However, the rapid increase of the websites and online population leads to web data explosion. For example, the web pages stored in Google database have reached 30 billion. The traditional single and centralized search engine may have trouble in dealing with the massive data because it cannot achieve efficient parallel operation. Cloud computing technology develops fast in recent years. Many companies have launched their own commercial clouds, such as Google App Engine, Amazon A WS, Microsoft Windows Azure, etc. In order to facilitate academic researches, Apache proposes an open source cloud computing platfonn---Hadoop[3], which consists of two basic parts: HDFS[4] and MapReduce[5], and some other items based on them. Hadoop 978-1-4799-1392-3/13/$31.00 m013 IEEE 691has the ability to store and efficiently process massive data and its applications are greatly extensive. Moreover, Hadoop can use lots of cheap machines to achieve more reliable and secure data center. The results of [6] prove Hadoop has many advantages in storing and processing massive data. As a result, many applications [7]-[8] are deployed on Hadoop. There are also some researchers proposed the combination of search engine and cloud computing platform [9]-[13], which can solve the problem of resources and efficiency and sharply reduce the user retrieval time. The feasibility and advantages of the combination of cloud co...

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“…Whereas researchers like Tang [4] have mentioned that still the present do search engines are unclear and the users have to figure out the semantic relationships by themselves by applying various efforts.…”

Section: Problem Statementmentioning

confidence: 99%

“…Little [17] recommended in his study the use of Semantic Framework and semantic annotations. This study was more relevant to information retrieval among Videos and this study proposes to adopt the same concept along with the study of Tang [4] which had certain limitations.…”

Section: Proposed Approachmentioning

confidence: 99%

A Real Time Visual Exploratory Search Engine for Information Retrieval in a Cloud

Mahdi¹,

Ahmad²,

Ismail³

2015

IJFCC

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Abstract-Search engines employed under cloud computing have been crucial in enabling users in retrieving information. This has allowed users to access wide volume of information that is significantly impossible under the tradition information collection that involved manual search of the intended information. The main focus of this study is on improving the traditional search engine by providing a novel framework for people to obtain reliable, personalization and graphical representation search results. This study proposes and develops a Visual Exploratory search engine solution extremely good in understanding semantic similarity computation which can access multiple Metadata based search engines at the same time and generating real-time relationship graphs for a better visual exploratory search in a cloud computing environment. The study proposes a Research Model based on which the proposed prototype would be developed.Index Terms-Cloud computing, exploratory search, meta-search, search engine.

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A Visual Exploratory Search Engine Solution Based on Cloud Computing

Cited by 3 publications

References 12 publications

A Visual Exploratory Meta Data Search Engine Solution based on Cloud Computing

A Visual Exploratory Meta Data Search Engine Solution based on Cloud Computing

The realization of the distributed search engine on cloud platform

A Real Time Visual Exploratory Search Engine for Information Retrieval in a Cloud

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