Siga este enlace para ver otros tipos de publicaciones sobre el tema: Search engines.
Artículos de revistas sobre el tema "Search engines"
Crea una cita precisa en los estilos APA, MLA, Chicago, Harvard y otros
Consulte los 50 mejores artículos de revistas para su investigación sobre el tema "Search engines".
Junto a cada fuente en la lista de referencias hay un botón "Agregar a la bibliografía". Pulsa este botón, y generaremos automáticamente la referencia bibliográfica para la obra elegida en el estilo de cita que necesites: APA, MLA, Harvard, Vancouver, Chicago, etc.
También puede descargar el texto completo de la publicación académica en formato pdf y leer en línea su resumen siempre que esté disponible en los metadatos.
Explore artículos de revistas sobre una amplia variedad de disciplinas y organice su bibliografía correctamente.
1
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.
Texto completoResumen
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.
2
Saraygord Afshari, Sajad, Bhargava Jonnadula, Xiangyang Xu, Xihui Liang, and Zhaohui Yang. "Jet Engine Optimal Preventive Maintenance Scheduling Using Golden Section Search and Genetic Algorithm." Journal of Prognostics and Health Management 2, no. 1 (July 13, 2022): 45–71. http://dx.doi.org/10.22215/jphm.v2i1.3321.
Texto completoResumen
Jet engines are critical assets in aircraft, and their availability is crucial in the modern aircraft industry. Therefore, their maintenance scheduling is one of the major tasks an airline has to make during an engine’s lifetime. A proper engine maintenance schedule can significantly reduce maintenance costs without compromising the aircraft's reliability and safety. Different maintenance scheduling approaches have been used for jet engines, such as corrective, preventive, and predictive maintenance strategies. Regarding the safety demands in aircraft industries, preventive maintenance is a frequent maintenance method for jet engines. However, preventive maintenance schedules are often use fixed maintenance intervals, which is usually suboptimal. This paper focuses on minimizing a jet engine's overall maintenance cost by optimizing its preventive maintenance schedule based on an engine’s comprehensive reliability model. A hierarchical optimization framework including the golden section search and genetic algorithms is applied to find the optimal set of preventive maintenance number and their times and the components to be replaced at those times during the jet engine's overall lifetime. The Monte Carlo simulation is used to estimate the engine’s failure times using their lifetime distributions from the reliability model. The estimated failure times are then used to determine the engine's overall corrective and preventive maintenance costs during its lifetime. Finally, an optimal preventive maintenance schedule is proposed for an RB 211 jet engine using the presented method. In the end, comparing the proposed method's overall maintenance cost with two other maintenance methods demonstrates the proposed schedule's effectiveness. The method presented in this paper is generic, and it can be used for other similar engineering systems.
3
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.
Texto completoResumen
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.
4
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.
Texto completoResumen
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.
5
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.
Texto completoResumen
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.
6
Zuo, Xiang Lin, Wen Bo Wang, Ying Wang, and Wan Li Zuo. "Research and Implementation of Improved Real-Time Crawler Modeling." Applied Mechanics and Materials 312 (February 2013): 791–95. http://dx.doi.org/10.4028/www.scientific.net/amm.312.791.
Texto completoResumen
The past decade has witnessed the rapid development of search engines, which has become an indispensable part of everyday life. However, people are no longer satisfied with accessing to ordinary information, and they may instead pay more attention to fresh information. This demand poses challenges to traditional search engines, which concern more about relevance and importance of web pages. A search engine compresses three modules: crawler, indexer and searcher. Changes are needed for all these three parts to improve search engine's freshness. This paper investigates the first part of search engine crawler, we analyze the requirements for real-time crawler, and propose a novel real-time crawler based on more accurate estimation of refresh time. Experimental results demonstrate that the proposed real-time crawler can help search engine improve its freshness.
7
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.
Texto completoResumen
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)
8
Seymour, Tom, Dean Frantsvog, and Satheesh Kumar. "History Of Search Engines." International Journal of Management & Information Systems (IJMIS) 15, no. 4 (September 12, 2011): 47. http://dx.doi.org/10.19030/ijmis.v15i4.5799.
Texto completoResumen
As the number of sites on the Web increased in the mid-to-late 90s, search engines started appearing to help people find information quickly. Search engines developed business models to finance their services, such as pay per click programs offered by Open Text in 1996 and then Goto.com in 1998. Goto.com later changed its name to Overture in 2001, and was purchased by Yahoo! in 2003, and now offers paid search opportunities for advertisers through Yahoo! Search Marketing. Google also began to offer advertisements on search results pages in 2000 through the Google Ad Words program. By 2007, pay-per-click programs proved to be primary money-makers for search engines. In a market dominated by Google, in 2009 Yahoo! and Microsoft announced the intention to forge an alliance. The Yahoo! & Microsoft Search Alliance eventually received approval from regulators in the US and Europe in February 2010. Search engine optimization consultants expanded their offerings to help businesses learn about and use the advertising opportunities offered by search engines, and new agencies focusing primarily upon marketing and advertising through search engines emerged. The term "Search Engine Marketing" was proposed by Danny Sullivan in 2001 to cover the spectrum of activities involved in performing SEO, managing paid listings at the search engines, submitting sites to directories, and developing online marketing strategies for businesses, organizations, and individuals. Some of the latest theoretical advances include Search Engine Marketing Management (SEMM). SEMM relates to activities including SEO but focuses on return on investment (ROI) management instead of relevant traffic building (as is the case of mainstream SEO). SEMM also integrates organic SEO, trying to achieve top ranking without using paid means of achieving top in search engines, and PayPerClick SEO. For example some of the attention is placed on the web page layout design and how content and information is displayed to the website visitor.
9
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.
Texto completoResumen

