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Journal articles on the topic 'Meta-search engine'

Author: Grafiati

Published: 4 June 2021

Last updated: 16 February 2022

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1

Maree, Mohammed, Saadat M. Alhashmi, and Mohammed Belkhatir. "Towards Improving Meta-Search through Exploiting an Integrated Search Model." Journal of Information & Knowledge Management 10, no. 04 (December 2011): 379–91. http://dx.doi.org/10.1142/s0219649211003073.

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Meta-search engines are created to reduce the burden on the user by dispatching queries to multiple search engines in parallel. Decisions on how to rank the returned results are made based on the query's keywords. Although keyword-based search model produces good results, better results can be obtained by integrating semantic and statistical based relatedness measures into this model. Such integration allows the meta-search engine to search by meanings rather than only by literal strings. In this article, we present Multi-Search+, the next generation of Multi-Search general-purpose meta-search engine. The extended version of the system employs additional knowledge represented by multiple domain-specific ontologies to enhance both the query processing and the returned results merging. In addition, new general-purpose search engines are plugged-in to its architecture. Experimental results demonstrate that our integrated search model obtained significant improvement in the quality of the produced search results.

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Puspitaningrum, Diyah. "TEKNIK PERANGKINGAN META-SEARCH ENGINE." Pseudocode 1, no. 1 (January 1, 2014): 15–23. http://dx.doi.org/10.33369/pseudocode.1.1.15-23.

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3

Zhang, Jin, and Chi Cheung. "Meta‐search‐engine feature analysis." Online Information Review 27, no. 6 (December 2003): 433–41. http://dx.doi.org/10.1108/14684520310510073.

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4

R. Sathiya, R., A. G. Jayasree, Raghuvamsi Tangirala, and Damerla Prasanna. "A Study of Various Result Merging Strategies for a Meta Search Engine." International Journal of Engineering & Technology 7, no. 3.6 (July 4, 2018): 255. http://dx.doi.org/10.14419/ijet.v7i3.6.14983.

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As the amount of data is growing day by day, the sources for these data are also growing simultaneously and to search through this very data, we need the use of search engines. Since each search engine is limited to its confined set of data, it would be even better to make use of a Meta search engine which will give us more relevant results than the ones obtained from any single search engine. It acts as an interface that provides the user with a single view from the various underlying search engines. The data is collected from these underlying search engines after they are accessed with the processed query from the Meta search engine. The collected data is merged using an algorithm and the algorithm will be a major factor in giving the best possible results. In this paper, we are going to discuss about the various existing metasearch engines and the different merging techniques and their approaches.

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Kejriwal, Mayank. "A meta-engine for building domain-specific search engines." Software Impacts 7 (February 2021): 100052. http://dx.doi.org/10.1016/j.simpa.2020.100052.

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Lee, In-K., Seo-H. Son, and Soon-H. Kwon. "Knowledge-based Semantic Meta-Search Engine." Journal of Korean Institute of Intelligent Systems 14, no. 6 (October 1, 2004): 737–44. http://dx.doi.org/10.5391/jkiis.2004.14.6.737.

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Borkar, N. A., and S. V. Kulkarni. "Architecture for Personalized Meta Search Engine." International Journal of Computer Sciences and Engineering 06, no. 01 (February 28, 2018): 55–59. http://dx.doi.org/10.26438/ijcse/v6si1.5559.

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El-Sayed, Maged. "SEARCHSENSE: A SEMANTIC META SEARCH ENGINE." International Journal of Intelligent Computing and Information Sciences 18, no. 1 (January 1, 2018): 15–25. http://dx.doi.org/10.21608/ijicis.2018.15907.

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Lawrence, Steve, and C. Lee Giles. "Inquirus, the NECI meta search engine." Computer Networks and ISDN Systems 30, no. 1-7 (April 1998): 95–105. http://dx.doi.org/10.1016/s0169-7552(98)00095-6.

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Kos, Alexander, and Hans-Jürgen Himmler. "CWM Global Search—The Internet Search Engine for Chemists and Biologists." Future Internet 2, no. 4 (December 3, 2010): 635–44. http://dx.doi.org/10.3390/fi2040635.

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CWM Global Search is a meta-search engine allowing chemists and biologists to search the major chemical and biological databases on the Internet, by structure, synonyms, CAS Registry Numbers and free text. A meta-search engine is a search tool that sends user requests to several other search engines and/or databases and aggregates the results into a single list or displays them according to their source [1]. CWM Global Search is a web application that has many of the characteristics of desktop applications (also known as Rich Internet Application, RIA), and it runs on both Windows and Macintosh platforms. The application is one of the first RIA for scientists. The application can be started using the URL http://cwmglobalsearch.com/gsweb.

