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Journal articles on the topic 'Web'

Author: Grafiati
Published: 4 June 2021
Last updated: 7 July 2025

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1

OPELL, B. D. "Webs and Web-Builders: Spiders." Science 234, no. 4783 (December 19, 1986): 1593–94. http://dx.doi.org/10.1126/science.234.4783.1593-a.

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2

Surya, S., E. Premalatha, and S. Muthulakshmi. "Intelligent Web Data with Semantic Web Mining." International Journal of Scientific Engineering and Research 5, no. 8 (August 27, 2017): 146–48. https://doi.org/10.70729/ijser171837.

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3

Pasnur, Pallavi, and Mohini Kumbhare. "Study of Beam With Plain Web, Trapezoidal Corrugated Web, and Triangular Corrugated Web." Journal of Advances and Scholarly Researches in Allied Education 15, no. 2 (April 1, 2018): 630–36. http://dx.doi.org/10.29070/15/56941.

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4

Im, Bokhee, and Hayi-Joo Ko. "Web loops and webs with reflections." Journal of Geometry 61, no. 1-2 (February 1998): 62–73. http://dx.doi.org/10.1007/bf01237496.

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5

Keusch, Florian, and Ting Yan. "Web Versus Mobile Web." Social Science Computer Review 35, no. 6 (November 2, 2016): 751–69. http://dx.doi.org/10.1177/0894439316675566.

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Due to a rising mobile device penetration, Web surveys are increasingly accessed and completed on smartphones or tablets instead of desktop computers or laptops. Mobile Web surveys are also gaining popularity as an alternative self-administered data collection mode among survey researchers. We conducted a methodological experiment among iPhone owners and compared the participation and response behavior of three groups of respondents: iPhone owners who started and completed our survey on a desktop or laptop PC, iPhone owners who self-selected to complete the survey on an iPhone, and iPhone owners who started on a PC but were requested to switch to iPhone. We found that respondents who completed the survey on a PC were more likely to be male, to have a lower educational level, and to have more experience with Web surveys than mobile Web respondents, regardless of whether they used the iPhone voluntarily or were asked to switch from a PC to an iPhone. Overall, iPhone respondents had more missing data and took longer to complete the survey than respondents who answered the questions on a PC, but they also showed less straightlining behavior. There are only minimal device differences on survey answers obtained from PCs and iPhones.
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6

Sangani, K. "Web everywhere [Web browser]." Engineering & Technology 5, no. 16 (October 23, 2010): 26–29. http://dx.doi.org/10.1049/et.2010.1604.

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7

Knights, M. "Web 2.0 [web technologies]." Communications Engineer 5, no. 1 (February 1, 2007): 30–35. http://dx.doi.org/10.1049/ce:20070104.

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8

Berger, Stefan. "Web Site: Resonantes Web." Angewandte Chemie 113, no. 5 (March 2, 2001): 993. http://dx.doi.org/10.1002/1521-3757(20010302)113:5<993::aid-ange993>3.0.co;2-p.

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9

Köhler, Felix. "Web Site: Chemisches Web." Angewandte Chemie 114, no. 5 (March 1, 2002): 911. http://dx.doi.org/10.1002/1521-3757(20020301)114:5<911::aid-ange911>3.0.co;2-r.

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10

Sumeet, Raghunath Koyande, Vishal Shivraj Reddy Yache, and Dendge Mayuri. "Invisible Web." International Journal of Trend in Scientific Research and Development 2, no. 4 (June 20, 2018): 2453–56. https://doi.org/10.31142/ijtsrd15630.