 
 
 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.
 
 
10
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.
Texto completoResumen
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.
11
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.
Texto completoResumen
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.
12
MARCHIORI, MASSIMO. "SOCIAL SEARCH ENGINES." International Journal of Bifurcation and Chaos 17, no. 07 (July 2007): 2355–61. http://dx.doi.org/10.1142/s0218127407018440.
Texto completoResumen
The web landscape has undergone massive changes in the past years. On the other hand, search engine technology has not quite kept the same pace. In this article we look at the current scenarios, and argue how social flows can be used to make up for a better generation of search engines. We consider how society and technological progress somehow changed the rules of the game, introducing good but also bad components, and see how this situation could be modeled by search engines. Along this line of thinking, we show how the real components of interest are not just web pages, but flows of information of any kind, that need to be merged: this opens up for a wide range of improvements and far-looking developments, towards a new horizon of social search.
13
Wellings, Susan, and Biddy Casselden. "An exploration into the information-seeking behaviours of engineers and scientists." Journal of Librarianship and Information Science 51, no. 3 (November 26, 2017): 789–800. http://dx.doi.org/10.1177/0961000617742466.
Texto completoResumen
This article considers findings from Master’s research that investigated the information-seeking behaviours of engineers and scientists in the workplace. The objectives of this research were to establish where engineers and scientists look for information, consider their search preferences and determine the understanding they have of online search engine operation. There is limited current research in these areas looking at engineers and scientists in the workplace. The research was undertaken using a mixed methods research methodology. A survey was conducted with engineers and scientists working in the UK, using an online questionnaire and interviews to obtain quantitative and qualitative data. Due to the small sample size (115: 58 engineers, 57 scientists) this research does not make generalisations about the wider population. The research showed both similarities and differences between engineers’ and scientists’ information-seeking behaviours. The most popular resources used by both engineers and scientists were online search engines, specialist databases and scholar search engines; and the most used sources were from within their own organisation (colleagues and documents). Electronic versions of sources were preferred over print because of their searchability; however, when an item was found it was often printed out to read. Although the main focus of this research was not information literacy it is suggested that there are significant gaps in the understanding of search engine functionality by both engineers and scientists, even though it is the most heavily used resource for information seeking. Whilst this research does not make generalisations about the wider engineer and scientist populations, potential implications for information professionals working with these groups are considered.
14
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.
Texto completoResumen
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.
15
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.
Texto completoResumen
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.
16
Garner, Wendy. "Search engines." Nursing Standard 20, no. 22 (February 8, 2006): 67–68. http://dx.doi.org/10.7748/ns.20.22.67.s53.
Texto completo
17
Al-Shahi, Rustam. "Search Engines." Practical Neurology 1, no. 1 (October 2001): 60–61. http://dx.doi.org/10.1046/j.1474-7766.2001.01012.x.
Texto completo
18
WOOTTON, JACQUELINE C. "Search Engines." Journal of Women's Health 6, no. 3 (June 1997): 345–47. http://dx.doi.org/10.1089/jwh.1997.6.345.
Texto completo
19
Mider, Daniel. "Sztuka wyszukiwania w Internecie – autorski przegląd wybranych technik i narzędzi." Studia Politologiczne 2019, no. 54 (November 20, 2019): 191–229. http://dx.doi.org/10.33896/spolit.2019.54.8.
Texto completoResumen
The text consists of two parts. The first analyzed the internet search techniques – in a general heuristic sense and detailed i.e. specific techniques belonging to the family of query languages – so called operators (logical operators, localization operators, operators for communication channels in social media, chronometric operators, search operators in the content of the www and search operators for specific types of content). Their main function is to clarify search queries. The second part of the text contains a review and analysis of selected internet exploration tools – search engines (global search engines, search engines focusing on user privacy, metasearch engines and multisearch engines, regional search engines and catalogues, people search engines, search engines of gray literature and internet archives). Preview is not exhaustive or deepened, it serves rather the initial orientation of those interested in the search engine universe.
20
