Journal articles: 'Search engine'

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MINASYAN, Vladimir. "Search Engine Friendliness of Search Engine Marketing Methods." Journal of Business 3, no. 1 (October 2, 2014): 47–51. http://dx.doi.org/10.31578/job.v3i1.80.

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The article examines search engine friendliness of the most popular and widely used search engine marketing (SEM) methods. In the first part, SEM methods and approaches that are in line with search engines’ official guidelines are examined and analyzed. The second part deals with popular methods which are not welcomed by search engines and are implemented by companies solely for search engine rankings manipulation purposes. Finally, the last section describes several experiments conducted on live websites in order to figure out modern search engines abilities to identify widely used deceptive practices and presents the risks associated with SEM methods which are strongly inconsistent with search engines’ official guidelines.

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Manjula, D., and T. V. Geetha. "Semantic Search Engine." Journal of Information & Knowledge Management 03, no. 01 (March 2004): 107–17. http://dx.doi.org/10.1142/s0219649204000729.

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Currently existing search engines index documents only by words and as a result, when a query can be interpreted in different senses, the irrelevant results are obtained in the midst of relevant results. A semantic search engine is proposed here which indexes documents both by words and senses and as a result tries to avoid the irrelevant results. The "crawler" traverses the worldwide web and the normalized documents are sent to the disambiguator module, which identifies the top few sense(s) of ambiguous words by employing a weighted disambiguation algorithm. The documents are then indexed by the words and the senses. The query is also disambiguated in a similar manner and retrieval is performed by matching both the sense and the word. The performance of the semantic search engine is compared against traditional word based indexing and also against the commercial search engines like Google, Yahoo, Hotbot and Lycos. The results show an impressive precision for the semantic search engine compared to other engines, particularly for ambiguous queries.

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Jha, Radhika. "Xperia Search Engine." International Journal for Research in Applied Science and Engineering Technology 11, no. 5 (May 31, 2023): 6331–40. http://dx.doi.org/10.22214/ijraset.2023.52996.

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Abstract: This research paper delves into the innerworkings of search engines and introduces Xperia, a personalized search engine aimed at enhancing information retrieval. The paper explores the fundamentaltechnologies employed by search engines, tracing their evolution and growth over time. It presents the development and implementation of Xperia, highlighting its unique feature set that goes beyond traditional search engines by providing users with not only relevant resourcelinks but also extracted information from various web sources. The paper begins with an introduction, providing the background and motivation for the research, as well as outlining the research objectives and scope. It then delves into the fundamentals of search engines, discussing their components, crawling and indexing processes, ranking algorithms, and user interfaces. The evolution of search engine technologies is examined, from the early stages to the current advancements in semantic search, natural language processing, and the incorporation of machine learning and artificial intelligence.

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Lee, Sungin, Wonhong Jang, Eunsol Lee, and Sam G. Oh. "Search engine optimization." Library Hi Tech 34, no. 2 (June 20, 2016): 197–206. http://dx.doi.org/10.1108/lht-02-2016-0014.

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Purpose – The purpose of this paper is to examine the effect of, and identify core techniques of, search engine optimization (SEO) techniques applied to the web (http://lg-sl.net) and mobile (http//m.lg-sl.net) Science Land content and services at LG Sangnam Library in Korea. Design/methodology/approach – In accordance with three major SEO guidelines, ten SEO techniques were identified and applied, and their implications were extracted on three areas: improved search engine accessibility, increased relevance between site content and search engine keywords, and improved site credibility. The effects were quantitatively analyzed in terms of registered search engine keywords and influx of visits via search engines. Findings – This study shows that SEO techniques help increase the exposure of the library services and the number of visitors through search engines. Practical implications – SEO techniques have been applied to a few non-Korean information service organizations, but it is not a well-accepted practice in Korean libraries. And the dominant search engines in Korea have published their own SEO guidelines. Prior to this study, no significant endeavors have been undertaken in the context of Korean library services that have adopted SEO techniques to boost exposure of library services and increase user traffics. Originality/value – This is the first published study that has applied optimized SEO techniques to Korean web and mobile library services, in order to demonstrate the usefulness of the techniques for maximized exposure of library content.

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Li, Yi, Zhihui Yuan, Yujie Li, and Jing Liu. "Factors influencing search engine usage behavior." Social Behavior and Personality: an international journal 46, no. 1 (January 9, 2018): 1–10. http://dx.doi.org/10.2224/sbp.6211.

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We analyzed the effect of individual factors, contextual factors, and perception of search engine advertising on users' search engine usage behavior. The sample comprised 404 Chinese who used search engines in the context of their paid employment. Results showed that (a) perceived search skills and perceived search engine reliance significantly and positively impacted users' general search engine usage, (b) perceived advertising clutter reduced the beneficial effects of perceived search skills on users' general search engine usage, (c) users with higher perceived search engine reliance preferred search engines to other online search methods, and (d) prior negative experience reduced the positive link between perceived search engine reliance and users' specific search engine usage. Our findings suggest that search engine designers and operators should focus on individual and contextual factors influencing search engine usage behavior, and should consider users' perception of advertising on search engine programs.

