Zeitschriftenartikel: „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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D.Minnie and S.Srinivasan. "META SEARCH ENGINE WITH AN INTELLIGENT INTERFACE FOR INFORMATION RETRIEVAL ON MULTIPLE DOMAINS." International Journal of Computer Science, Engineering and Information Technology (IJCSEIT) 1, no. 4 (October 31, 2011): 37–45. https://doi.org/10.5281/zenodo.3542608.

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This paper analyses the features of Web Search Engines, Vertical Search Engines, Meta Search Engines, and proposes a Meta Search Engine for searching and retrieving documents on Multiple Domains in the World Wide Web (WWW). A web search engine searches for information in WWW. A Vertical Search provides the user with results for queries on that domain. Meta Search Engines send the user’s search queries to various search engines and combine the search results. This paper introduces intelligent user interfaces for selecting domain, category and search engines for the proposed Multi-Domain Meta Search Engine. An intelligent User Interface is also designed to get the user query and to send it to appropriate search engines. Few algorithms are designed to combine results from various search engines and also to display the results.

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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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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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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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Asim, Shahzad, Witarsyah Jacob Deden, Mohd Nawi Nazri, Mahdin Hairulnizam, and Eka Saputri Marheni. "The new trend for search engine optimization, tools and techniques." Indonesian Journal of Electrical Engineering and Computer Science (IJEECS) 18, no. 3 (June 1, 2020): 1568–83. https://doi.org/10.11591/ijeecs.v18.i3.pp1568-1583.

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Search Engines are used to search any information on the internet. 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.

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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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Jose, Jeeva, and Lal P. Sojan. "Analysis of the Temporal Behaviour of Search Engine Crawlers at Web Sites." COMPUSOFT: An International Journal of Advanced Computer Technology 02, no. 06 (June 30, 2013): 136–42. https://doi.org/10.5281/zenodo.14602851.

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Web log mining is the extraction of web logs to analyze user behaviour at web sites. In addition to user information, web logs provide immense information about search engine traffic and behaviour. Search engine crawlers are highly automated programs that periodically visit the web site to collect information. The behaviour of search engines could be used in analyzing server load, quality of search engines, dynamics of search engine crawlers, ethics of search engines etc. The time spent by various crawlers is significant in identifying the server load as major proportion of the server load is constituted by search engine crawlers. A temporal analysis of the search engine crawlers were done to identify their behaviour. It was found that there is a significant difference in the total time spent by various crawlers. The presence of search engine crawlers at web sites on hourly basis was also done to identify the dynamics of search engine crawlers at web sites. 

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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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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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Tatyana, Ivanova. "Ontology-Based Metasearch Engine in Electronics Area." International Journal of Innovative Technology and Exploring Engineering (IJITEE) 9, no. 12 (October 30, 2020): 273–77. https://doi.org/10.35940/ijitee.L8014.1091220.

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Paper The goal of search engines is to return accurate and complete results. Satisfying concrete user information needs becomes more and more difficult because of inability in it complete explicit specification and short comes of keyword-based searching and indexing. General search engines have indexed millions of web resources and often return thousands of results to the user query (most of them often inadequate). To increase result’s precession, users sometimes choose search engines, specialized in searching concrete domain, personalized or semantic search. A grand variety of specialized search engines may be found (and used) in the internet, but no one may guarantee finding of existing in the web and needed for the concrete user resources. In this paper we present our research on building a meta-search engine that uses domain and user profile ontologies, as well as information (or metadata), directly extracted from web sites to improve search result quality. We state main requirements to the search engine for students, PHD students and scientists, propose a conceptual model and discuss approaches of it practical realization. Our prototype metasearch engine first perform interactive semantic query refinement and then, using refined query, it automatically generate several search queries, sends them to different digital libraries and web search engines, augments and ranks returned results, using ontologically represented domain and user metadata. For testing our model, we develop domain ontologies in the electronic domain. We will use ontological terminology representation to propose recommendations for query disambiguation, and to ensure knowledge for reranking the returned results. We also present some partial initial implementations query disambiguation strategies and testing results.

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Al-anbaki, Simaa Hassan Hadi. "Smart Search Engine." International Academic Journal of Science and Engineering 11, no. 1 (June 5, 2024): 317–21. http://dx.doi.org/10.9756/iajse/v11i1/iajse1137.

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Existing information retrieval systems, such search engines, must be improved due to the issue of having too much information on the web or in broad sectors. More consideration is needed. Integrated search tools that can manage searches and filters effectively and show relevant results The main sitting technology is bloated with ever-increasing volumes of data, much like the Internet. You'll have finished your keyword research and all of this information one day. Its capacity to deliver timely information that people are seeking. Search engines work to overcome the restrictions imposed by the conventional method of keyword research as a result. This study seeks to outline the primary issues that keyword search engines currently face in order to keep up with the rapid expansion of the web and to meet all user expectations in a timely manner. In the next section, it examines a number of models that are not dependent on keywords that have been created, created, or used by researchers and search engines, and rates those technologies in accordance with the aspects that each search engine prioritizes in order to deliver results.