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O’Neill, Stephen, and Kevin Curran. "The Core Aspects of Search Engine Optimisation Necessary to Move up the Ranking." International Journal of Ambient Computing and Intelligence 3, no. 4 (October 2011): 62–70. http://dx.doi.org/10.4018/jaci.2011100105.

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Search engine optimization (SEO) is the process of improving the visibility, volume and quality of traffic to website or a web page in search engines via the natural search results. SEO can also target other areas of a search, including image search and local search. SEO is one of many different strategies used for marketing a website but SEO has been proven the most effective. An Internet marketing campaign may drive organic search results to websites or web pages but can be involved with paid advertising on search engines. All search engines have a unique way of ranking the importance of a website. Some search engines focus on the content while others review Meta tags to identify who and what a web site’s business is. Most engines use a combination of Meta tags, content, link popularity, click popularity and longevity to determine a sites ranking. To make it even more complicated, they change their ranking policies frequently. This paper provides an overview of search engine optimisation strategies and pitfalls.

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Zhang, Yong Hua, and Chao Wang. "Design and Implementation of News Summary Based on Meta Search Engine." Advanced Materials Research 798-799 (September 2013): 803–7. http://dx.doi.org/10.4028/www.scientific.net/amr.798-799.803.

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The relationship between the meta search engine and independent search engine is presented. The news information searched by the independent search engine is not accurate and complete. After researching the technology of summary generation and meta search engine, summary generation algorithm is improved, the news summary based meta search engine system is put forward and the realization of it is expounded. Experiment showed the summary created did well in readability and coverage, and enhanced the precision.

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Raeth, Peter G. "Accessing Quality Open-Access Literature to Enable Teaching, Learning, and Industry." International Journal of ICT Research in Africa and the Middle East 7, no. 2 (July 2018): 1–16. http://dx.doi.org/10.4018/ijictrame.2018070101.

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Commercial control of the world's published literature has grown to the point where costs are prohibitive for developing nations. This article describes a computer engineer's response to this problem. The result is a publicly-accessible meta-search engine that focuses on open-access sources. With one set of keywords, this engine searches many engines at the same time. It has been used to help develop entire courses based solely on open-access literature. While there are excellent search capabilities for open-access literature that deliver full and searchable text, none of these cover the entire space. To examine a larger space, one must manually employ numerous engines. Herein is a discussion, background, vision, and top-level dataflow for the author's publicly-accessible meta-search engine that evolves with the needs of education, training, and industry.

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Ayaz, A. Salman, Jaya A. Venkat, and Zameer Gulzar. "Recommendation-Based Meta-Search Engine for Suggesting Relevant Documents Links." International Journal of Information and Communication Technology Education 16, no. 4 (October 2020): 86–99. http://dx.doi.org/10.4018/ijicte.2020100106.

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The information available online is mostly present in an unstructured form and search engines are indispensable tools especially in higher education organizations for obtaining information from the Internet. Various search engines were developed to help learners to retrieve the information but unfortunately, most of the information retrieved is not relevant. The main objective of this research is to provide relevant document links to the learners using a three-layered meta-search architecture. The first layer retrieves information links from the web based on the learner query, which is then fed to the second layer where filtering and clustering of document links are done based on semantics. The third layer, with the help of a reasoner, categorizes information into relevant and irrelevant information links in the repository. The experimental study was conducted on a training data set using web queries related to the domain of sports, entertainment, and academics. The results indicate that the proposed meta-search engine performs well as compared to another stand-alone search engine with better recall.

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Kumar, Naresh. "Document Clustering Approach for Meta Search Engine." IOP Conference Series: Materials Science and Engineering 225 (August 2017): 012291. http://dx.doi.org/10.1088/1757-899x/225/1/012291.

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Vargas-Vera, Maria, Yesica Castellanos, and Miltiadis D. Lytras. "CONQUIRO: A cluster-based meta-search engine." Computers in Human Behavior 27, no. 4 (July 2011): 1303–9. http://dx.doi.org/10.1016/j.chb.2010.07.025.

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17

Hildebrandt, Mario, Aamir Shakir, Alexander Ziemke, Mohamed Abdelrazek, Hannes Stuetzer, Dominik Blut, Kevin Lamshoeft, Salatiel Ezennaya-Gomez, Christian Kraetzer, and Jana Dittmann. "AiroIdent – User identification based on analyzing WPA2 encrypted traffic containing search engine interactions." Electronic Imaging 2021, no. 4 (January 18, 2021): 344–1. http://dx.doi.org/10.2352/issn.2470-1173.2021.4.mwsf-344.