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Goyal, Harsh, and Komal kapoor. "Search Engine Optimization with Google." International Journal for Research in Applied Science and Engineering Technology 10, no. 12 (December 31, 2022): 496–501. http://dx.doi.org/10.22214/ijraset.2022.47904.

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Abstract: This paper is a finished survey that how various strategies of Search Engine Optimization (SEO) can help to improve product marketing. Search engines have now become an important channel for increasing SMEs’ global reach and helps companies to compete with other and large companies. SMEs are using search engine optimization to improve their online visibility as a result (SEO). With the help of Search Engine Optimization small companies can actually now compete with the large companies and can appear ahead of large. The main objective of every website to list at the top of all thelinks on search engines. So, search engine optimization is an art which helps to improves a website’s visibility in the search engine results. Search engines makes the business environment more transparent and more competitive. For data collection used literature survey. The findings of this study show that using an SEO strategy can significantly enhance product marketing.

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Stevenson, Valerie. "Search Engine Update." Legal Information Management 1, no. 3 (2001): 28–31. http://dx.doi.org/10.1017/s1472669600000566.

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Looking back to 1999, there were a number of search engines which performed equally well. I recommended defining the search strategy very carefully, using Boolean logic and field search techniques, and always running the search in more than one search engine. Numerous articles and Web columns comparing the performance of different search engines came to different conclusions on the ‘best’ search engines. Over the last year, however, all the speakers at conferences and seminars I have attended have recommended Google as their preferred tool for locating all kinds of information on the Web. I confess that I have now abandoned most of my carefully worked out search strategies and comparison tests, and use Google for most of my own Web searches.

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Takama, Yasufumi, Yanjun Zhu, Shogo Kori, Koichi Yamaguchi, Lieu-Hen Chen, and Hiroshi Ishikawa. "Design of Context Search Engine Based on Analysis of User’s Search Intentions." Journal of Advanced Computational Intelligence and Intelligent Informatics 20, no. 6 (November 20, 2016): 910–18. http://dx.doi.org/10.20965/jaciii.2016.p0910.

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The context search engine has been studied for answering trend-related queries. As trend information is obtained from temporal data, which is common in many applications, the context engine is expected to be available regardless of domains. When using existing search engines, it is supposed that users submit a series of queries based on search intention. Therefore, search functions of the context search engine should be designed based on the user’s potential search intention. To analyze user’s behavior in information retrieval, this paper conducted experiments using existing Web search engines. The experimental result is analyzed, based on which the design of a context search engine is described. As another contribution of this paper, new types of temporal variations which can be used to specify queries of the context search engine are also proposed. The results of user experiments confirmed the usability of the proposed temporal variations.

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de Cornière, Alexandre. "Search Advertising." American Economic Journal: Microeconomics 8, no. 3 (August 1, 2016): 156–88. http://dx.doi.org/10.1257/mic.20130138.

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Search engines enable advertisers to target consumers based on the query they have entered. In a framework in which consumers search sequentially after having entered a query, I show that such targeting reduces search costs, improves matches and intensifies price competition. However, a profit-maximizing monopolistic search engine imposes a distortion by charging too high an advertising fee, which may negate the benefits of targeting. The search engine also has incentives to provide a suboptimal quality of sponsored links. Competition among search engines can increase or decrease welfare, depending on the extent of multi-homing by advertisers. (JEL D43, D83, L13, L86, M37)

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Radadiya, Jitendrakumar P., Kalpesh Rasiklal Rakholiya, and Dr Dhaval R. Kathiriya. "Intelligent Sementic Web Search Engine." International Journal of Scientific Research 1, no. 7 (June 1, 2012): 34–35. http://dx.doi.org/10.15373/22778179/dec2012/13.

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Sharma, Dilip Kumar, and A. K. Sharma. "Search Engine." International Journal of Information Communication Technologies and Human Development 3, no. 2 (April 2011): 38–51. http://dx.doi.org/10.4018/ijicthd.2011040103.

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ICT plays a vital role in human development through information extraction and includes computer networks and telecommunication networks. One of the important modules of ICT is computer networks, which are the backbone of the World Wide Web (WWW). Search engines are computer programs that browse and extract information from the WWW in a systematic and automatic manner. This paper examines the three main components of search engines: Extractor, a web crawler which starts with a URL; Analyzer, an indexer that processes words on the web page and stores the resulting index in a database; and Interface Generator, a query handler that understands the need and preferences of the user. This paper concentrates on the information available on the surface web through general web pages and the hidden information behind the query interface, called deep web. This paper emphasizes the Extraction of relevant information to generate the preferred content for the user as the first result of his or her search query. This paper discusses the aspect of deep web with analysis of a few existing deep web search engines.