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.
Texto completoResumen
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.
21
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.
Texto completoResumen
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.
22
Stevenson, Valerie. "Search Engine Update." Legal Information Management 1, no. 3 (2001): 28–31. http://dx.doi.org/10.1017/s1472669600000566.
Texto completoResumen
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.
23
Dayanand, Dr C. D., and Syed M. S. Zain. "Search Engines in Biomedical Research." JOURNAL OF CLINICAL AND BIOMEDICAL SCIENCES 04, no. 1 (March 15, 2014): 259–60. http://dx.doi.org/10.58739/jcbs/v04i1.7.
Texto completo
24
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.
Texto completoResumen
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.
25
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.
Texto completoResumen
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.
26
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.
Texto completoResumen
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.
27
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.
Texto completoResumen
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.
28
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.
Texto completoResumen
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.
29
O’Neill, Stephen, and Kevin Curran. "The Core Aspects of Search Engine Optimisation Necessary to Move up the Ranking." International Journal of Ambient Computing and Intelligence 3, no. 4 (October 2011): 62–70. http://dx.doi.org/10.4018/jaci.2011100105.
Texto completoResumen
Search engine optimization (SEO) is the process of improving the visibility, volume and quality of traffic to website or a web page in search engines via the natural search results. SEO can also target other areas of a search, including image search and local search. SEO is one of many different strategies used for marketing a website but SEO has been proven the most effective. An Internet marketing campaign may drive organic search results to websites or web pages but can be involved with paid advertising on search engines. All search engines have a unique way of ranking the importance of a website. Some search engines focus on the content while others review Meta tags to identify who and what a web site’s business is. Most engines use a combination of Meta tags, content, link popularity, click popularity and longevity to determine a sites ranking. To make it even more complicated, they change their ranking policies frequently. This paper provides an overview of search engine optimisation strategies and pitfalls.
30
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.
Texto completoResumen
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.
31
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.
Texto completoResumen
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.
32
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.
Texto completoResumen
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.
33
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.
Texto completoResumen
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.
34
Qian, Shuang Yan. "Design and Implementation of Landscape Plant Information Search Engine." Advanced Materials Research 971-973 (June 2014): 1892–96. http://dx.doi.org/10.4028/www.scientific.net/amr.971-973.1892.
Texto completoResumen
With the explosive growth of the World Wide Web information, we need the appropriate retrieval tools, especially the retrieval of the professional information, we need a embody of search engines with the professional vocabulary features. Based on the research of search engine's core technology, this paper presents a design scheme which is the botanical garden plant information search engine based on Internet data, we descript of its design.
35
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.
Texto completoResumen
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.
36
Heintz, Christophe. "Web search engines and distributed assessment systems." Distributed Cognition 14, no. 2 (September 21, 2006): 387–409. http://dx.doi.org/10.1075/pc.14.2.15hei.
Texto completoResumen
I analyse the impact of search engines on our cognitive and epistemic practices. For that purpose, I describe the processes of assessment of documents on the Web as relying on distributed cognition. Search engines together with Web users, are distributed assessment systems whose task is to enable efficient allocation of cognitive resources of those who use search engines. Specifying the cognitive function of search engines within these distributed assessment systems allows interpreting anew the changes that have been caused by search engine technologies. I describe search engines as implementing reputation systems and point out the similarities with other reputation systems. I thus call attention to the continuity in the distributed cognitive processes that determine the allocation of cognitive resources for information gathering from others.
37
Hook, David. "Study of Search Engine Transaction Logs Shows Little Change in How Users use Search Engines." Evidence Based Library and Information Practice 1, no. 3 (September 14, 2006): 67. http://dx.doi.org/10.18438/b80014.
Texto completoResumen
A review of:
 
