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Google Adwords – Szkolenia Certyfikowane Szkolenia Sem
MAGAZYN MARKETINGU W WYSZUKIWARKACH www.semspecialist.pl • Numer 8/9 • lipiec-sierpień 2011 • ISSN 2082-3894 #8/9 GOOGLE PANDA UPDATE BIZNES LOKALNY MIEJSCA GOOGLE WYDAWCA Paulina Gawlińska Duarte Leszek Wolany e-mail: [email protected] ul. Studzienna 18/25 tel. 601 244 074 15-771 Białystok NIP: 966-174-99-46 GRAFIKA I SKŁAD Joanna Kołacz-Śmieja ADRES DO KORESPONDENCJI e-mail: [email protected] SEM Specialist ul. Zawiszy 16A/91 01-167 Warszawa PISZCIE DO NAS [email protected] Czekamy na Wasze komentarze i uwagi. REDAKTOR NACZELNY Jeśli chcesz publikować na łamach SEM Specialist Leszek Wolany – napisz z propozycją tematu. Redakcja nie zwraca nie zamówionych materiałów oraz zastrzega so- AUTORZY NUMERU bie prawo do skrótów i redakcyjnego opracowania tekstów przyjętych Mateusz Dałek, Adam Jankowiak, Marcin Kowalik, do publikacji. Paulina Niżankowska, Sebastian Suma, Michał Zawadzak. REKLAMA Za treść reklam i ogłoszeń redakcja nie odpowiada. © SEM Specialist 2010 Magazyn dystrybuowany jest dzieki Wszystkie prawa zastrzeżone. 2 SEM Specialist nr 8/9 lipiec-sierpień 2011 SPIS TREŚCI WYDARZENIA WARTO PRZECZYTAĆ FELIETON 8 KUP PAN BILET Marcin Kowalik 13 MIEJSCE GOOGLE A POZYCJONOWANIE STRONY Sebastian Suma 18 DOWIEDZ SIĘ, ILE +1 DOSTAŁA TWOJA WITRYNA Adam Jankowiak PPC 20 DEAL MIESIĄCA CZYLI GRUPOWE KAMPANIE LINKÓW SPONSOROWANYCH I ICH EFEKTY Paulina Niżankowska SEO 24 GOOGLE PANDA UPDATE Michał Zawadzak ANALITYKA 28 ŚCIEŻKI WIELOKANAŁOWE – OMÓWIENIE NOWEGO ZESTAWU RAPORTÓW DOSTĘPNEGO W RAMACH GOOGLE ANALYTICS Mateusz Dałek INFORMACJA PRASOWA 34 E-NNOVATION ODSŁANIA KARTY I PUBLIKUJE PROGRAM www.semspecialist.pl 3 ANI CHWILI SPOKOJU Wakacje dla większości z nas są leniwe, spokojne. Odpoczywamy, sta- ramy się trochę mniej myśleć o pracy. -
TRANSFORMING the SOCIO ECONOMY with DIGITAL INNOVATION This Page Intentionally Left Blank TRANSFORMING the SOCIO ECONOMY with DIGITAL INNOVATION
TRANSFORMING THE SOCIO ECONOMY WITH DIGITAL INNOVATION This page intentionally left blank TRANSFORMING THE SOCIO ECONOMY WITH DIGITAL INNOVATION CHIHIRO WATANABE Professor Emeritus, Tokyo Institute of Technology, Meguro, Tokyo, Japan Research Professor, University of Jyväskylä, Jyväskylä, Finland Guest Research Scholar, International Institute for Systems Analysis (IIASA), Laxenburg, Austria YUJI TOU Associate Professor, Tokyo Institute of Technology, Meguro, Tokyo, Japan PEKKA NEITTAANMÄKI Professor, University of Jyväskylä, Jyväskylä, Finland Elsevier Radarweg 29, PO Box 211, 1000 AE Amsterdam, Netherlands The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, United Kingdom 50 Hampshire Street, 5th Floor, Cambridge, MA 02139, United States Copyright © 2021 Elsevier Inc. All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Details on how to seek permission, further information about the Publisher’s permissions policies and our arrangements with organizations such as the Copyright Clearance Center and the Copyright Licensing Agency, can be found at our website: www.elsevier.com/permissions. This book and the individual contributions contained in it are protected under copyright by the Publisher (other than as may be noted herein). Notices Knowledge and best practice in this field are constantly changing. As new research and experience broaden our understanding, changes in research methods, professional practices, or medical treatment may become necessary. Practitioners and researchers must always rely on their own experience and knowledge in evaluating and using any information, methods, compounds, or experiments described herein. In using such information or methods they should be mindful of their own safety and the safety of others, including parties for whom they have a professional responsibility. -
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. -
Natural Language Processing Technique for Information Extraction and Analysis
International Journal of Research Studies in Computer Science and Engineering (IJRSCSE) Volume 2, Issue 8, August 2015, PP 32-40 ISSN 2349-4840 (Print) & ISSN 2349-4859 (Online) www.arcjournals.org Natural Language Processing Technique for Information Extraction and Analysis T. Sri Sravya1, T. Sudha2, M. Soumya Harika3 1 M.Tech (C.S.E) Sri Padmavati Mahila Visvavidyalayam (Women’s University), School of Engineering and Technology, Tirupati. [email protected] 2 Head (I/C) of C.S.E & IT Sri Padmavati Mahila Visvavidyalayam (Women’s University), School of Engineering and Technology, Tirupati. [email protected] 3 M. Tech C.S.E, Assistant Professor, Sri Padmavati Mahila Visvavidyalayam (Women’s University), School of Engineering and Technology, Tirupati. [email protected] Abstract: In the current internet era, there are a large number of systems and sensors which generate data continuously and inform users about their status and the status of devices and surroundings they monitor. Examples include web cameras at traffic intersections, key government installations etc., seismic activity measurement sensors, tsunami early warning systems and many others. A Natural Language Processing based activity, the current project is aimed at extracting entities from data collected from various sources such as social media, internet news articles and other websites and integrating this data into contextual information, providing visualization of this data on a map and further performing co-reference analysis to establish linkage amongst the entities. Keywords: Apache Nutch, Solr, crawling, indexing 1. INTRODUCTION In today’s harsh global business arena, the pace of events has increased rapidly, with technological innovations occurring at ever-increasing speed and considerably shorter life cycles. -