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Most search engines provide search suggestions and autocompletion mechanisms based on the partially typed search string. In order to implement such functionality, frequent requests are being sent to the search engine provider. Recent publications show that there is a risk that the user can be identified by observing the TLS encrypted traffic and analyzing the unencrypted meta data. In this paper we extend this approach to the observation of widely used encrypted WiFi networks in order to estimate the potential privacy impact. Without having access to Layer 3 and 4 meta data, the main challenge of this approach is the identification of potential requests being sent to the search engine. We use a linear regression-based approach to identify candidate packet sequences for the feature extraction. The evaluation is done in an optimal environment (reduced WiFi-traffic) to determine a first tendency and performed using three search engines. In total four different user identification/verification approaches are utilized: M1 identification using a neural network, M2 identification using Manhattan distance, M3 identification using Euclidean distance and M4 verification using a one-class support vector machine (SVM). Our results show a classification performance for 10 different test subjects is ranging from 13.2% using the one-class SVM (M4) to 64.1% using the neural network (M1) for the identical search engine. In comparison to a group of five test subjects it can be seen that M1 provides more scalability in comparison to M2, M3 and M4. In addition to that, we present potential countermeasures which could help to increase the privacy of the users of a search engine.

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Hasan, S. M., Md Fazle, and Kazihise Ntikurako. "An Agent-based Meta-Search Engine Architecture for Open Government Datasets Search." Communications on Applied Electronics 4, no. 7 (March 25, 2016): 21–25. http://dx.doi.org/10.5120/cae2016652131.

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19

M, Manoj, and Elizabeth Jacob. "Design and Development of a Programmable Meta Search Engine." International Journal of Computer Applications 74, no. 5 (July 26, 2013): 6–11. http://dx.doi.org/10.5120/12879-9739.

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Wei-feng, Zhang, Xu Bao-wen, Zhou Xiao-yu, and Huang Hui. "Scheduling in a meta search engine by Genetic Algorithm." Wuhan University Journal of Natural Sciences 6, no. 1-2 (March 2001): 541–46. http://dx.doi.org/10.1007/bf03160299.

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21

Kumar, Naresh, and Praveer Singh. "Meta Search Engine with Semantic Analysis and Query Processing." International Journal of Computational Intelligence Research 13, no. 8 (October 30, 2017): 2005–13. http://dx.doi.org/10.37622/ijcir/13.8.2017.2005-2013.

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22

Ren, Wu Ling, and Li Juan Liu. "The Research of a Multi-Language Supporting Description-Oriented Clustering Algorithm on Meta-Search Engine Result." Applied Mechanics and Materials 151 (January 2012): 549–53. http://dx.doi.org/10.4028/www.scientific.net/amm.151.549.

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Search engine has adopted a variety of techniques to improve the accuracy of information retrieval, but the way of a linear list of search engine results, which mixes unrelated documents with relevant documents, has brought user great burden. This article commits to build clustering of search results, which is based on meta search engine techniques. We use all the popular search engine as a data source, then after a certain pre-processing of the source search engine, hierarchical clustering results is formed and returned to the query users. we propose a multi-language supporting, label first clustering algorithm, which we named DCFC algorithm. This algorithm supports both Chinese and English query, focuses on generating human readable labels, shows search results in hierarchical structure.

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23

Maskur, Maskur. "PENGUKUR PARAMETER SEARCH ENGINE OPTIMIZATION (SEO) SECARA ON PAGE PADA TOKO ONLINE UNTUK MENINGKATKAN PENJUALAN." Adbis: Jurnal Administrasi dan Bisnis 13, no. 1 (June 30, 2019): 83. http://dx.doi.org/10.33795/j-adbis.v13i1.68.

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The current search engine is not only for searching the pages of the website you want to visit but also as the main source of visitors on the internet. With the development of technology several ways that can be used to improve website ranking on search engines, one effective way by utilizing Search Engine Optimization (SEO) can help some websites to get SERP rankings (Search Engine Results Pages) on search engines, by a good SERP ranking will then be determined on the number of visitors on the website. An application is needed to calculate SEO applications on a web site, with the application of Online SEO measurement parameters can help business users of online stores to increase visitors and invite visitors who become buyers. In the Complete SEO Parameter Measurement Application on this page has 6 important parameters in SEO on the page provided, Title Tag, Title Tag, Meta Description, Content, Alt Tag and Keyword Density, with an explanation of each - each parameter where The accuracy of the application results in the calculation can be obtained Kappa value of 0.57..

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Hayaty, Mardhiya, and Dwi Meylasari. "Implementasi Website Berbasis Search Engine Optimization (SEO) Sebagai Media Promosi." Jurnal Informatika 5, no. 2 (September 15, 2018): 295–300. http://dx.doi.org/10.31311/ji.v5i2.4027.

