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Awareness and Utilization of Search Engines for Information Retrieval by Students of National Open University of Nigeria in Enugu Study Centre Library
University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln Library Philosophy and Practice (e-journal) Libraries at University of Nebraska-Lincoln 2020 Awareness and Utilization of Search Engines for Information Retrieval by Students of National Open University of Nigeria in Enugu Study Centre Library SUNDAY JUDE ONUH National Open University of Nigeria, [email protected] OGOEGBUNAM LOVETH EKWUEME National Open University of Nigeria, [email protected] Follow this and additional works at: https://digitalcommons.unl.edu/libphilprac Part of the Library and Information Science Commons ONUH, SUNDAY JUDE and EKWUEME, OGOEGBUNAM LOVETH, "Awareness and Utilization of Search Engines for Information Retrieval by Students of National Open University of Nigeria in Enugu Study Centre Library" (2020). Library Philosophy and Practice (e-journal). 4650. https://digitalcommons.unl.edu/libphilprac/4650 Awareness and Utilization of Search Engines for Information Retrieval by Students of National Open University of Nigeria in Enugu Study Centre Library By Jude Sunday Onuh Enugu Study Centre Library National Open University of Nigeria [email protected] & Loveth Ogoegbunam Ekwueme Department of Library and Information Science National Open University of Nigeria [email protected] Abstract This study dwelt on awareness and utilization of search engines for information retrieval by students of National Open University of Nigeria (NOUN) Enugu Study centre. Descriptive survey research was adopted for the study. Two research questions were drawn from the two purposes that guided the study. The population consists of 5855 undergraduate students of NOUN Enugu Study Centre. A sample size of 293 students was used as 5% of the entire population. -
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. -
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. -
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. -
Downloads the Lists of Search Engines and Query Terms That Are Previously Defined As Part of an Experimental Design
Running Head: ALGORITHM AUDITING AT A LARGE-SCALE 1 Algorithm Auditing at a Large-Scale: Insights from Search Engine Audits Roberto Ulloa1, Mykola Makhortykh2 and Aleksandra Urman3 1 GESIS – Leibniz-Institute for the Social Sciences 2 University of Bern 3 University of Zurich Author Note We have no conflicts of interest to disclose. This is a preprint and working version of the paper. Data collections were sponsored from the SNF (100001CL_182630/1) and DFG (MA 2244/9-1) grant for the project “Reciprocal relations between populist radical-right attitudes and political information behaviour: A longitudinal study of attitude development in high- choice information environments” lead by Silke Adam (U of Bern) and Michaela Maier (U of Koblenz-Landau) and FKMB (the Friends of the Institute of Communication and Media Science at the University of Bern) grant “Algorithmic curation of (political) information and its biases” awarded to Mykola Makhortykh and Aleksandra Urman. Running Head: ALGORITHM AUDITING AT A LARGE-SCALE 2 Abstract Algorithm audits have increased in recent years due to a growing need to independently assess the performance of automatically curated services that process, filter and rank the large and dynamic amount of information available on the internet. Among several methodologies to perform such audits, virtual agents stand out because they offer the ability to perform systematic experiments, simulating human behaviour without the associated costs of recruiting participants. Motivated by the importance of research transparency and replicability of results, this paper focuses on the challenges of such an approach. It provides methodological details, recommendations, lessons learned and limitations that researchers should take into consideration when setting up experiments with virtual agents. -
Seo-101-Guide-V7.Pdf
Copyright 2017 Search Engine Journal. Published by Alpha Brand Media All Rights Reserved. MAKING BUSINESSES VISIBLE Consumer tracking information External link metrics Combine data from your web Uploading backlink data to a crawl analytics. Adding web analytics will also identify non-indexable, redi- data to a crawl will provide you recting, disallowed & broken pages with a detailed gap analysis and being linked to. Do this by uploading enable you to find URLs which backlinks from popular backlinks have generated traffic but A checker tools to track performance of AT aren’t linked to – also known as S D BA the most link to content on your site. C CK orphans. TI L LY IN A K N D A A T B A E W O R G A A T N A I D C E S IL Search Analytics E F Crawler requests A G R O DeepCrawl’s Advanced Google CH L Integrate summary data from any D Search Console Integration ATA log file analyser tool into your allows you to connect technical crawl. Integrating log file data site performance insights with enables you to discover the pages organic search information on your site that are receiving from Google Search Console’s attention from search engine bots Search Analytics report. as well as the frequency of these requests. Monitor site health Improve your UX Migrate your site Support mobile first Unravel your site architecture Store historic data Internationalization Complete competition Analysis [email protected] +44 (0) 207 947 9617 +1 929 294 9420 @deepcrawl Free trail at: https://www.deepcrawl.com/free-trial Table of Contents 9 Chapter 1: 20 -
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 . -
List of Search Engines Listed by Types of Searches
List of Search Engines Listed by Types of Searches - © 09-14-2014 - images removed Copyright - Professional Web Services Internet Marketing SEO Business Solutions - http://pwebs.net - All Rights Reserved List of Search Engines Listed by Types of Searches by ProWebs - Article last updated on: Saturday, July 28, 2012 http://pwebs.net/2011/04/search-engines-list/ To view images click link above. This page posting has been updated with the addition of some of the newer search engines. The original search engine page was dealing mainly with B2B and B2C search. However, with today's broad based Internet activity, and how it relates to various aspects of business usage, personal searches, and even internal intranet enterprise searches, we wanted to highlight some of the different search market segments. This list of the various search engines, is posted here mainly for research and education purposes. We felt it is nice to be able to reference and have links to some of the different search engines all in one place. While the list below does not cover each and every search engine online, it does provide a broad list of most of the major search companies that are available. Also note that some of the search engine links have been redirected to other sites due to search buyouts, mergers, and acquisitions with other companies, along with changes with the search engines themselves (for example: search companies have changed brand names, different URLs, and links). You will also notice that some of the search websites go back a number of years. If you would like to read more about the details of any particular search engine, take a look at the Wikipedia Search Engines List article, and follow the links to each specific search engine for a descriptive overview. -
Michigan IT Lawyer a Publication of the State Bar of Michigan Information Technology Law Section
State Bar of Michigan Michigan IT Lawyer A Publication of the State Bar of Michigan Information Technology Law Section http://www.michbar.org/computer Table of Contents Bits and Bytes from the Chair March 2010 . Vol. 27, Issue 2 By Jeremy D. Bisdorf, Jaffe Raitt Heuer & Weiss PC . Bits and Bytes from the Chair ................1 . Recent Developments in Information I am excited about our next Section event! Please keep your calendars Technology Law .....................................2 clear to participate in our Spring Networking Event on Thursday, April 15, . Meet a Section Member ......................... 6 2010 at the Post Bar in Novi from 5:00 – 8:00 PM. Our Section will be a co-sponsor of one of Michigan’s premier I.T. networking events, attended by . Google and Antitrust ............................... 7 hundreds of I.T. professionals, recruiters, job-seekers and lawyers. There will be no cost to our members to attend the event. For more information, check . Publicly Available Websites for IT www.detroitnet.org and our Section website at www.michbar.org/computer. Lawyers ................................................. 17 We are about half-way through our Section’s year (we begin the year with . Save the Date ........................................ 18 our Annual Meeting in September). The first half of the year has included some solid planning sessions and involvement in interesting activities. Our section . 2010 Edward F. Langs Writing Award ... 18 has had the opportunity to provide input on recent proposed legislation per- taining to amending Michigan’s Uniform Electronic Transaction Act. We have also held a seminar at Cooley Law School’s Ann Arbor campus on Intellectual Property Escrow Agreements.