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Bukhor, Saiful i. "Analisis Perbandingan Fitur Search Engine." INFORMAL: Informatics Journal 3, no. 1 (February 25, 2019): 17. http://dx.doi.org/10.19184/isj.v3i1.9850.

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Search engines are used in the web as a tool for information retrieval. Web Server is a large warehouse of heterogeneous and unstructured data so that to filter out relevant information from people, a search engine is needed. Search engines usually consist of page repositories, indexing modules, query modules and ranking modules. Search engines do not work alone, besides that there is a web browser that supports the work of this search engine to be more optimal. A browser is software that is run on a user's computer (user) that displays web documents or information taken from a web server [1]. A browser is the type of intermediary the user uses most often. This paper aims to analyze three search engines namely Google, Yahoo, and Bing based on existing features. These features include web search, image search, video search, news search, route search, book search, change search settings, display number of views, shopping, language translator. Google stands as the best search engine among all search engines, which works using the Page Rank algorithm. Page Rank is a numerical value that determines the importance of a web page by calculating the number of backlinks.

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Ivanechko, N., V. Dudar, and V. Pavelko. "Search engine marketing." Galic'kij ekonomičnij visnik 74, no. 1 (2022): 158–62. http://dx.doi.org/10.33108/galicianvisnyk_tntu2022.01.158.

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The article considers the elements of Internet marketing. It is determined that search marketing is a search engine optimization and a modern method of site promotion by optimizing the resource for social networks. The classification of search queries is carried out according to the following features: query competitiveness, query frequency, query value, query geodependence, query regionality, query seasonality, query time of day. It is established that the sign of competitiveness of the request is divided into highly competitive, medium competitive, low competitive; the query frequency attribute is divided into high-frequency, medium-frequency, low-frequency; the degree of value of the request is divided into commercial and non-commercial; sign of geodependence of the request for non-independent and geo-dependent requests. The advantages and disadvantages of SEO and contextual advertising are found. Advantages of SEO are as follows: the presence of the site in search engines adds credibility and confidence in consumers; has good clickthrough rate; can show simultaneously several links of the same site in the TOP 10; in the long-term strategy the cheapest of all channels to attract traffic to the site; when you stop promoting the site, search positions are stored for up to 1 year; the effect of promotion affects all search engines; there is no threat to «convene» the budget by competitors. Advantages of contextual advertising are: fast traffic; full control over the ads and the ability to make changes quickly; independence from updates of search engine algorithms; the ability to set fixed daily budget, after reaching the set metric ads will stop running. The main disadvantages of SEO are: long lead times; change in the algorithm by search engine can dramatically affect the result; threat of sanctions against the site; it is impossible to predict the actions of the search engine in advance. The main disadvantages of contextual advertising are the following: the consumer understands that he goes to the company's website for advertising; when the money runs out, consumers will stop going to the site; in the end it can be very expensive; cost-per-click is constantly changing. The common disadvantage of these two elements is the lack of guarantees for the purchase of goods or services in any case.

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Ivanechko, N., V. Dudar, and V. Pavelko. "Search engine marketing." Galic'kij ekonomičnij visnik 74, no. 1 (2022): 158–62. http://dx.doi.org/10.33108/galicianvisnyk_tntu2022.01.158.

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The article considers the elements of Internet marketing. It is determined that search marketing is a search engine optimization and a modern method of site promotion by optimizing the resource for social networks. The classification of search queries is carried out according to the following features: query competitiveness, query frequency, query value, query geodependence, query regionality, query seasonality, query time of day. It is established that the sign of competitiveness of the request is divided into highly competitive, medium competitive, low competitive; the query frequency attribute is divided into high-frequency, medium-frequency, low-frequency; the degree of value of the request is divided into commercial and non-commercial; sign of geodependence of the request for non-independent and geo-dependent requests. The advantages and disadvantages of SEO and contextual advertising are found. Advantages of SEO are as follows: the presence of the site in search engines adds credibility and confidence in consumers; has good clickthrough rate; can show simultaneously several links of the same site in the TOP 10; in the long-term strategy the cheapest of all channels to attract traffic to the site; when you stop promoting the site, search positions are stored for up to 1 year; the effect of promotion affects all search engines; there is no threat to «convene» the budget by competitors. Advantages of contextual advertising are: fast traffic; full control over the ads and the ability to make changes quickly; independence from updates of search engine algorithms; the ability to set fixed daily budget, after reaching the set metric ads will stop running. The main disadvantages of SEO are: long lead times; change in the algorithm by search engine can dramatically affect the result; threat of sanctions against the site; it is impossible to predict the actions of the search engine in advance. The main disadvantages of contextual advertising are the following: the consumer understands that he goes to the company's website for advertising; when the money runs out, consumers will stop going to the site; in the end it can be very expensive; cost-per-click is constantly changing. The common disadvantage of these two elements is the lack of guarantees for the purchase of goods or services in any case.