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AbstrakKemajuan teknologi informasi berkembang secara pesat di berbagai bidang kehidupan. Internet adalah salah satu bagian dari teknologi informasi dan komunikasi mempunyai efek dan pengaruh yang sangat besar. Website salah satu teknologi internet tidak hanya sebagai media informasi tetapi menjadi proses pendukung bisnis perusahaan, akan tetapi penjualan melalui website belum cukup efektif jika tidak didukung dengan strategi promosi yang baik. SEO (Search Engine Optimization) adalah salah satu teknik promosi dengan cara memanfaatkan pengoptimalan mesin pencari agar website yang sudah kita buat berada diperingkat teratas atau halaman pertama (first page) sebuah halaman mesin pencari. Peneltian ini dilakukan pada sebuah website yang awalnya belum dilakukan teknik-teknik dari SEO, kemudian dengan menerapkan metode SEO on Page seperti optimasi keyword pada title tag, content, meta keyword,meta description, dan share ke sosial media, pada tahap ini juga dilakukan beberapa pengujian sebagai tolak ukur keberhasilan penerapan teknik-teknik SEO. Hasil dari penerapan teknik-teknik SEO mampu meningkatkan SERP (Search Engine Results Page) website di mesin pencari dan berhasil terindek oleh google berada di page kedua pada bulan kedua dan berhasil terindex di page pertama dalam pencarian google denga waktu kurang dari 3 bulan. Kata kunci : Website, SEO, Seo on Page, SERP AbstractThe advancement of information technology is growing rapidly in various fields of life. The internet is one part of information and communication technology has a very large effect and influence. The website not only serves as a medium of information but supports the company's business, but sales through the website are not effective enough if it is not supported by a good promotional strategy. SEO (Search Engine Optimization) is a promotional technique by utilizing search engine optimization so that the website we have created is at the top or first page (first page) of a search engine page.This research was conducted on a website that has not been done techniques from SEO, then by applying the SEO on Page method such as keyword optimization on title tags, content, meta keywords, meta description, and sharing to social media, at this stage several tests are also carried out. as a benchmark for the successful application of SEO techniques.The results of the application of SEO techniques are able to increase the SERP (Search Engine Results Page) of websites in search engines and successfully indexed by Google on the second page in the second month and successfully indexed on the first page in google search with less than 3 months. Keywords: Website, SEO, Seo on Page, SERP

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Hayaty, Mardhiya, and Dwi Meylasari. "Implementasi Website Berbasis Search Engine Optimization (SEO) Sebagai Media Promosi." Jurnal Informatika 5, no. 2 (September 15, 2018): 295–300. http://dx.doi.org/10.31294/ji.v5i2.4027.

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AbstrakKemajuan teknologi informasi berkembang secara pesat di berbagai bidang kehidupan. Internet adalah salah satu bagian dari teknologi informasi dan komunikasi mempunyai efek dan pengaruh yang sangat besar. Website salah satu teknologi internet tidak hanya sebagai media informasi tetapi menjadi proses pendukung bisnis perusahaan, akan tetapi penjualan melalui website belum cukup efektif jika tidak didukung dengan strategi promosi yang baik. SEO (Search Engine Optimization) adalah salah satu teknik promosi dengan cara memanfaatkan pengoptimalan mesin pencari agar website yang sudah kita buat berada diperingkat teratas atau halaman pertama (first page) sebuah halaman mesin pencari. Peneltian ini dilakukan pada sebuah website yang awalnya belum dilakukan teknik-teknik dari SEO, kemudian dengan menerapkan metode SEO on Page seperti optimasi keyword pada title tag, content, meta keyword,meta description, dan share ke sosial media, pada tahap ini juga dilakukan beberapa pengujian sebagai tolak ukur keberhasilan penerapan teknik-teknik SEO. Hasil dari penerapan teknik-teknik SEO mampu meningkatkan SERP (Search Engine Results Page) website di mesin pencari dan berhasil terindek oleh google berada di page kedua pada bulan kedua dan berhasil terindex di page pertama dalam pencarian google denga waktu kurang dari 3 bulan. Kata kunci : Website, SEO, Seo on Page, SERP AbstractThe advancement of information technology is growing rapidly in various fields of life. The internet is one part of information and communication technology has a very large effect and influence. The website not only serves as a medium of information but supports the company's business, but sales through the website are not effective enough if it is not supported by a good promotional strategy. SEO (Search Engine Optimization) is a promotional technique by utilizing search engine optimization so that the website we have created is at the top or first page (first page) of a search engine page.This research was conducted on a website that has not been done techniques from SEO, then by applying the SEO on Page method such as keyword optimization on title tags, content, meta keywords, meta description, and sharing to social media, at this stage several tests are also carried out. as a benchmark for the successful application of SEO techniques.The results of the application of SEO techniques are able to increase the SERP (Search Engine Results Page) of websites in search engines and successfully indexed by Google on the second page in the second month and successfully indexed on the first page in google search with less than 3 months. Keywords: Website, SEO, Seo on Page, SERP

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Raut, Sagar A. "Patient Centric Meta-Search Engine for Quality of Care Services." International Journal for Research in Applied Science and Engineering Technology 7, no. 6 (June 30, 2019): 1200–1208. http://dx.doi.org/10.22214/ijraset.2019.6207.