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In this research paper our topic is to analyze and dig deeper into deep web and what can we find when we go dive deep into the internet world. Web means internet as we all know, today almost everyone usesthe internet. We use internet for sharing information or to get information. The web which we use is called as Surface web, which is huge. This surface web contains billions of websites which are indexed on the goggle or other web search engines. Search engines can easily search for this indexed website or even the data on that website with the help of crawlers and modern search algorithm. Another part of the web is the deep web, which is almost 95 of total web i.e. although the surface web is huge but it&#39;s only 5 of the entire web. Deep web websites are not visible to everyone, because these websites are not indexed on any search engine. To search these links, we need a TOR browser, a special browser which hides the IP address of the computer by bouncing the connection around a distributed network 1 . The deep web also contains large databases such as iCloud, Google&#39;s databases So that this information should not visible to anyone from the surface web. The deep web provides a good amount of security for such systems because this links only be accessible for specific users and with specific credential and specific address. All the data we store on the cloud is stored on physical location but the only way to access this data is thru deep web links only. These links and databases controlled by the companies which provide cloud services. Because of this all the data is stored on servers also and not visible to anyone and users can only access their data with their login credential and data of other users remain safe 3 4 . Sumeet Raghunath Koyande | Yache Vishal Shivraj Reddy | Mayuri Dendge &quot;Invisible Web&quot; 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/ijtsrd15630.pdf
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11

W Ramteke, Shrikant, and Anil Nanaji Chikate. "Web 3.0: Evolution of Web - Based Library Services." International Journal of Science and Research (IJSR) 13, no. 10 (October 5, 2024): 492–95. http://dx.doi.org/10.21275/sr241005162833.

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12

Asra, Kalim, K. Jha C, Singh Tomar Deepak, and Rishi Sahu Divya. "A Framework for Web Application Vulnerability Detection." International Journal of Engineering and Advanced Technology (IJEAT) 9, no. 3 (February 29, 2020): 543–49. https://doi.org/10.35940/ijeat.C4778.029320.

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Hardly a facet of human life is not influenced by the Internet due to the continuous proliferation in the Internet facilities, usage, speed, user friendly browsing, global access, etc. At flip side, hackers are also attacking this digital world with new tactics and techniques through exploiting the web application vulnerabilities. The analysis of these vulnerabilities is of paramount importance in direction to secure social digital world. It can be carried out in two ways. First, manual analysis which is error prone due to the human nature of forgiveness, dynamic change in technology and fraudulence attack techniques. Second, through the existing web application vulnerability scanners that sometime may suffer from generating false alarm rate. Hence, there is a need to develop a framework that can detect different levels of vulnerabilities, ranging from client side vulnerabilities, communication side vulnerabilities to server side vulnerabilities. This paper has carried out the literature survey in direction of identifying the new attack vectors, vulnerabilities, detection mechanism, research gaps and new working areas in same field. Continuous improvement in framework is easy. Hence, a framework is proposed to overcome the identified research gap.
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13

Zhao, Jie, Xiaoyang Lu, Xueya Wang, and Zheng Ma. "Web Information Credibility: From Web 1.0 to Web 2.0." International Journal of u- and e-Service, Science and Technology 8, no. 7 (July 31, 2015): 161–72. http://dx.doi.org/10.14257/ijunesst.2015.8.7.16.

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14

Yakovlev, Ilya. "Web 2.0 compared to Web 1.0. [perspectives-Web 2.0]." IT Professional 9, no. 99 (2007): x7. http://dx.doi.org/10.1109/mitp.2007.4374050.

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15

Dukes, Mark, Einan Gardi, Einar Steingrímsson, and Chris D. White. "Web worlds, web-colouring matrices, and web-mixing matrices." Journal of Combinatorial Theory, Series A 120, no. 5 (July 2013): 1012–37. http://dx.doi.org/10.1016/j.jcta.2013.02.001.

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16

Thawkar, Sonu G., and Sharyu V. Ghonmode. "Study on structure and types of spider webs from Nagpur district Maharashtra India." Advanced Studies in Biology 16, no. 1 (2024): 157–67. http://dx.doi.org/10.12988/asb.2024.91933.