 Jansen, Bernard J., and Amanda Spink. “How Are We Searching the World Wide Web? A Comparison of Nine Search Engine Transaction Logs.” Information Processing & Management 42.1 (2006): 248-263.
 
 Objective – To examine the interactions between users and search engines, and how they have changed over time. 
 
 Design – Comparative analysis of search engine transaction logs.
 
 Setting – Nine major analyses of search engine transaction logs.
 
 Subjects – Nine web search engine studies (4 European, 5 American) over a seven-year period, covering the search engines Excite, Fireball, AltaVista, BWIE and AllTheWeb.
 
 Methods – The results from individual studies are compared by year of study for percentages of single query sessions, one-term queries, operator (and, or, not, etc.) usage and single result page viewing. As well, the authors group the search queries into eleven different topical categories and compare how the breakdown has changed over time.
 
 Main Results – Based on the percentage of single query sessions, it does not appear that the complexity of interactions has changed significantly for either the U.S.-based or the European-based search engines. As well, there was little change observed in the percentage of one-term queries over the years of study for either the U.S.-based or the European-based search engines. Few users (generally less than 20%) use Boolean or other operators in their queries, and these percentages have remained relatively stable. One area of noticeable change is in the percentage of users viewing only one results page, which has increased over the years of study. Based on the studies of the U.S.-based search engines, the topical categories of ‘People, Place or Things’ and ‘Commerce, Travel, Employment or Economy’ are becoming more popular, while the categories of ‘Sex and Pornography’ and ‘Entertainment or Recreation’ are declining.
 
