Awareness and Utilization of Search Engines for Information Retrieval by Students of National Open University of Nigeria in Enugu Study Centre Library
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Search Techniques: Web Based Search MODULE - 5B INFORMATION RETRIEVAL SYSTEM
Search Techniques: Web Based Search MODULE - 5B INFORMATION RETRIEVAL SYSTEM 18 Notes SEARCH TECHNIQUES: WEB BASED SEARCH 18.1 INTRODUCTION Internet has become the biggest repository of information in the world. It can be considered as a global library where variety of information in different languages and formats is stored in digital form. The volume of information on web is enormous and it has become near to impossible to estimate its size. Because of its size and storing mechanism, finding relevant and precise information has become a difficult task. For searching information from this vast repository, we use search engines. There are thousands of search engines available on internet. For example, if you visit http://www.thesearchen ginelist.com/, you will find a classified list of search engines. This list is category-wise and includes all-purpose search engines in various fields like accounting, blogs, books, legal, medical, etc. In Lesson 17, you studied basic concepts of search techniques. Here, you will learn various aspects of searching information on web. 18.2 OBJECTIVES After studying this lesson, you will be able to: explain purpose of simple and advanced search techniques; develop search string using Boolean logic on a given topic; illustrate search string with the help of a diagram; give examples of simple search and advanced search on internet; identify various Search Engines, viz. Google, Yahoo, Google Scholar; LIBRARY AND INFORMATION SCIENCE 367 MODULE - 5B Search Techniques: Web Based Search INFORMATION RETRIEVAL SYSTEM identify Search Engines on internet in different vernacular languages; illustrate search in specific categories, viz. maps, images; and modify search strings to get precise results. -
Gender and Information Literacy: Evaluation of Gender Differences in a Student Survey of Information Sources
Gender and Information Literacy: Evaluation of Gender Differences in a Student Survey of Information Sources Arthur Taylor and Heather A. Dalal Information literacy studies have shown that college students use a va- riety of information sources to perform research and commonly choose Internet sources over traditional library sources. Studies have also shown that students do not appear to understand the information quality issues concerning Internet information sources and may lack the information literacy skills to make good choices concerning the use of these sources. No studies currently provide clear guidance on how gender might influ- ence the information literacy skills of students. Such guidance could help improve information literacy instruction. This study used a survey of college-aged students to evaluate a subset of student information literacy skills in relation to Internet information sources. Analysis of the data collected provided strong indications of gender differences in information literacy skills. Female respondents ap- peared to be more discerning than males in evaluating Internet sources. Males appeared to be more confident in the credibility and accuracy of the results returned by search engines. Evaluation of other survey responses strengthened our finding of gender differentiation in informa- tion literacy skills. ollege students today have come of age surrounded by a sea of information delivered from an array of sources available at their fingertips at any time of the day or night. Studies have shown that the most common source of information for college-aged students is the Internet. Information gathered in this environment is most likely found using a commercial search engine that returns sources of dubious quality using an unknown algorithm. -
Document Selection in a Distributed Search Engine Architecture Ibrahim
Document Selection in a Distributed Search Engine Architecture 1Ibrahim AlShourbaji, 2Samaher Al-Janabi and 3Ahmed Patel 1Computer Network Department, Computer Science and Information System College, Jazan University, Jazan 82822-6649, Saudi Arabia 2Department of Information Networks, Faculty of Information Technology,University of Babylon, Babylon, Hilla 00964, Iraq 3Visiting Professor School of Computing and Information Systems, Faculty of Science, Engineering and Computing, Kingston University, Kingston upon Thames KT1 2EE, United Kingdom Abstract Distributed Search Engine Architecture (DSEA) hosts numerous independent topic-specific search engines and selects a subset of the databases to search within the architecture. The objective of this approach is to reduce the amount of space needed to perform a search by querying only a subset of the total data available. In order to manipulate data across many databases, it is most efficient to identify a smaller subset of databases that would be most likely to return the data of specific interest that can then be examined in greater detail. The selection index has been most commonly used as a method for choosing the most applicable databases as it captures broad information about each database and its indexed documents. Employing this type of database allows the researcher to find information more quickly, not only with less cost, but it also minimizes the potential for biases. This paper investigates the effectiveness of different databases selected within the framework and scope of the distributed search engine architecture. The purpose of the study is to improve the quality of distributed information retrieval. Keywords: web search, distributed search engine, document selection, information retrieval, Collection Retrival Inference network 1. -