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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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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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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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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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Gurneet, Kaur. "ROLE AND IMPORTANCE OF SEARCH ENGINE OPTIMIZATION." International Journal of Research - Granthaalayah 5, no. 6 (June 26, 2017): 147–51. https://doi.org/10.5281/zenodo.818213.

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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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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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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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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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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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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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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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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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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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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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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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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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Tanjot, Kaur Kakkar, Kumar Nrip Nripesh, and Deshmukh Amarjeet. "A Study of Search Engine Optimizations (SEOs)." International Journal of Multidisciplinary Research Transactions 6, no. 5 (May 6, 2024): 38–55. https://doi.org/10.5281/zenodo.11118982.

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Search Engine Optimization (SEO) can be defined as the process of affecting the website visibility in the world of evergreen search engines’s unpaid results. It can also be defined as a process including various techniques that is being used to enhance more traffic on the website from the ”free” and ”organic” search results that are being available on the search engines. SEO’s is an effort that is made to make your website be in the top search results of a search engine because mostly the user searches out with the keyword of their desired need, rather than searching for the organisation name, and if the page link comes up in the top position then the page comes out to be profitable. SEO is a strategic technique to take a web document in the top search result of a search Engine. In today’s era as we all are aware of the fact that the internet marketing strategy, this research considers how a search engine works, what people search for, or actual terms/ keywords typed in the Search Bar, and how these are analyzed and optimised. This whole work describes the effort of taking the page on the top position in any search engine, say “Google” by increasing the page rank which may result in an improved position in the gang of competitors. Amongst the various search engines available in the market the Google Chrome is found to be the most user-friendly search engine proved for the Indian Users as it provides which gives user-oriented results. In this research paper, we analyzed the impact of search engine optimization techniques that can improve the visibility of a Website.

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Ti, Haowei, and Ding Ma. "Research on Google Search and Amazon Search Based on the Comparison of Algorithms." International Journal of Economics & Management Sciences 11, no. 3 (March 28, 2022): 4. https://doi.org/10.37421/ 2162-6359.2022.11.626.

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Search engine optimization, which can optimize the search display position of content and expose the target content to readers faster, is a great tool for marketing. For foreign trade practitioners, the traffic entrances of the two major search engines, Amazon and Google, determine the exposure of products. Amazon drives consumers to click and search with shopping as the demand and has a clearer consumption intention, while Google is a bigger information plaza than Amazon, leading people to various websites.

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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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Gyasoddin, Imran Ahemad, and Prof. D. G. Ingale. "META SEARCH ENGINE." International Journal of Ingenious Research, Invention and Development (IJIRID) 3, no. 5 (October 25, 2024): 311–14. https://doi.org/10.5281/zenodo.13991669.

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Meta search engines are designed to improve the efficiency and breadth of online searches by aggregating results from multiple search engines. Unlike traditional search engines, which rely on their own indexed databases and algorithms, meta search engines query several search engines simultaneously and present a unified set of results. This approach addresses limitations in single search engines, such as limited coverage, ranking biases, and incomplete results (Zhang & Wu, 2005; Jansen & Pooch, 2001). Meta search engines work by distributing user queries to various search engines, collecting the results, and then aggregating and ranking them based on their own algorithms (Kumar & Desai, 2021). This enables users to access a broader range of information, combining results from different sources and increasing the likelihood of finding relevant content. Additionally, meta search engines offer features like result filtering, customization, and privacy protection to enhance the overall search experience. By combining results from multiple sources, meta search engines help mitigate ranking biases present in individual search engines (Yuwono & Lee, 1997).

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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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Kunal, Karalkar, and Bhide Shripad. "A Review on SEO Search Engine Optimization." International Journal of Trend in Scientific Research and Development 2, no. 4 (December 18, 2019): 331–41. https://doi.org/10.31142/ijtsrd12963.

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Search engine optimization affects the presence or appearance of a website in the first page of a search engine. The visibility of a website can be paid or unpaid, but generally if a website wants to appear in the top position after an organic search then search engine optimization is the most important strategic tool to use. The whole internet marketing strategy circles around the SEO. The search engine optimization processes try to follow the working pattern of all the search engines and more specifically try to consider the algorithm used in search engines. The SEO implementation is also based on the searching process of people. It is very important to see and analyse the keywords that people are searching more. The SEO process for a website is required to upgrade or optimized periodically because the search engines are modifying their algorithms and trying to be more realistic in nature. There many things that affect the SEO process and that includes content of a website, the presence of the website data on social networking sites, codes used in HTML and the use of tags, backlinks etc. If a website wants to optimize its SEO and improve SERP search engine results page position then it has to take care of all those SEO tactics that we have discussed earlier. Kunal Karalkar | Shripad Bhide "A Review on SEO: Search Engine Optimization" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-4 , June 2018, URL: https://www.ijtsrd.com/papers/ijtsrd12963.pdf

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