 Conclusions – The percentage of users viewing only one results page increased during the years of the study, while the percentages of single query sessions, one-term sessions and operator usage remained stable. The increase in single result page viewing implies that users are tending to view fewer results per web query. There was also a significant difference in the percentage of queries using Boolean operators between the US-based and the European-based search engines. One of the study’s findings was that results from a study of a particular search engine cannot necessarily be applied to all search engines. Finally, web search topics show a trend towards information or commerce searching rather than entertainment.
38
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.
Texto completoResumen
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.
39
Bello, Rotimi-Williams, and Firstman Noah Otobo. "Conversion of Website Users to Customers-The Black Hat SEO Technique." International Journal of Advanced Research in Computer Science and Software Engineering 8, no. 6 (June 29, 2018): 29. http://dx.doi.org/10.23956/ijarcsse.v8i6.714.
Texto completoResumen
Search Engine Optimization (SEO) is a technique which helps search engines to find and rank one site over another in response to a search query. SEO thus helps site owners to get traffic from search engines. Although the basic principle of operation of all search engines is the same, the minor differences between them lead to major changes in results relevancy. Choosing the right keywords to optimize for is thus the first and most crucial step to a successful SEO campaign. In the context of SEO, keyword density can be used as a factor in determining whether a webpage is relevant to a specified keyword or keyword phrase. SEO is known for its contribution as a process that affects the online visibility of a website or a webpage in a web search engine's results. In general, the earlier (or higher ranked on the search results page), and more frequently a website appears in the search results list, the more visitors it will receive from the search engine's users; these visitors can then be converted into customers. It is the objective of this paper to re-present black hat SEO technique as an unprofessional but profitable method of converting website users to customers. Having studied and understood white hat SEO, black hat SEO, gray hat SEO, crawling, indexing, processing and retrieving methods used by search engines as a web software program or web based script to search for documents and files for keywords over the internet to return the list of results containing those keywords; it would be seen that proper application of SEO gives website a better user experience, SEO helps build brand awareness through high rankings, SEO helps circumvent competition, and SEO gives room for high increased return on investment.
40
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.
Texto completoResumen
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.
41
Chen, Lin Chih. "Building a Post-Search Academic Search Engine Based on a Serial of Clustering Methods." Applied Mechanics and Materials 284-287 (January 2013): 3051–55. http://dx.doi.org/10.4028/www.scientific.net/amm.284-287.3051.
Texto completoResumen
Academic search engines, such as Google Scholar and Scirus, provide a Web-based interface to effectively find relevant scientific articles to researchers. However, current academic search engines are lacking the ability to cluster the search results into a hierarchical tree structure. In this paper, we develop a post-search academic search engine by using a mixed clustering method. In this method, we first adopt a suffix tree clustering and a two-way hash mechanism to generate all meaningful labels. We then develop a divisive hierarchical clustering algorithm to organize the labels into a hierarchical tree. According to the results of experiments, we conclude that using our mixed clustering method to cluster the search results can give significant performance gains than current academic search engines. In this paper, we make two contributions. First, we present a high performance academic search engine based on our mixed clustering method. Second, we develop a divisive hierarchical clustering algorithm to organize all returned search results into a hierarchical tree structure.
42
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.
Texto completo
43
Vegesna, Rohith. "AI Query Protocol (AIQP) : AI-Powered Search Engine, Eliminating Traditional Crawling." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 02 (February 12, 2025): 1–9. https://doi.org/10.55041/ijsrem41538.
Texto completoResumen
Search engines currently function by carrying out web crawling followed by indexing and ranking the retrieved websites for information retrieval purposes. Window search engines create inefficient operations and expensive maintenance requirements because they allow outdated information and Search Engine Optimization manipulations. This article presents AI Query Protocol (AIQP) as a standardized communication framework which provides real-time exchanges between search engines and website AI assistants. Website AI agents receive structured questions from search engines which yield instant verified responses that are structured in format. AIQP delivers improved search results while avoiding outdated information because it enables greater control of search visibility through direct communication between search engines and website AI assistants. This paper presents the structure of AIQP together with its deployment process while showing how it changes online search systems.
44
Beneventano, Domenico, and Sonia Bergamaschi. "Provenance-Aware Semantic Search Engines Based On Data Integration Systems." International Journal of Organizational and Collective Intelligence 4, no. 2 (April 2014): 1–30. http://dx.doi.org/10.4018/ijoci.2014040101.
Texto completoResumen
Search engines are common tools for virtually every user of the Internet and companies, such as Google and Yahoo!, have become household names. Semantic Search Engines try to augment and improve traditional Web Search Engines by using not just words, but concepts and logical relationships. Given the openness of the Web and the different sources involved, a Web Search Engine must evaluate quality and trustworthiness of the data; a common approach for such assessments is the analysis of the provenance of information. In this paper a relevant class of Provenance-aware Semantic Search Engines, based on a peer-to-peer, data integration mediator-based architecture is described. The architectural and functional features are an enhancement with provenance of the SEWASIE semantic search engine developed within the IST EU SEWASIE project, coordinated by the authors. The methodology to create a two level ontology and the query processing engine developed within the SEWASIE project, together with provenance extension are fully described.