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Liebel, U., B. Kindler, and R. Pepperkok. "'Harvester': a fast meta search engine of human protein resources." Bioinformatics 20, no. 12 (February 26, 2004): 1962–63. http://dx.doi.org/10.1093/bioinformatics/bth146.

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Vijaya, P., G. Raju, and Santosh Kumar Ray. "Artificial neural network-based merging score for Meta search engine." Journal of Central South University 23, no. 10 (October 2016): 2604–15. http://dx.doi.org/10.1007/s11771-016-3322-7.

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Gupta, Amar, Michael Nissan, Michael Carron, Giancarlo Zuliani, and Hani Rayess. "Search Engine Optimization: An Analysis of Rhinoplasty Web sites." Facial Plastic Surgery 33, no. 06 (December 2017): 665–69. http://dx.doi.org/10.1055/s-0037-1607973.

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AbstractThe Internet is the primary source of information for facial plastic surgery patients. Most patients only analyze information in the first 10 Web sites retrieved. The aim of this study was to determine factors critical for improving Web site traffic and search engine optimization. A Google search of “rhinoplasty” was performed in Michigan. The first 20 distinct Web sites originating from private sources were included. Private was defined as personal Web sites for private practice physicians. The Web sites were evaluated using SEOquake and WooRANK, publicly available programs that analyze Web sites. Factors examined included the presence of social media, the number of distinct pages on the Web site, the traffic to the Web site, use of keywords, such as rhinoplasty in the heading and meta description, average visit duration, traffic coming from search, bounce rate, and the number of advertisements. Readability and Web site quality were also analyzed using the DISCERN and Health on the Net Foundation code principles. The first 10 Web sites were compared with the latter 10 Web sites using Student's t-tests. The first 10 Web sites received a significantly lower portion of traffic from search engines than the second 10 Web sites. The first 10 Web sites also had significantly fewer tags of the keyword “nose” in the meta description of the Web site. The first 10 Web sites were significantly more reliable according to the DISCERN instrument, scoring an average of 2.42 compared with 2.05 for the second 10 Web sites (p = 0.029). Search engine optimization is critical for facial plastic surgeons as it improves online presence. This may potentially result in increased traffic and an increase in patient visits. However, Web sites that rely too heavily on search engines for traffic are less likely to be in the top 10 search results. Web site curators should maintain a wide focus for obtaining Web site traffic, possibly including advertising and publishing information in third party sources such as “RealSelf.”

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Hong, Ying. "Research of Personalized Intelligent Information Retrieval System Based on Agent." Advanced Materials Research 945-949 (June 2014): 3406–9. http://dx.doi.org/10.4028/www.scientific.net/amr.945-949.3406.

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To efficiently retrieve information from the vast source of the internet, search engines are required. There are some search engines that can help people to search for needed information, but they are difficult to ensure precision rate and personalization of information. To solve these problems, this paper proposed a personalized information retrieval system based on meta-search engine. This paper used multi-agent technology to construct the personalized information retrieval system, adopted user knowledge database to create and update user model and improved vector space model algorithm combining with user knowledge database which used in results ranking. Analysis and experiment show that personalized information retrieval system implemented in this paper can improve the precision ratio and can meet the needs of the user's personality requirements.

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Schlegel, Kai, Florian Stegmaier, Sebastian Bayerl, Harald Kosch, and Mario Döller. "Exploring Different Optimization Techniques for an External Multimedia Meta-Search Engine." International Journal of Multimedia Data Engineering and Management 3, no. 4 (October 2012): 31–51. http://dx.doi.org/10.4018/jmdem.2012100102.

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Along with the tremendous growth of Social Media, the variety of multimedia sharing platforms on the Web is ever growing, whereas unified retrieval issues remain unsolved. Beside unified retrieval languages and metadata interoperability issues, a crucial task in such a retrieval environment is query optimization in federated and distributed retrieval scenarios. This work introduces three different dimensions of query optimization that have been integrated in an external multimedia meta-search engine. The main innovations are query execution planning, various query processing strategies as well as a multimedia perceptual caching system.

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Hassanpour, Hamid, and Farzaneh Zahmatkesh. "An adaptive meta-search engine considering the user’s field of interest." Journal of King Saud University - Computer and Information Sciences 24, no. 1 (January 2012): 71–81. http://dx.doi.org/10.1016/j.jksuci.2011.10.004.