Information Technology: Applications DLIS408
Information Technology: Applications DLIS408 Edited by: Jovita Kaur INFORMATION TECHNOLOGY: APPLICATIONS Edited By Jovita Kaur Printed by LAXMI PUBLICATIONS (P) LTD. 113, Golden House, Daryaganj, New Delhi-110002 for Lovely Professional University Phagwara DLP-7765-079-INFO TECHNOLOGY APPLICATION C-4713/012/02 Typeset at: Shubham Composers, Delhi Printed at: Sanjay Printers & Publishers, Delhi SYLLABUS Information Technology: Applications Objectives: • To understand the applications of Information technology in organizations. • To appreciate how information technology can help to improve decision-making in organizations. • To appreciate how information technology is used to integrate the business disciplines. • To introduce students to business cases, so they learn to solve business problems with information technology. • To introduce students to the strategic applications of information technology. • To introduce students to the issues and problems involved in building complex systems and organizing information resources. • To introduce students to the social implications of information technology. • To introduce students to the management of information systems. S. No. Topics Library automation: Planning and implementation, Automation of housekeeping operations – Acquisition, 1. Cataloguing, Circulation, Serials control OPAC Library management. 2. Library software packages: RFID, LIBSYS, SOUL, WINISIS. 3. Databases: Types and generations, salient features of select bibliographic databases. 4. Communication technology: Fundamentals communication media and components. 5. Network media and types: LAN, MAN, WAN, Intranet. 6. Digital, Virtual and Hybrid libraries: Definition and scope. Recent development. 7. Library and Information Networks with special reference to India: DELNET, INFLIBNET, ERNET, NICNET. Internet—based resources and services Browsers, search engines, portals, gateways, electronic journals, mailing 8. list and scholarly discussion lists, bulletin board, computer conference and virtual seminars. -
Final Study Report on CEF Automated Translation Value Proposition in the Context of the European LT Market/Ecosystem
Final study report on CEF Automated Translation value proposition in the context of the European LT market/ecosystem FINAL REPORT A study prepared for the European Commission DG Communications Networks, Content & Technology by: Digital Single Market CEF AT value proposition in the context of the European LT market/ecosystem Final Study Report This study was carried out for the European Commission by Luc MEERTENS 2 Khalid CHOUKRI Stefania AGUZZI Andrejs VASILJEVS Internal identification Contract number: 2017/S 108-216374 SMART number: 2016/0103 DISCLAIMER By the European Commission, Directorate-General of Communications Networks, Content & Technology. The information and views set out in this publication are those of the author(s) and do not necessarily reflect the official opinion of the Commission. The Commission does not guarantee the accuracy of the data included in this study. Neither the Commission nor any person acting on the Commission’s behalf may be held responsible for the use which may be made of the information contained therein. ISBN 978-92-76-00783-8 doi: 10.2759/142151 © European Union, 2019. All rights reserved. Certain parts are licensed under conditions to the EU. Reproduction is authorised provided the source is acknowledged. 2 CEF AT value proposition in the context of the European LT market/ecosystem Final Study Report CONTENTS Table of figures ................................................................................................................................................ 7 List of tables .................................................................................................................................................. -
A Comparative Analysis of the Search Feature Effectiveness of the Major English and Chinese Search Engines