45
Wani, Zahid Ashraf, and Adil Ahmad Sofi. "Retrieval efficiency of select search engines vis-à-vis diverse open courseware formats." Electronic Library 34, no. 3 (June 6, 2016): 457–70. http://dx.doi.org/10.1108/el-08-2014-0132.
Texto completoResumen
Purpose This paper aims to gauge the visibility of open content available in different formats of select open courseware (OCW) repositories through prominent search engines. Design/methodology/approach Open content in three formats (pdf, audio and video) from four OCW repositories listed in the OCW consortium under the science and technology subject heading were searched through seven select search engines. Findings None of the selected OCW repositories are fully visible on the selected search engines. Visibility of OCW content varied from one search engine to the other and was affected by the format in which it is available. Google is the best search engine for retrieving OCW content, whereas OCWfinder – a specialized search engine for retrieving OCW – has performed dismally. Research limitations/implications The study demonstrates the need for enhancing the visibility of open content through using search engine optimization techniques. Originality/value The study intends to supply findings that could be used by stakeholders to improve the visibility of OCW repositories. It is an attempt to draw a comparison between search engines for their ability to index different formats of OCW in the selected repositories. Findings can be used by information professionals to brush their information hunting skills.
46
Zhang, Fan, Xiu Lan Feng, and Jin Sheng Yuan. "Vertical Search Engines on Forestry." Advanced Materials Research 143-144 (October 2010): 1270–74. http://dx.doi.org/10.4028/www.scientific.net/amr.143-144.1270.
Texto completoResumen
With the rapid growth of forestry information,the amount of information on forestry is increasing rapidly. Comprehensive search engine is powerful,but its speed and accuracy of industry search is limited, owing to a host of information. According to the definition of vertical search engines,Heritrix Web Crawler and full text search framework of Lucene,this paper is mainly concerned the information of capture,indexing and search strategies in order to achieve an ideal forestry vertical search engine design. Experiments compared with comprehensive have proved the effectiveness of the proposed method.
47
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.
Texto completoResumen
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
48
Fesenmaier, Daniel R., Zheng Xiang, Bing Pan, and Rob Law. "A Framework of Search Engine Use for Travel Planning." Journal of Travel Research 50, no. 6 (December 28, 2010): 587–601. http://dx.doi.org/10.1177/0047287510385466.
Texto completoResumen
Search engines have become one of the primary tools for travel planning and, as such, have become an important element in the marketing efforts of destination marketing organizations. Recently, it has been demonstrated that because of the dynamic relationships among search engine providers, the tourism industry, and travelers, it is essential that destination marketing organizations understand how search engines are used by travelers within the travel planning process. This study proposed a three-stage model that provides a framework for examining how online travelers use search engines and how different aspects of the travel planning process shape this use. The model was evaluated based on a national survey of American online travel planners, and the findings provide significant insight into the role of search engines for travel planning. The implications of the study for search engine marketing are discussed as well as several challenges for future research.
49
Alqaaidi, Sakher Khalil. "A Hybrid Approach for Web Change Detection." International Journal of Information Technology and Web Engineering 8, no. 2 (April 2013): 46–69. http://dx.doi.org/10.4018/jitwe.2013040104.
Texto completoResumen
Search engines save copies of crawled web pages to provide instant search results, saved pages may become old and un-updated as original pages change providing new information and new links, and most of websites don’t submit these new changes to search engines so search engines don’t depend mainly on websites techniques of submitting changes. Keeping pages fresh and updated in search engine is important for giving real page ranks and for providing real time information. Techniques were invented to improve the page update process by search engine. In this paper the author combines two of good known techniques and implements the new one via experiments that improve better results in different experiment cases.
50
Economides, Anastasios A., and Antonia Kontaratou. "Hotels Pricing at Travel Search Engines." International Journal of Online Marketing 1, no. 4 (October 2011): 64–74. http://dx.doi.org/10.4018/ijom.2011100105.
Texto completoResumen
Web 2.0 applications have been increasingly recognized as important information sources for consumers, including the domain of tourism. In the center of the travelers’ interest is the use of these applications in order to compare and choose hotels for their accommodation at various tourism destinations. It is important to investigate the issues related to the presence of the hotels on some of the most dominant tourism search engines and to the prices that they present. This paper compares the search engines and determines whether the cheapest and to the most complete one can be discovered. This paper focuses on analyzing the hotel prices presented on their official websites and on the following eight tourism search engines: Booking.com, Expedia.com, Hotelclub.com, Hotels.com, Orbitz.com, Priceline.com, Travelocity.com, and Venere.com. The data analysis, by the use of the descriptive statistics, showed that only 23% of the hotels examined are found at all the search engines. Furthermore, the price analysis showed that there are differences among the search engines. Although some search engines statistically give lower prices, there is not a single search engine that always gives the lowest price for every hotel.