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The structure of spider webs varies substantially between species, and web building has even been lost completely in some clades. Examples of different web forms include the classic orb webs, which may be oriented vertically to the ground or horizontally, sheet webs, and cobwebs, consisting of three-dimensional meshwork and ascending sticky threads for support and capture of prey. The primary function of spider webs is to capture prey. This ecological success is in part due to the exceptional mechanics of the spider web, with its strength, toughness, elasticity, and robustness, which originate from its hierarchical structures from sequence design to web architecture. Hence a preliminary survey was carried out to structure and identify types of spider webs from Nagpur district, Maharashtra, India. This study explores the structure and identification of spider webs (Arachnids) in the Nagpur District of Maharashtra. Sampling was carried out in 8 months from January 2024 to August 2024 during the weak and month wise. Spider webs are collected using a Photograph collection and black paper for the collection of type’s spider webs. The results of the study concluded that a total of 8 types of spider webs were collected there were Site A 3 types of spider webs, Site B 3 types of spider webs, Site C 1 type of spider web and Site D 1 type of spider web were identified. A total 8 types of spider webs are identified, the names of types of spider webs are the total 8 types of spider webs Identified in Nagpur district the following types of spider webs are the Funnel-web of spider, Sheet web, Classic round webs of spider webs or Orb webs, Mesh web of a spider, Cobweb of spider, Tangle web, Messy web of a spider, and Triangle web of spider.
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17

Koyande, Sumeet Raghunath, Yache Vishal Shivraj Reddy, and Mayuri Dendge. "Invisible Web." International Journal of Trend in Scientific Research and Development Volume-2, Issue-4 (June 30, 2018): 2453–56. http://dx.doi.org/10.31142/ijtsrd15630.

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18

Nagasivaanjaneya Reddy R, Sunkara. "Web Mining." International Journal of Science and Research (IJSR) 12, no. 3 (March 5, 2023): 900–903. http://dx.doi.org/10.21275/sr23303173846.

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19

Vartak, Amey. "Web Personalization using Web Mining." International Journal for Research in Applied Science and Engineering Technology 6, no. 4 (April 30, 2018): 86–89. http://dx.doi.org/10.22214/ijraset.2018.4019.

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20

Serrhini, Mohammed. "Web Browsers Security Web-Lab." International Journal of Online Engineering (iJOE) 9, no. 3 (June 11, 2013): 4. http://dx.doi.org/10.3991/ijoe.v9i3.2468.

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21

Ferraris, Maurizio. "Web tolemaico e web copernicano." Phenomenology & Mind 20 (2021): 146. http://dx.doi.org/10.17454/pam-2013.

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22

Powell, Grant. "The Web Before the Web." ITNOW 66, no. 4 (2024): 36–37. http://dx.doi.org/10.1093/itnow/bwae124.

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23

Greaves, Mark, and Peter Mika. "Semantic Web and Web 2.0." Journal of Web Semantics 6, no. 1 (February 2008): 1–3. http://dx.doi.org/10.1016/j.websem.2007.12.002.

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24

Pomerantz, Bruce. "WEB STRANDS: SPYING WEB SITES." Internet Reference Services Quarterly 3, no. 2 (May 11, 1998): 83–88. http://dx.doi.org/10.1300/j136v03n02_12.

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25

Bernal, P. A. "Web 2.5: The Symbiotic Web." International Review of Law, Computers & Technology 24, no. 1 (March 2010): 25–37. http://dx.doi.org/10.1080/13600860903570145.

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26

Castro-Leon, E. "The Web Within the Web." IEEE Spectrum 41, no. 2 (February 2004): 42–46. http://dx.doi.org/10.1109/mspec.2004.1265137.

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27

Eirinaki, Magdalini, and Michalis Vazirgiannis. "Web mining for web personalization." ACM Transactions on Internet Technology 3, no. 1 (February 2003): 1–27. http://dx.doi.org/10.1145/643477.643478.

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28

Stoffel, Kilian. "Web + Data Mining = Web Mining." HMD Praxis der Wirtschaftsinformatik 46, no. 4 (August 2009): 6–20. http://dx.doi.org/10.1007/bf03340377.

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29

Hall, Wendy, and Thanassis Tiropanis. "Web evolution and Web Science." Computer Networks 56, no. 18 (December 2012): 3859–65. http://dx.doi.org/10.1016/j.comnet.2012.10.004.