The current issue and full text archive of this journal is available at www.emeraldinsight.com/1468-4527.htm Search feature A comparative analysis of the effectiveness search feature effectiveness of the major English and Chinese search engines 217 Refereed article received Jin Zhang 6 July 2011 School of Information Studies, University of Wisconsin Milwaukee, Approved for publication Milwaukee, Wisconsin, USA 5 May 2012 Wei Fei Suzhou Library, Suzhou, China, and Taowen Le Goddard School of Business and Economics, Weber State University, Ogden, Utah, USA Abstract Purpose – The purpose of this paper to investigate the effectiveness of selected search features in the major English and Chinese search engines and compare the search engines’ retrieval effectiveness. Design/approach/methodology – The search engines Google, Google China, and Baidu were selected for this study. Common search features such as title search, basic search, exact phrase search, PDF search, and URL search, were identified and used. Search results from using the five features in the search engines were collected and compared. One-way ANOVA and regression analysis were used to compare the retrieval effectiveness of the search engines. Findings – It was found that Google achieved the best retrieval performance with all five search features among the three search engines. Moreover Google achieved the best webpage ranking performance. Practical implications – The findings of this study improve the understanding of English and Chinese search engines and the differences between them in terms of search features, and can be used to assist users in choosing appropriate and effective search strategies when they search for information on the internet. -
Shaping the Web: Why the Politics of Search Engines Matters
TheInformation Society, 16:169 –185, 2000 Copyright c 2000T aylor& Francis 0197-2243/° 00$12.00+ .00 Shaping the Web: Whythe Politics ofSearch Engines Matters Lucas D.Introna LondonSchool of Economics,London, United Kingdom Helen Nissenbaum University Center for HumanV alues,Princeton University, Princeton,New Jersey,USA Enhancedby the technologyof the WorldWide W eb,it This articleargues that searchengines raise not merely technical has becomean integral part ofthe ever-expandingglobal issuesbut alsopolitical ones. Our studyof searchengines suggests media system, movingonto center stage ofmedia politics thatthey systematically exclude (in somecases by design and in alongsidetraditional broadcastmedia— television andra- some,accidentally ) certainsites and certaintypes of sitesin favor dio.Enthusiasts ofthe “newmedium” have heralded it as ofothers,systematically giving prominence to some at theexpense ademocratizingforce that will givevoice to diverse so- ofothers. We argue that such biases,which would leadto a nar- cial, economic,and cultural groups,to members ofsociety rowingof theWeb’ s functioningin society,run counterto thebasic notfrequentlyheard in the publicsphere. It will empower architectureof the Web aswell as tothevalues and idealsthat have the traditionally disempowered,giving them access both fueledwidespread support for its growth and development.We to typically unreachablenodes of powerand to previously considerways of addressingthe politics of searchengines, raising inaccessible troves ofinformation. doubts whether,in -
Merging Multiple Search Results Approach for Meta-Search Engines
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by D-Scholarship@Pitt MERGING MULTIPLE SEARCH RESULTS APPROACH FOR META-SEARCH ENGINES By Khaled Abd-El-Fatah Mohamed B.S-------- Cairo University, Egypt, 1995 M.A-------Cairo University, Egypt, 1999 M.A------- University of Pittsburgh 2001 Submitted to the Graduate Faculty of School of Information Sciences in Partial Fulfillment of the requirements for the degree of Doctor of Philosophy University of Pittsburgh 2004 UNIVERSITY OF PITTSBURGH INFORMATION SCIENCES This dissertation was presented by Khaled Abd-El-Fatah Mohamed It was defended on Janauary 29, 2004 and approved by Chris Tomer, PhD, Associate Professor, DLIS Jose-Marie Griffiths, PhD, Professor, DLIS Don King, Research Professor, DLIS Amy Knapp, PhD, ULS Dissertation Director: Chris Tomer, PhD, Associate Professor MERGING MULTIPLE SEARCH RESULTS APPROACH FOR META-SEARCH ENGINES Khaled A. Mohamed, PhD University of Pittsburgh, 2004 Meta Search Engines are finding tools developed for enhancing the search performance by submitting user queries to multiple search engines and combining the search results in a unified ranked list. They utilized data fusion technique, which requires three major steps: databases selection, the results combination, and the results merging. This study tries to build a framework that can be used for merging the search results retrieved from any set of search engines. This framework based on answering three major questions: 1. How meta-search developers could define the optimal rank order for the selected engines. 2. How meta-search developers could choose the best search engines combination. 3. What is the optimal heuristic merging function that could be used for aggregating the rank order of the retrieved documents form incomparable search engines. -
Meta Search Engine with an Intelligent Interface for Information Retrieval on Multiple Domains