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Zhang, Jin, Xin Cai, Taowen Le, Wei Fei, and Feicheng Ma. "A Study on Effective Measurement of Search Results from Search Engines." Journal of Global Information Management 27, no. 1 (January 2019): 196–221. http://dx.doi.org/10.4018/jgim.2019010110.

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This article describes how as internet technology continues to change and improve lives and societies worldwide, effective global information management becomes increasingly critical, and effective Internet information retrieval systems become more and more significant in providing Internet users worldwide with accurate and complete information. Search engine evaluation is an important research field as search engines directly determine the quality of information users' Internet searches. Relevance-decrease pattern/model plays an important role in search engine result evaluation. This research studies effective measurement of search results through investigating relevance-decrease patterns of search results from two popular search engines: Google and Bing. The findings can be applied to relevance-evaluation of search results from other information retrieval systems such as OPAC, can help make search engine evaluations more accurate and sound, and can provide global information management personnel with valuable insights.

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Paraskevas, Alexandros, Ioannis Katsogridakis, Rob Law, and Dimitrios Buhalis. "Search Engine Marketing: Transforming Search Engines into Hotel Distribution Channels." Cornell Hospitality Quarterly 52, no. 2 (January 27, 2011): 200–208. http://dx.doi.org/10.1177/1938965510395016.

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Zilincan, Jakub. "SEARCH ENGINE OPTIMIZATION." CBU International Conference Proceedings 3 (September 19, 2015): 506–10. http://dx.doi.org/10.12955/cbup.v3.645.

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Search engine optimization techniques, often shortened to “SEO,” should lead to first positions in organic search results. Some optimization techniques do not change over time, yet still form the basis for SEO. However, as the Internet and web design evolves dynamically, new optimization techniques flourish and flop. Thus, we looked at the most important factors that can help to improve positioning in search results. It is important to emphasize that none of the techniques can guarantee high ranking because search engines have sophisticated algorithms, which measure the quality of webpages and derive their position in search results from it. Next, we introduced and examined the object of the optimization, which is a particular website. This web site was created for the sole purpose of implementing and testing all the main SEO techniques. The main objective of this article was to determine whether search engine optimization increases ranking of website in search results and subsequently leads to higher traffic. This research question is supported by testing and verification of results. The last part of our article concludes the research results and proposes further recommendations.

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Zhou, Bao Jian, Wei Qi, Li Gang Chen, and Qiang Ye. "Online Sponsored Search Budget Allocation across Search Engines: A Simulation Analysis." Applied Mechanics and Materials 577 (July 2014): 926–30. http://dx.doi.org/10.4028/www.scientific.net/amm.577.926.

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Recently, sponsored search has been rapidly growing which increase tremendous interests in improving performance in search engine marketplace. The complexity of market dynamics makes it difficult for advertisers to maximizing the effect of advertising. Simulation analysis is a more viable option than real world testing especially in fast accomplishing different experiments and effectively prompting decision making supports. In this paper, the sponsored search budget allocation problem model integrated with quality score for single search engine has been explored and then extended to multiple quality-based search engines. Also, several advertising policies have been proposed and verified under the general simulation framework in both single and multiple search engine scenarios.

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Gunjan, Vinit Kumar, Pooja, Monika Kumari, Amit Kumar, and Allam Appa Rao. "Search Engine Optimization with Google." Asian Journal of Engineering and Applied Technology 1, no. 1 (May 5, 2012): 36–42. http://dx.doi.org/10.51983/ajeat-2012.1.1.2503.

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Search engine optimization is a strategical technique to take a web document in top search results of a search engine. Online presence of an organisation is not only an easy way to reach among the target users but it may be profitable too if optimization is done keeping in view of the target users as of the reason that most of the time users search out with the keywords of their use (Say; Ph.D in web technology) rather than searching the organisation name, and if the page link comes in the top positions then the page may be profitable. This work describes the tweaks of taking the page on top position in Google by increasing the Page rank which may result in the improved visibility and profitable deal for an organisation. Google is most user friendly search engine proved for the Indian users which gives user oriented results. In addition, most of other search engines use Google search patterns so we have concentrated on it. So, if a page is optimised in Google it is optimised for most of the search engines.

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ALMUKHTAR, Firas, Nawzad MAHMOODD, and Shahab KAREEM. "SEARCH ENGINE OPTIMIZATION: A REVIEW." Applied Computer Science 17, no. 1 (March 30, 2021): 70–80. http://dx.doi.org/10.35784/acs-2021-07.

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The Search Engine has a critical role in presenting the correct pages to the user because of the availability of a huge number of websites, Search Engines such as Google use the Page Ranking Algorithm to rate web pages according to the nature of their content and their existence on the world wide web. SEO can be characterized as methodology used to elevate site keeping in mind the end goal to have a high rank i.e., top outcome. In this paper the authors present the most search engine optimization like (Google, Bing, MSN, Yahoo, etc.), and compare by the performance of the search engine optimization. The authors also present the benefits, limitation, challenges, and the search engine optimization application in business.