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M, Chandran, and Ramani A. V. "Website Quality Evaluation Based on Search Engine Queries using Web Rank Position Algorithm (WRPA)." Indonesian Journal of Electrical Engineering and Computer Science 4, no. 1 (October 1, 2016): 224. http://dx.doi.org/10.11591/ijeecs.v4.i1.pp224-230.

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<p>The research work is about to test the quality of the website and to improve the quality by analyzing the hit counts, impressions, clicks, count through rates and average positions. This is accomplished using WRPA and SEO technique. The quality of the website mainly lies on the keywords which are present in it. The keywords can be of a search query which is typed by the users in the search engines and based on these keywords, the websites are displayed in the search results. This research work concentrates on bringing the particular websites to the first of the search result in the search engine. The website chosen for research is SRKV. The research work is carried out by creating an index array of Meta tags. This array will hold all the Meta tags. All the search keywords for the website from the users are stored in another array. The index array is matched and compared with the search keywords array. From this, hit to count is calculated for the analysis. Now the calculated hit count and the searched keywords will be analyzed to improve the performance of the website. The matched special keywords from the above comparison are included in the Meta tag to improve the performance of the website. Again all the Meta tags and newly specified keywords in the index array are matched with the SEO keywords. If this matches, then the matched keyword will be stored for improving the quality of the website. Metrics such as impressions, clicks, CTR, average positions are also measured along with the hit counts. The research is carried out under different types of browsers and different types of platforms. Queries about the website from different countries are also measured. In conclusion, if the number of the clicks for the website is more than the average number of clicks, then the quality of the website is good. This research helps in improvising the keywords using WRPA and SEO and thereby improves the quality of the website easily.</p>

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Patil, Snehal. "Analysis of Health Care Services using Meta Search Engine and Web Mining." International Journal for Research in Applied Science and Engineering Technology 8, no. 9 (September 30, 2020): 291–94. http://dx.doi.org/10.22214/ijraset.2020.31438.

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NajahMahdi, Mohammed, Abdul Rahim Ahmad, and Roslan Ismail. "A Visual Exploratory Meta Data Search Engine Solution based on Cloud Computing." International Journal of Computer Applications 104, no. 8 (October 18, 2014): 21–24. http://dx.doi.org/10.5120/18223-9354.

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Cao, Ya-li, Tie-jun Huang, and Yong-hong Tian. "A ranking SVM based fusion model for cross-media meta-search engine." Journal of Zhejiang University SCIENCE C 11, no. 11 (November 2010): 903–10. http://dx.doi.org/10.1631/jzus.c1001009.

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Badhe, Neha. "Analysis of Health Care Services using Meta Search Engine and Web Mining." International Journal for Research in Applied Science and Engineering Technology 7, no. 11 (November 30, 2019): 52–54. http://dx.doi.org/10.22214/ijraset.2019.11009.

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Han, Seung-hee, and Seung-ho Sun. "The Effect of Banhasasim-tang in Cough: A Systematic Review and Meta-analysis." Journal of Internal Korean Medicine 42, no. 3 (June 30, 2021): 385–402. http://dx.doi.org/10.22246/jikm.2021.42.3.385.

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Objective: This study confirms the safety and efficacy of Banhasasim-tang (BST) against cough through systematic review and meta-analysis.Methods: PubMed, Cochrane, ScienceDirect, Wiley online library, OASIS, KISS, NDSL, RISS, Science and Technology Society Village, DBpia, CNKI, J-STAGE, and CiNii were used as search engines. The search period was from the start of search engine support to June 30. 2020. And search language was not limited. Cochrane’s risk of bias (RoB) tool was used to evaluate the quality of the studies. A meta-analysis of the total effective rate (TER), cough symptom score, and spirometry results was performed using the Review Manager program.Results: 6 studies were finally selected. The group using BST showed significant symptom relief, as the odds ratio (OR) value of TER was 5.56 times higher (95% CI: 3.50, 8.82, P<0.0001) compared to the control groups. The reported adverse effects did not occur in the intervention group. In addition, the cough symptom score and spirometry results showed that BST was more effective than Western medicine alone.Conclusion: BST can be expected to relieve cough, and it can be applied to chronic cough that is not treated with existing treatments. However, due to the low quality of the selected articles, additional high-quality RCTs will be required in the future.

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A., Sagar, Sandeep B., Deepak D., Gaurav S., and Syed Ahmed. "A Review on Patient Centric Meta-Search Engine for Quality of Care Services." International Journal of Computer Applications 182, no. 47 (April 11, 2019): 34–37. http://dx.doi.org/10.5120/ijca2019918715.

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FANG, XIANYONG, CHRISTIAN JACQUEMIN, and FRÉDÉRIC VERNIER. "WEBCONTENT VISUALIZER: A VISUALIZATION SYSTEM FOR SEARCH ENGINES IN SEMATIC WEB." International Journal of Information Technology & Decision Making 10, no. 05 (September 2011): 913–31. http://dx.doi.org/10.1142/s0219622011004646.