United States Patent (19) 11 Patent Number: 6,094,649 Bowen Et Al
US006094649A United States Patent (19) 11 Patent Number: 6,094,649 Bowen et al. (45) Date of Patent: Jul. 25, 2000 54) KEYWORD SEARCHES OF STRUCTURED “Charles Schwab Broadens Deployment of Fulcrum-Based DATABASES Corporate Knowledge Library Application', Uknown, Full 75 Inventors: Stephen J Bowen, Sandy; Don R crum Technologies Inc., Mar. 3, 1997, pp. 1-3. Brown, Salt Lake City, both of Utah (List continued on next page.) 73 Assignee: PartNet, Inc., Salt Lake City, Utah 21 Appl. No.: 08/995,700 Primary Examiner-Hosain T. Alam 22 Filed: Dec. 22, 1997 Assistant Examiner Thuy Pardo Attorney, Agent, or Firm-Computer Law---- (51) Int. Cl." ...................................................... G06F 17/30 52 U.S. Cl. ......................................... 707/3; 707/5; 707/4 (57 ABSTRACT 58 Field of Search .................................... 707/1, 2, 3, 4, 707/5, 531, 532,500 Methods and Systems are provided for Supporting keyword Searches of data items in a structured database, Such as a 56) References Cited relational database. Selected data items are retrieved using U.S. PATENT DOCUMENTS an SQL query or other mechanism. The retrieved data values 5,375,235 12/1994 Berry et al. ................................. is are documented using a markup language such as HTML. 5,469,354 11/1995 Hatakeyama et al. ... 707/3 The documents are indexed using a web crawler or other 5,546,578 8/1996 Takada ................. ... 707/5 indexing agent. Data items may be Selected for indexing by 5,685,003 11/1997 Peltonen et al. .. ... 707/531 5,787.295 7/1998 Nakao ........... ... 707/500 identifying them in a data dictionary. The indexing agent 5,787,421 7/1998 Nomiyama .. -
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. -
Digital Marketing Report for Q4, 2011
RKG Digital Marketing Report Q4.2011 Table of Contents Executive Summary Paid search spend growth accelerated in Q4 to a 31% year over 2 Executive Summary year rate, up from 20.9% in Q3. Higher click-through rates were the primary driver as impression growth was limited to 5.5% and 3 Methodology & About RKG cost-per-click declined 1.4% Y/Y. 4 Paid Search Google paid search spend increased 38.5% Y/Y on a 46% • Overall increase in clicks. CPC declined 5.2% as a shift to mobile and • Google other ad formats, as well as increased advertiser rationality, • Bing & Yahoo brought downward pressure on click costs. • Google vs Bing • Mobile Trends Bing and Yahoo non-brand paid search spend fell 6.1% Y/Y in • 2011 Trends Q4, an improvement from Q3 as 2010 comps weakened. Higher brand keyword costs for advertisers could drive Bing’s and Yahoo’s 11 SEO combined paid search revenue growth into positive territory. • Overall Google increased its search lead over Bing & Yahoo in Q4, generating • Link Development 86.5% of paid clicks and 83.5% of organic search visits. • Google vs Bing • Mobile and Other Mobile, including smartphones and tablets, contributed 9.6% of paid and organic search traffic for the full fourth quarter of 15 Facebook Advertising 2011, but surged to 14.2% of paid traffic at the end of the year. 17 Comparison Shopping Engines Amazon’s Kindle Fire quickly jumped to second place in the tablet space with 4.1% of tablet traffic compared to the iPad’s 87.8%. -
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. -
1.3.4 Web Technologies Concise Notes
OCR Computer Science A Level 1.3.4 Web Technologies Concise Notes www.pmt.education Specification 1.3.4 a) ● HTML ● CSS ● JavaScript 1.3.4 b) ● Search engine indexing 1.3.4 c) ● PageRank algorithm 1.3.4 d) ● Server and Client side processing www.pmt.education Web Development HTML ● HTML is the language/script that web pages are written in, ● It allows a browser to interpret and render a webpage for the viewer by describing the structure and order of the webpage. ● The language uses tags written in angle brackets (<tag>, </tag>) there are two sections of a webpage, a body and head. HTML Tags ● <html> : all code written within these tags is interpreted as HTML, ● <body> :Defines the content in the main browser content area, ● <link> :this is used to link to a css stylesheet (explained later in the notes) ● <head> :Defines the browser tab or window heading area, ● <title> :Defines the text that appears with the tab or window heading area, ● <h1>, <h2>, <h3> :Heading styles in decreasing sizes, ● <p> :A paragraph separated with a line space above and below ● <img> :Self closing image with parameters (img src = location, height=x, width = y) ● <a> : Anchor tag defining a hyperlink with location parameters (<a href= location> link text </a>) ● <ol> :Defines an ordered list, ● <ul> :Defines an unordered list, ● <li> :defines an individual list item ● <div> :creates a division of a page into separate areas each which can be referred to uniquely by name, (<div id= “page”>) Classes and Identifiers ● Class and identifier selectors are the names which you style, this means groups of items can be styled, the selectors for html are usually the div tags. -
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