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Kaur, Gurneet. "ROLE AND IMPORTANCE OF SEARCH ENGINE OPTIMIZATION." International Journal of Research -GRANTHAALAYAH 5, no. 6 (June 30, 2017): 147–51. http://dx.doi.org/10.29121/granthaalayah.v5.i6.2017.2007.

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Search Engines are an indispensible platform for users all over the globe to search for relevant information online. Search Engine Optimization (SEO) is the exercise of improving the position of a website in search engine rankings, for a chosen set of keywords. SEO is divided into two parts: On-Page and Off-Page SEO. In order to be successful, both the areas require equal attention. This paper aims to explain the functioning of the search engines along with the role and importance of search engine optimization.

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Kumar, Kailash, and Abdulaziz Al-Besher. "Critical Analysis of Major Search Engines." Journal of Computational and Theoretical Nanoscience 16, no. 9 (September 1, 2019): 3712–16. http://dx.doi.org/10.1166/jctn.2019.8239.

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This paper examines the overlapping of the results retrieved between three major search engines namely Google, Yahoo and Bing. A rigorous analysis of overlap among these search engines was conducted on 100 random queries. The overlap of first ten web page results, i.e., hundred results from each search engine and only non-sponsored results from these above major search engines were taken into consideration. Search engines have their own frequency of updates and ranking of results based on their relevance. Moreover, sponsored search advertisers are different for different search engines. Single search engine cannot index all Web pages. In this research paper, the overlapping analysis of the results were carried out between October 1, 2018 to October 31, 2018 among these major search engines namely, Google, Yahoo and Bing. A framework is built in Java to analyze the overlap among these search engines. This framework eliminates the common results and merges them in a unified list. It also uses the ranking algorithm to re-rank the search engine results and displays it back to the user.

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RAKHSHAN, ARASH, LAWRENCE B. HOLDER, and DIANE J. COOK. "STRUCTURAL WEB SEARCH ENGINE." International Journal on Artificial Intelligence Tools 13, no. 01 (March 2004): 27–44. http://dx.doi.org/10.1142/s0218213004001405.

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We present a new approach in web search engines. The web creates new challenges for information retrieval. The vast improvement in information access is not the only advantage resulting from the keyword search. Additionally, much potential exists for analyzing interests and relationships within the structure of the web. The creation of a hyperlink by the author of a web page explicitly represents a relationship between the source and destination pages which demonstrates the hyperlink structure between web pages. Our web search engine searches not only for the keywords in the web pages, but also for the hyperlink structure between them. Comparing the results of structural web search versus keyword-based search indicates an improved ability to access desired information. We also discuss steps toward mining the queries input to the structural web search engine.

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Isbandi, Isbandi, Zatnika Zatnika, and Edwin Triyatna. "IMPLEMENTASI TEKNIK SEO (SEARCH ENGINE OPTIMIZATION) UNTUK OPTIMASI WEBSITE PENJUALAN DI LESTARI JAYA MEBEL." EDUSAINTEK: Jurnal Pendidikan, Sains dan Teknologi 10, no. 3 (June 30, 2023): 1047–60. http://dx.doi.org/10.47668/edusaintek.v10i3.867.

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The background of this research is to help Micro, Small and Medium Enterprises (MSMEs) which need promotional media in the form of websites. Therefore the author has an idea to implement SEO (Search Engine Optimization). SEO (Search Engine Optimization) is a technique for improving a website in the search results of search engines such as Google, Bing, etc. SEO (Search Engine Optimization) is an important marketing strategy for increasing the visibility of a website and the number of organic visitors to the intended site. This research uses quantitative methods. Data collected by online survey and interview techniques. Toko Lestari Jaya Mebel has not been ranked optimally enough on search engines or search engines, with the implementation of SEO (Search Engine Optimization) techniques it is hoped that it can improve the website's position on search engines. So that the site can be easily found and compete with competitors, and is expected to increase sales.

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Shahzad, Asim, Deden Witarsyah Jacob, Nazri Mohd Nawi, Hairulnizam Mahdin, and Marheni Eka Saputri. "The new trend for search engine optimization, tools and techniques." Indonesian Journal of Electrical Engineering and Computer Science 18, no. 3 (June 1, 2020): 1568. http://dx.doi.org/10.11591/ijeecs.v18.i3.pp1568-1583.

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<span>Search Engines are used to search any information on the internet. <br /> The primary objective of any website owner is to list their website at the top of all the results in Search Engine Results Pages (SERPs). Search Engine Optimization is the art of increasing visibility of a website in Search Engine Result Pages. This art of improving the visibility of website requires the tools and techniques; This paper is a comprehensive survey of how a Search Engine (SE) works, types and parts of Search Engine and different techniques and tools used for Search Engine Optimization (SEO.) In this paper, we will discuss the current tools and techniques in practice for Search Engine Optimization.</span>

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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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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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Laddha, Shilpa S., and Pradip M. Jawandhiya. "Semantic Search Engine." Indian Journal of Science and Technology 10, no. 21 (February 1, 2017): 1–6. http://dx.doi.org/10.17485/ijst/2017/v10i23/115568.