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Since the results from Semantic Web search engines are highly structured XML documents, they cannot be efficiently visualized with traditional explorers. Therefore, the Semantic Web calls for a new generation of search query visualizers that can rely on document metadata. This paper introduces such a visualization system called WebContent Visualizer that is used to display and browse search engine results. The visualization is organized into three levels: (1) Carousels contain documents with the same ranking, (2) carousels are piled into stacks, one for each date, and (3) these stacks are organized along a meta-carousel to display the results for several dates. Carousel stacks are piles of local carousels with increasing radii to visualize the ranks of classes. For document comparison, colored links connect documents between neighboring classes on the basis of shared entities. Based on these techniques, the interface is made of three collaborative components: an inspector window, a visualization panel, and a detailed dialog component. With this architecture, the system is intended to offer an efficient way to explore the results returned by Semantic Web search engines.

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Jbene, Mourad, Smail Tigani, Saadane Rachid, and Abdellah Chehri. "Deep Neural Network and Boosting Based Hybrid Quality Ranking for e-Commerce Product Search." Big Data and Cognitive Computing 5, no. 3 (August 13, 2021): 35. http://dx.doi.org/10.3390/bdcc5030035.

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In the age of information overload, customers are overwhelmed with the number of products available for sale. Search engines try to overcome this issue by filtering relevant items to the users’ queries. Traditional search engines rely on the exact match of terms in the query and product meta-data. Recently, deep learning-based approaches grabbed more attention by outperforming traditional methods in many circumstances. In this work, we involve the power of embeddings to solve the challenging task of optimizing product search engines in e-commerce. This work proposes an e-commerce product search engine based on a similarity metric that works on top of query and product embeddings. Two pre-trained word embedding models were tested, the first representing a category of models that generate fixed embeddings and a second representing a newer category of models that generate context-aware embeddings. Furthermore, a re-ranking step was performed by incorporating a list of quality indicators that reflects the utility of the product to the customer as inputs to well-known ranking methods. To prove the reliability of the approach, the Amazon reviews dataset was used for experimentation. The results demonstrated the effectiveness of context-aware embeddings in retrieving relevant products and the quality indicators in ranking high-quality products.

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Matošević, Goran, Jasminka Dobša, and Dunja Mladenić. "Using Machine Learning for Web Page Classification in Search Engine Optimization." Future Internet 13, no. 1 (January 2, 2021): 9. http://dx.doi.org/10.3390/fi13010009.

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This paper presents a novel approach of using machine learning algorithms based on experts’ knowledge to classify web pages into three predefined classes according to the degree of content adjustment to the search engine optimization (SEO) recommendations. In this study, classifiers were built and trained to classify an unknown sample (web page) into one of the three predefined classes and to identify important factors that affect the degree of page adjustment. The data in the training set are manually labeled by domain experts. The experimental results show that machine learning can be used for predicting the degree of adjustment of web pages to the SEO recommendations—classifier accuracy ranges from 54.59% to 69.67%, which is higher than the baseline accuracy of classification of samples in the majority class (48.83%). Practical significance of the proposed approach is in providing the core for building software agents and expert systems to automatically detect web pages, or parts of web pages, that need improvement to comply with the SEO guidelines and, therefore, potentially gain higher rankings by search engines. Also, the results of this study contribute to the field of detecting optimal values of ranking factors that search engines use to rank web pages. Experiments in this paper suggest that important factors to be taken into consideration when preparing a web page are page title, meta description, H1 tag (heading), and body text—which is aligned with the findings of previous research. Another result of this research is a new data set of manually labeled web pages that can be used in further research.

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Ding, C. H., and R. Buyya. "Guided Google: A Meta Search Engine and its Implementation Using the Google Distributed Web Services." International Journal of Computers and Applications 26, no. 3 (January 2004): 1–7. http://dx.doi.org/10.1080/1206212x.2004.11441740.

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Hamdi, Mohamed Salah. "SOMSE: A semantic map based meta-search engine for the purpose of web information customization." Applied Soft Computing 11, no. 1 (January 2011): 1310–21. http://dx.doi.org/10.1016/j.asoc.2010.04.004.

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Abdelbaki, Issam, El habib Benlahmar, and El Houssine Labriji. "Custom Fusion Methode Based on Borda." International Journal of Recent Contributions from Engineering, Science & IT (iJES) 4, no. 3 (October 26, 2016): 35. http://dx.doi.org/10.3991/ijes.v4i3.6300.