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30

Köhler, Felix. "Web Site: The Chemists' Web." Angewandte Chemie International Edition 41, no. 5 (March 1, 2002): 871. http://dx.doi.org/10.1002/1521-3773(20020301)41:5<871::aid-anie871>3.0.co;2-r.

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31

Patel, Akshar, Deep Thakar, Dhairya Patel, Akshay Dave, Dr Dipesh M Patel, and Prof Brijesh Shukla. "Web 3.0: The Risks and Benefits of Web 3.0 no Web 2.0, Web 1.0." International Journal of Research Publication and Reviews 03, no. 12 (2022): 249–56. http://dx.doi.org/10.55248/gengpi.2022.31203.

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The internet as the most important international data media through which purchaser can percentage, read, and composes information thru pcs related to internet. In maximum current couple of years, net has had a number of development from web1.0 to web 3.0. The fundamental emphasis of the web or web 1. 0, in any other case referred to as the Exemplary net, confirmed up in 1991. Web1. 0 become tied in with associating and getting statistics at the net. Then, at that point, got here internet 2.0, empowering clients to peruse as well as make and convey content. because of the read and compose functionalities of net 2.0, there was a fantastic development within the at the web, uniquely in digital amusement close by net based totally enterprise. Web3.0 is by using and big viewed as the development of the semantic internet, wherein pc will creating and thinking new information in preference to human beings. utilizing man-made awareness and AI advances, clients will really want to speak with facts. The Metaverse is the destiny emphasis of the net. it'll consolidates numerous distinct virtual spaces that gives admittance to an assorted collection of diversion and undertakings using the overall scope of elevated reality
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32

TF, Michael Raj,, and Siva Prakasam P. "Semantic Web: A Study on Web Service Composition Approaches." International Journal of Trend in Scientific Research and Development Volume-1, Issue-4 (June 30, 2017): 196–209. http://dx.doi.org/10.31142/ijtsrd115.

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33

Lingaraju, Dr G. M., and Dr S. Jagannatha. "Review of Web Page Classification and Web Content Mining." Journal of Advanced Research in Dynamical and Control Systems 11, no. 10 (October 31, 2019): 142–47. http://dx.doi.org/10.5373/jardcs/v11i10/20193017.

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34

Joshila Grace, L. K., V. Maheswari, and Dhinaharan Nagamalai. "Analysis of Web Logs And Web User In Web Mining." International Journal of Network Security & Its Applications 3, no. 1 (January 28, 2011): 99–110. http://dx.doi.org/10.5121/ijnsa.2011.3107.

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35

Kistler, Thomas, and Hannes Marais. "WebL—a programming language for the Web." Computer Networks and ISDN Systems 30, no. 1-7 (April 1998): 259–70. http://dx.doi.org/10.1016/s0169-7552(98)00018-x.

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36

Abdulelah, A. Algosaibi1 Saleh Albahli2 Samer F. Khasawneh3 and Austin Melton4. "WEB EVOLUTION - THE SHIFT FROM INFORMATION PUBLISHING TO REASONING." International Journal of Artificial Intelligence and Applications (IJAIA) 8, November (March 31, 2020): 11–28. https://doi.org/10.5281/zenodo.3734635.

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The Web, as communication channel, has had variety of development that allows information to be published and accessed in a scaleable approach. With the revolution of the information, some research studies have conducted to boost the present situation and propose advance version of the Web. Therefore, it is important to look into the new version of the Web in order to improve the way that information is expressed, to make more intelligent choices and to obtain a better meaning of the information over the Web. That is, future web would require specific architecture in order to support the extracting of better meaning or &quot;reasoning&quot;. With Web 1.0 and Web 2.0, the current information over the Web is not understandable for the machines. Understanding is big shift for wide open door for innovatoion and reasoning. In this work, we research the progress of the Web from Web 1.0, Web 2.0, Web 3.0, Web 4.0, to Web 5.0. We are pointing out document types and technologies employed to understand the changes from Web 1.0 to Web 3.0 and to predicate the future of the Web (Web 4.0 and Web 5.0). Also, we present the current status and concerns about the Web as an information source and communication channel.
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37

Kwame, Boakye Agyapong, J.B.Hayfron-Acquah Dr., and M. Asante Dr. "AN OPTIMIZED PAGE RANK ALGORITHM WITH WEB MINING, WEB CONTENT MINING AND WEB STRUCTURE MINING." International Journal of Engineering Technologies and Management Research 4, no. 8 (September 21, 2017): 22–27. https://doi.org/10.5281/zenodo.914660.