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Vázquez, José. "Science Search Engine." American Biology Teacher 66, no. 1 (January 1, 2004): 70. http://dx.doi.org/10.2307/4451620.

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Vyas, Pooja, Archith Menon, Aditya Ravindran, and Samit Shivadekar. "Ubiquitous Search Engine." International Journal of Computer Applications 117, no. 20 (May 20, 2015): 24–27. http://dx.doi.org/10.5120/20673-3429.

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Editorial, Article. "Credible Search Engine." Bibliotekovedenie [Russian Journal of Library Science], no. 4 (July 27, 2011): 132–33. http://dx.doi.org/10.25281/0869-608x-2011-0-4-132-133.

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Veglis and Giomelakis. "Search Engine Optimization." Future Internet 12, no. 1 (December 31, 2019): 6. http://dx.doi.org/10.3390/fi12010006.

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Jayavel, Senthil, Margret Anouncia, and Abhinav Kapoor. "Semantic Search Engine." International Journal of Recent Contributions from Engineering, Science & IT (iJES) 1, no. 2 (November 2, 2013): 19. http://dx.doi.org/10.3991/ijes.v1i2.2711.

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Corrigan, Catherine P. "Search engine secrets." Nursing 45, no. 9 (September 2015): 1–3. http://dx.doi.org/10.1097/01.nurse.0000463659.71155.06.

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Stern, Ewan. "Search-engine power." New Scientist 206, no. 2759 (May 2010): 26. http://dx.doi.org/10.1016/s0262-4079(10)61126-8.

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Anthes, Gary. "Search engine agendas." Communications of the ACM 59, no. 4 (March 23, 2016): 19–21. http://dx.doi.org/10.1145/2892712.

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., Deepthi K. "SEARCH ENGINE OPTIMIZATION." International Journal of Research in Engineering and Technology 06, no. 01 (January 25, 2017): 84–87. http://dx.doi.org/10.15623/ijret.2017.0601016.

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Abbas, Ahmed Abdulrudah. "University Search Engine." Journal of Kufa for Mathematics and Computer 1, no. 2 (October 30, 2010): 46–53. http://dx.doi.org/10.31642/jokmc/2018/010205.

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In this paper, I present a new search engine system to find the home page of any university. This system ( University Search Engine ) depends on building a database that has information which it used to access the home page of any university by entering a keyword. This keyword is used to generate a hyperlink for this university . In fact, most students use the Internet for accessing and using the webpages; therefore, the target of this research is to build a new search engine that makes the students access the home pages of the universities easily. When testing the system ( UniversitySearch Engine ) it succeeds in accessing the Iraqi universities ( kufa university, Baghdaduniversity etc) and give the exact home pages for these universities. It is also tested for foreign universities ( University Saine Malaysia, University Collage Lincoln etc), and it succeeds in giving the exact home pages for these universities. I build my system ( University Search Engine ) undervisual basic 6 language (VB6) and Microsoft Access 2003.

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Duka, Mariusz, Marek Sikora, and Artur Strzelecki. "From Web Catalogs to Google: A Retrospective Study of Web Search Engines Sustainable Development." Sustainability 15, no. 8 (April 17, 2023): 6768. http://dx.doi.org/10.3390/su15086768.

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This study presents a review of search engines and search engine optimization and shows how the search engine landscape relates to sustainable development. We have used a narrative review research method and described three main topics: the past and present of web catalogs and search engines; current knowledge about the dominant types of search results presented in Google search; and methods of search engine optimization. Technical elements of important website areas related to technical website auditing are discussed. We summarize our research with several key findings on how web search engines are involved in sustainable development and offer a glimpse into the future use of web searching with the help of artificial intelligence chats and prompt engineering.

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Mager, Astrid. "European Search? How to counter-imagine and counteract hegemonic search with European search engine projects." Big Data & Society 10, no. 1 (January 2023): 205395172311631. http://dx.doi.org/10.1177/20539517231163173.

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This article investigates how developers of alternative search engines challenge increasingly corporate imaginaries of digital futures by building out counter-imaginaries of search engines devoted to social values instead of mere profit maximization. Drawing on three in-depth case studies of European search engines, it analyzes how search engine developers counter-imagine hegemonic search, what social values support their imaginaries, and how they are intertwined with their sociotechnical practices. This analysis shows that notions like privacy, independence, and openness appear to be fluid, context-dependent, and changing over time, leading to a certain “value pragmatics” that allows the projects to scale beyond their own communities of practice. It further shows how European values, and broader notions of Europe as “unified or pluralistic,” are constructed and co-produced with developers’ attempts to counter-imagine and counteract hegemonic search. To conclude, I suggest three points of intervention that may help alternative search engine projects, and digital technologies more generally, to not only make their counter-imaginaries more powerful, but also acquire the necessary resources to build their technologies and infrastructures accordingly. I finally discuss how “European values,” in all their richness and diversity, can contribute to this undertaking.