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<p class="Abstract"><span lang="EN-US">Searching for information on the Internet is not only an activity newly rediscovered, but also a strategic tool to achieve a wide variety of information. Indeed, it’s extremely important to know how to find the information quickly and efficiently. Unfortunately, the Web is so huge and so little structured, that gathering precise, fair and useful information becomes an expensive task. In order to define an information retrieval tool (meta search engine) that brings together multiple sources of information search, interest must be credited to the merger phase of search engines results. On the other hand, information search systems tend primarily to model the user with a profile and then to integrate it into the information access chain, to better meet its specific needs. </span></p><p class="Abstract"><span lang="EN-US">This paper presents a custom fusion method based on Borda method and values retrieved from the user profile. We evaluated our approach on multiple domains and we present some experimental results.</span></p>

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Reitelshöfer, Sebastian, Sebastian Meister, and Jörg Franke. "Recognition and Description of Unknown Everyday Objects by Using an Image Based Meta-Search Engine for Service Robots." Advanced Engineering Forum 19 (October 2016): 132–38. http://dx.doi.org/10.4028/www.scientific.net/aef.19.132.

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In future applications service robots will operate in complex and unstructured environments. While performing daily tasks such systems will have to recognize many different unknown objects in order to be able to conduct continuative processes. To support enhanced functionalities of a service robot system an image based meta-search engine that is accessible for a machine can be used. In this contribution the realization of an approach to determine reasonable identification results for single and multiple everyday objects by using the Google reverse image search system is described. In order to deliver convenient results for the communication of a robotic system with a human user the generated search results are post-processed and prepared in order to provide reasonable object descriptions. To enable an intuitive application, control a gesture based approach allows potential users to initialize a search procedure by pointing at an object of interest while being observed by a camera system. The performed experiments show a quite reliable detection behavior for a reasonably broad variety of everyday objects.

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Borowczyk, Henryk, Józef Błachnio, and Jarosław Spychała. "Scopus as a Meta-Source of Knowledge About Turbine Blade Damage in the Aspect of Designing an Expert Diagnostic System." Journal of KONBiN 43, no. 1 (October 1, 2017): 145–62. http://dx.doi.org/10.1515/jok-2017-0044.

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AbstractThe paper presents the concept of using the Scopus as a meta-source of knowledge about turbine blade damage in the aspect of designing an expert diagnostic system. In the first stage, the search was limited to the scope of the general term “turbine engine”, followed by a refinement of the search terms within the area of rotary machines components degradation including their construction, manufacturing, repair technology and diagnostic methods. By using EndNote software in semi-automatic mode, specific issue groups have been designated. In the second stage, a query focused on the main causes of turbine blade damage and diagnostic methods was proposed. Using the Scopus-based search and archiving tools, one can systematically update the knowledge.

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Li, Dehua, Binghang Liu, Hancheng Zheng, Xu Xiao, Zhenyu Li, Enhui Luan, Wei Li, et al. "XY-Meta: A High-Efficiency Search Engine for Large-Scale Metabolome Annotation with Accurate FDR Estimation." Analytical Chemistry 92, no. 8 (March 26, 2020): 5701–7. http://dx.doi.org/10.1021/acs.analchem.9b03355.

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Bonadio, E., and A. M. Rovati. "Use of dedicated meta-search engine infringes database right: the CJEU's stance in Innoweb v Wegener." Journal of Intellectual Property Law & Practice 9, no. 6 (April 25, 2014): 458–60. http://dx.doi.org/10.1093/jiplp/jpu053.

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Baladrón, Carlos, Alejandro Santos-Lozano, Javier M. Aguiar, Alejandro Lucia, and Juan Martín-Hernández. "Tool for filtering PubMed search results by sample size." Journal of the American Medical Informatics Association 25, no. 7 (February 1, 2018): 774–79. http://dx.doi.org/10.1093/jamia/ocx155.

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Abstract Objective The most used search engine for scientific literature, PubMed, provides tools to filter results by several fields. When searching for reports on clinical trials, sample size can be among the most important factors to consider. However, PubMed does not currently provide any means of filtering search results by sample size. Such a filtering tool would be useful in a variety of situations, including meta-analyses or state-of-the-art analyses to support experimental therapies. In this work, a tool was developed to filter articles identified by PubMed based on their reported sample sizes. Materials and Methods A search engine was designed to send queries to PubMed, retrieve results, and compute estimates of reported sample sizes using a combination of syntactical and machine learning methods. The sample size search tool is publicly available for download at http://ihealth.uemc.es. Its accuracy was assessed against a manually annotated database of 750 random clinical trials returned by PubMed. Results Validation tests show that the sample size search tool is able to accurately (1) estimate sample size for 70% of abstracts and (2) classify 85% of abstracts into sample size quartiles. Conclusions The proposed tool was validated as useful for advanced PubMed searches of clinical trials when the user is interested in identifying trials of a given sample size.

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