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<strong><em>With the rapid increase in internet technology, users get easily confused in large hypertext structure. The primary goal of the web site owner is to provide the relevant information to the users to fulfill their needs. In order to achieve this goal, they use the concept of web mining. Web mining is used to categorize users and pages by analyzing the users" behaviour, the content of the pages, and the order of the URLs that tend to be accessed in order. Most of the search engines are ranking their search results in response to users' queries to make their search navigation easier. With a web browser, one can view web pages that may contain text, images, videos, and other multimedia, and navigate between them via hyperlinks. It is very difficult for a user to find the high quality information which he wants. Page Ranking algorithm is needed which provide the higher ranking to the important pages. In this paper, we discuss the improvement of Page ranking algorithm to provide the higher ranking to important pages. Most of the search engines are ranking their search results in response to user’s queries to make their search navigations easier.</em></strong>
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38

LEAN, JENNIFER ANN. "Web." Scrutiny2 11, no. 1 (January 2006): 105. http://dx.doi.org/10.1080/18125441.2006.9684207.

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39

Fearnside, Jeff. "Web." ISLE: Interdisciplinary Studies in Literature and Environment 25, no. 3 (2018): 656. http://dx.doi.org/10.1093/isle/isy027.

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40

Thompson, Don. "Web." JAMA 296, no. 15 (October 18, 2006): 1812. http://dx.doi.org/10.1001/jama.296.15.1812-b.

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41

Harvey, Ken. "Web site review: AdWatch web site." Australian Prescriber 27, no. 3 (June 1, 2004): 63. http://dx.doi.org/10.18773/austprescr.2004.056.

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42

Suganya, E., and Vijayarani . "Web Crawlers for Web Content Extraction." International Journal of Computer Sciences and Engineering 7, no. 4 (April 30, 2019): 238–47. http://dx.doi.org/10.26438/ijcse/v7i4.238247.

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43

Francek, Mark. "Web Resources: Weather on the Web." Journal of Geoscience Education 50, no. 4 (September 2002): 469–70. http://dx.doi.org/10.5408/1089-9995-50.4.469.

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44

Hatta, Masayuki. "Deep web, dark web, dark net." Annals of Business Administrative Science 19, no. 6 (December 15, 2020): 277–92. http://dx.doi.org/10.7880/abas.0200908a.

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45

Rastier, François. "Sémantique du web vs. Semantic Web ?" Syntaxe et sémantique 9, no. 1 (2008): 15. http://dx.doi.org/10.3917/ss.009.0015.

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46

Nerurkar, Nupur Kapoor, Asitama Sarkar, and Sameer Yermalkar. "To Web or Not to Web." Bombay Hospital Journal 63, no. 1 (2021): 42–45. http://dx.doi.org/10.15713/ins.bhj.50.

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47

Ma, Lingfeng, and Gavriel Salvendy. "Graphical Web directory for Web search." Behaviour & Information Technology 22, no. 2 (January 2003): 71–77. http://dx.doi.org/10.1080/0144929031000092222.

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48

Ketterl, Markus, Robert Mertens, and Oliver Vornberger. "Bringing Web 2.0 to web lectures." Interactive Technology and Smart Education 6, no. 2 (May 14, 2009): 82–96. http://dx.doi.org/10.1108/17415650910968099.

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49

Petren, John, and John Beidler. "ReUse/Web: Web-based Ada reuse." ACM SIGAda Ada Letters XVIII, no. 2 (March 1998): 81–88. http://dx.doi.org/10.1145/279578.279598.

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50

Qin, Li. "XBRL, semantic web and web services." International Journal of Business and Systems Research 5, no. 5 (2011): 443. http://dx.doi.org/10.1504/ijbsr.2011.042093.

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