International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.1, No.4, October 2011 META SEARCH ENGINE WITH AN INTELLIGENT INTERFACE FOR INFORMATION RETRIEVAL ON MULTIPLE DOMAINS D.Minnie1, S.Srinivasan2 1Department of Computer Science, Madras Christian College, Chennai, India [email protected] 2Department of Computer Science and Engineering, Anna University of Technology Madurai, Madurai, India [email protected] ABSTRACT 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. KEYWORDS Information Retrieval, Web Search Engine, Vertical Search Engine, Meta Search Engine. 1. INTRODUCTION AND RELATED WORK WWW is a huge repository of information. The complexity of accessing the web data has increased tremendously over the years. There is a need for efficient searching techniques to extract appropriate information from the web, as the users require correct and complex information from the web. A Web Search Engine is a search engine designed to search WWW for information about given search query and returns links to various documents in which the search query’s key words are found. -
List of Search Engines
A blog network is a group of blogs that are connected to each other in a network. A blog network can either be a group of loosely connected blogs, or a group of blogs that are owned by the same company. The purpose of such a network is usually to promote the other blogs in the same network and therefore increase the advertising revenue generated from online advertising on the blogs.[1] List of search engines From Wikipedia, the free encyclopedia For knowing popular web search engines see, see Most popular Internet search engines. This is a list of search engines, including web search engines, selection-based search engines, metasearch engines, desktop search tools, and web portals and vertical market websites that have a search facility for online databases. Contents 1 By content/topic o 1.1 General o 1.2 P2P search engines o 1.3 Metasearch engines o 1.4 Geographically limited scope o 1.5 Semantic o 1.6 Accountancy o 1.7 Business o 1.8 Computers o 1.9 Enterprise o 1.10 Fashion o 1.11 Food/Recipes o 1.12 Genealogy o 1.13 Mobile/Handheld o 1.14 Job o 1.15 Legal o 1.16 Medical o 1.17 News o 1.18 People o 1.19 Real estate / property o 1.20 Television o 1.21 Video Games 2 By information type o 2.1 Forum o 2.2 Blog o 2.3 Multimedia o 2.4 Source code o 2.5 BitTorrent o 2.6 Email o 2.7 Maps o 2.8 Price o 2.9 Question and answer . -
Information Rereival, Part 1
11/4/2019 Information Retrieval Deepak Kumar Information Retrieval Searching within a document collection for a particular needed information. 1 11/4/2019 Query Search Engines… Altavista Entireweb Leapfish Spezify Ask Excite Lycos Stinky Teddy Baidu Faroo Maktoob Stumpdedia Bing Info.com Miner.hu Swisscows Blekko Fireball Monster Crawler Teoma ChaCha Gigablast Naver Walla Dogpile Google Omgili WebCrawler Daum Go Rediff Yahoo! Dmoz Goo Scrub The Web Yandex Du Hakia Seznam Yippy Egerin HotBot Sogou Youdao ckDuckGo Soso 2 11/4/2019 Search Engine Marketshare 2019 3 11/4/2019 Search Engine Marketshare 2017 Matching & Ranking matched pages ranked pages 1. 2. query 3. muddy waters matching ranking “hits” 4 11/4/2019 Index Inverted Index • A mapping from content (words) to location. • Example: the cat sat on the dog stood on the cat stood 1 2 3 the mat the mat while a dog sat 5 11/4/2019 Inverted Index the cat sat on the dog stood on the cat stood 1 2 3 the mat the mat while a dog sat a 3 cat 1 3 dog 2 3 mat 1 2 on 1 2 sat 1 3 stood 2 3 the 1 2 3 while 3 Inverted Index the cat sat on the dog stood on the cat stood 1 2 3 the mat the mat while a dog sat a 3 cat 1 3 dog 2 3 mat 1 2 Every word in every on 1 2 web page is indexed! sat 1 3 stood 2 3 the 1 2 3 while 3 6 11/4/2019 Searching the cat sat on the dog stood on the cat stood 1 2 3 the mat the mat while a dog sat a 3 cat 1 3 query dog 2 3 mat 1 2 cat on 1 2 sat 1 3 stood 2 3 the 1 2 3 while 3 Searching the cat sat on the dog stood on the cat stood 1 2 3 the mat the mat while a dog sat a 3 cat -
Websites from Presentation 4 Handout
Websites from Presentation Search Engines Google https://www.google.com/ Google Scholar https://scholar.google.com/ Google Advanced Search https://www.google.com/advanced_search USA.gov https://www.usa.gov/ Duck Duck Go https://duckduckgo.com/ Bing https://www.bing.com/ Yahoo https://www.yahoo.com/ Yahoo Advanced Search http://www.vcrlter.virginia.edu/yahoosearch.html Excite http://www.excite.com/ Lycos http://www.lycos.com/ Dogpile https://www.dogpile.com/ Yippy https://yippy.com/ Webopedia https://www.webopedia.com/ Way Back Machine https://archive.org/index.php People Search Engines True People Search https://www.truepeoplesearch.com/ White Pages https://www.whitepages.com/ Public Record Directories Search Systems http://publicrecords.searchsystems.net/ BRB https://www.brbpublications.com/ Online Searches https://publicrecords.onlinesearches.com/ Portico http://www.indorgs.virginia.edu/portico/home.html Black Book Online https://www.blackbookonline.info/ NETR Online https://publicrecords.netronline.com/ Legal Dockets https://legaldockets.com/ Law Enforcement Directory https://www.policeone.com/law-enforcement-directory/ Public Record Retriever Network https://www.prrn.us/content/Search.aspx Courts and Criminal Mississippi Electronic Courts (MEC) https://courts.ms.gov/mec/mec.php PACER https://pacer.login.uscourts.gov/csologin/login.jsf Court Listener & RECAP https://www.courtlistener.com/ Mississippi Administrative Office of Courts https://courts.ms.gov/aoc/aoc.php Tribal Court Clearinghouse https://www.tribal-institute.org/ United