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Reddy, Mr D. Ranadeep. "Creating Search Engine Using Machine Learning Methods." International Journal for Research in Applied Science and Engineering Technology 12, no. 4 (April 30, 2024): 667–72. http://dx.doi.org/10.22214/ijraset.2024.59841.

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Abstract: The vast and ever-expanding amount of information available in the WWW has led to the widespread usage of search engines for data retrieval. It can be challenging to locate information that is actually relevant and helpful, even while ordinary search engines offer users an intuitive interface for entering queries and retrieving web page links as results. To rectify that problem, which paper presents a novel search engine that work ML techniques. The target is to come up users with most relevant web sites when they query the engine. The suggested search engine improves the relevancy and accuracy of search results by utilizing machine learning algorithms. This system seeks to grasp user intent, adjust to individual preferences, and deliver contextually relevant information by going beyond the bounds of traditional search engines. By using machine learning models, the search engine may learn dynamically and enhance the standard of its results over time by continuously refining its understanding. More sophisticated and adaptable search engines are being developed as an outcome of these combination of state-of-the-art machine learning libraries, tools for processing natural language, and effective indexing systems. The target of the research is too advance information retrieval systems by providing a more advanced and user-focused method of tackling the difficulties presented by the WWW's immense scope

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Zhang, Qing Hua. "Existing Condition Analysis on Bad Faith of Auto Bidding for Search Engine Keywords." Key Engineering Materials 439-440 (June 2010): 128–33. http://dx.doi.org/10.4028/www.scientific.net/kem.439-440.128.

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With rapid development of search engine users, the auto bidding for search engine keywords is stealthily rising and such kind of service is now essentially being conducted on the majority of existing search engines. For merchants, users and even the search engine service suppliers, auto bidding is of many advantages, which is also thought it has brought forth serious phenomenon of bad faith in terms of such kind of similar search websites, leading to a crisis of confidence. This text is intended to give it a full analysis on the various problems of bad faith resulted from the auto bidding for search engine keywords. And it is in consideration of the huge controlling forcing and social influence of the search engines, there lies a great need in strengthening the closer government supervision. While guaranteeing a healthy and orderly development of search engine, our purpose is to render back an honest and clean searching environment of internet information to the public.

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Ordoñez, Cristian Camilo, Armando Ordoñez, and Hugo Ordoñez Erazo. "DEVA a Methodology based on User-Centered Design for the development of a search system for judicial documents." Investigación e Innovación en Ingenierías 10, no. 1 (May 23, 2022): 178–88. http://dx.doi.org/10.17081/invinno.10.1.5641.

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Summary: This work provides a methodology to analyze user preferences regarding the components that a judicial search engine should include. We validate this methodology by developing a search system. Starting from initial characteristics, we designed a search prototype. A test was then applied to identify whether the search engine meets the user's needs. The prototype developed was compared to other next-generation search engines in terms of user satisfaction and accuracy. The results show that our proposal outperforms other search engines. Objective: Define and implement the components for the development of a judicial search engine. Methodology: The methodology consists of in: Definition: Includes a review of the state of the art of the technologies associated with the project. Prototype development: Different modules and components of the system are developed here. Evaluation: focused on usability and user satisfaction. Results: The characteristics and elements necessary for the search engine were identified. To this end, Benchmarking on general aspects and components of jurisprudence search engines was carried out. Additionally, a survey was conducted with 79 legal experts. Finally, a use test was carried out. Conclusions: A prototype of the search engine was designed according to the characteristics declared by the users. This prototype showed optimal usability and navigation because it was designed considering the needs of the user's jurisprudence. Its interfaces are easy to understand and its filters make the search process more agile and precise. Finally, the developed search engine offers a good experience to the users.

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Zhang, Hong, Yan Hong Ma, Wei Jun Ma, and Zhong Xian Bao. "Study of Distributed Personalized Search Engine." Advanced Materials Research 756-759 (September 2013): 1035–39. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.1035.

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Combining distributed computing and data mining techniques, a distributed personalized search engine is put forward to solve the the problems current search engines faced. It has described the theoretical model and algorithmic processing. Under the Hadoop, a distributed platform processing information with Java, the key parts are programmed and implemented. The experimental results show that this theoretical model can improve the accuracy and speed of the user's queries so it can improve the retrieval performance of the search engine.

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Aryani, Diah, Shine Pintor Siolemba Patiro, Aji Setiawan, and Budi Tjahjono. "Comparative Analysis Of On-Page And Off-Page White Hat Search Engine Optimization (SEO) Techniques On Website Popularity." International Journal of Science, Technology & Management 4, no. 3 (May 31, 2023): 527–33. http://dx.doi.org/10.46729/ijstm.v4i3.815.

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Currently, the use of Search Engine Optimization (SEO) has become a necessity to achieve better ranking results from Search Engines known as Search Engine Optimization, which is a collection of techniques for positioning a site so that it can be indexed by search engines and get a position in search engine results—result Pages (SERPs). Based on Globalstatistics data, there has been an increase in internet users in Indonesia who search for products through the search engine market, which has reached 97.38%. This study aims to increase the visibility of a website or multi-umah web page in search results to get a higher ranking on the SERPs in the search results. search results using white hat SEO by comparing on-page techniques and off-page techniques through descriptive qualitative methods, then analyzed using Google Search Console and Google Analytics tools to understand keyword performance, behavior, and customer interests on the umahmulti.biz.id website

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Salamun, Salamun, Yessi Jusman, and Widdya Rahmalina. "POWER SEARCH DALAM MENGGUNAKAN SEARCH ENGINE." Jurnal Pengabdian Masyarakat Multidisiplin 1, no. 1 (January 11, 2018): 65–71. http://dx.doi.org/10.36341/jpm.v1i1.398.

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Mesin pencari web / web search engine adalah program komputer yang dirancang untuk melakukan pencarian atas berkas-berkas yang tersimpan dalam layanan www, ftp, publikasi milis, ataupun news group dalam sebuah ataupun sejumlah komputer dalam suatu jaringan. Dalam menggunakan fasilitas mesin pencarian seperti google harus dengan beberapa cara agar bisa langsung mendapatkan informasi atau file yang di inginkan. Dalam kegiatan ini siswa/I akan di ajarkan bagaimana cara mengguanakan mesin pencarian raksasa saat ini seperti google secara efektif dan terarah. Metode yang digunakan untuk melakukan pelatihan yaitu memberikan langsung ke pada SMK dan SMA pengetahuan dengan menggunakan perangkat komputer/laptop dan jaringan internet. Untuk pencapain tujuan tersebut maka kegiatan pengabdian akan dilakukan secara langsung dalam ruangan yang diikuti oleh 35 orang siswa. Adapun untuk menggunakan mesin pencarian yang efektif dan efisien dengan cara menggunakan kata kunci yang tepat agar apa yang tampilkan sesuai dengan yang di cari seperti, mencari file dengan type tertentu maka gunakan kata kunci yang memiliki type dari file tersebut seperti doc, pdf, ppt dan type file lainnya.

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Hearst, M. A., A. Divoli, H. Guturu, A. Ksikes, P. Nakov, M. A. Wooldridge, and J. Ye. "BioText Search Engine: beyond abstract search." Bioinformatics 23, no. 16 (June 1, 2007): 2196–97. http://dx.doi.org/10.1093/bioinformatics/btm301.

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Ebnehoseini, Zahra. "HEALTH INFORMATION SEARCH ENGINE THE NEW TOOLS OF HEALTH LITERACY." Medical Technologies Journal 1, no. 4 (November 29, 2017): 107. http://dx.doi.org/10.26415/2572-004x-vol1iss4p107-107.

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Introduction: Access to Health Information is very essential for promoting health literacy, self-care, shared decision making, medication adherence. The Internet is one of the main resources of health information. Many studies showed the main gateway for seeking health information was search engines. But finding qualified health information is a challenge. Therefore, this study aimed to introduce top health Searches engines and review their features. Methods: According to the literature review, 10 health Searches engines were selected. Common features of each search engine, such as the ability to create profiles, the type of health information provided, target users, health information sources contained in the search engine, and the unique feature and other features, were reviewed and the comparison table was provided. A common search scenario was also tested on all search engines and the result of the data retrieval was reported by the search engine. Results: health Searches engine like that PubMed، Med scape، McGraw-Hill Medical، iMediSearch، medicin.net, Hardin.Md، Health line ، EMedicine، Merck and Ovid were chosen and reported. Conclusion: The results of this study can help users such as patient to choose a valid health searches engine and also help them to find health searches engine appropriate for their health problem and know what features in health website is important.

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Unadkat, Rimpal. "Survey Paper on Semantic Web." International Journal of Advanced Pervasive and Ubiquitous Computing 7, no. 4 (October 2015): 13–17. http://dx.doi.org/10.4018/ijapuc.2015100102.

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The World Wide Web (WWW) allows the people to share the information (data) from the large database repositories globally. The tremendous growth in the volume of data and with the terrific growth of number of web pages, traditional search engines now days are not appropriate and not suitable anymore. Search engine is the most important tool to discover any information in World Wide Web. Semantic Search Engine is born of traditional search engine to overcome the above problem. However, to overcome this problem in search engines to retrieve meaningful information intelligently, semantic web technologies are playing a major role. In this paper the authors present survey on the role of search engines in intelligent web, Background, Challenges and some issues.

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G, Shravya, and Prof Smitha G R. "Image Search Engine and Individual Profile Building." International Journal of Innovative Research in Computer Science & Technology 7, no. 3 (May 2019): 75–78. http://dx.doi.org/10.21276/ijircst.2019.7.3.8.

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Journal articles on the topic 'Search engine'

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