DOCSLIB.ORG

Utilizing Query Performance Predictors for Early Termination in Meta-Search

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Utilizing Query Performance Predictors for Early Termination in Meta-Search UTILIZING QUERY PERFORMANCE PREDICTORS FOR EARLY TERMINATION IN META-SEARCH A THESIS SUBMITTED TO THE GRADUATE SCHOOL OF NATURAL AND APPLIED SCIENCES OF MIDDLE EAST TECHNICAL UNIVERSITY BY EMRE ŞENER IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE IN COMPUTER ENGINEERING AUGUST 2016 Approval of the thesis: UTILIZING QUERY PERFORMANCE PREDICTORS FOR EARLY TERMINATION IN META-SEARCH submitted by EMRE ŞENER in partial fulfillment of the requirements for the degree of Master of Science in Computer Engineering Department, Middle East Technical University by, Prof. Dr. Gülbin Dural Ünver _____________ Dean, Graduate School of Natural and Applied Sciences Prof. Dr. Adnan Yazıcı _____________ Head of Department, Computer Engineering Assoc. Prof. Dr. İsmail Sengör Altıngövde _____________ Supervisor, Computer Engineering Department, METU Examining Committee Members: Prof. Dr. İsmail Hakkı Toroslu _____________ Computer Engineering Department, METU Assoc. Prof. Dr. İsmail Sengör Altıngövde _____________ Computer Engineering Department, METU Assoc. Prof. Dr. Pınar Karagöz _____________ Computer Engineering Department, METU Assist. Prof. Dr. Selim Temizer _____________ Computer Engineering Department, METU Assist. Prof. Dr. Engin Demir _____________ Computer Engineering Department, UTAA Date: 22.08.2016 I hereby declare that all information in this document has been obtained and presented in accordance with academic rules and ethical conduct. I also declare that, as required by these rules and conduct, I have fully cited and referenced all material and results that are not original to this work. Name, Last name: Emre ŞENER Signature: iv ABSTRACT UTILIZING QUERY PERFORMANCE PREDICTORS FOR EARLY TERMINATION IN META-SEARCH Şener, Emre M.S., Department of Computer Engineering Supervisor: Assoc. Prof. Dr. İsmail Sengör Altıngövde August 2016, 153 pages In the context of web, a meta-search engine is a system that forwards an incoming user query to all the component search engines (aka, resources); and then merges the retrieved results. Given that hundreds of such resources may exist, it is mandatory for a meta-search engine to avoid forwarding a query to all available resources, but rather focus on a subset of them. In this thesis, we first introduce a novel incremental query forwarding strategy for meta-search. More specifically, given a ranked list of N search engines, our strategy operates in rounds, such that in each round, we retrieve the results of the next k “unvisited” resources in the list (where k<N), asses the quality of the intermediate merged list, and stop if any further quality improvement seems unlikely. As our second contribution, we introduce a novel incremental query result merging strategy. In this strategy, we forward query to all search engines but we assess the quality of intermediate merged lists as early as we retrieve the results from an engine and stop if any further quality improvements are not likely. In order to assess the result quality, we utilize post-retrieval query performance prediction (QPP) techniques. Our experiments using the standard FedWeb 2013 dataset reveal that the proposed strategies can reduce the response v time and/or network bandwidth usage, while the quality of the result is comparable to, or sometimes, even better than the baseline strategy. Keywords: Meta-search Engines, Query Performance Prediction, Evaluation vi ÖZ META-ARAMA İÇİN SORGU PERFORMANS TAHMİNİ YÖNTEMLERİYLE ERKEN SONUÇ OLUŞTURMA Şener, Emre Yüksek Lisans, Bilgisayar Mühendisliği Bölümü Tez Yöneticisi: Doç. Dr. İsmail Sengör Altıngövde Ağustos 2016, 153 sayfa Meta-arama motorları diğer kaynaklardan gelen sorgu sonuçlarını kullanarak sonuç listesi oluştururlar. Bu tez ile meta-arama motorlarındaki sorgu maliyetini düşürmeyi hedeflemekteyiz. Bu amaçla, ilk olarak seçilen arama kaynaklarının hepsine birden sorgunun yönlendirilmesi yerine, artırımlı olarak daha küçük k elemanlı alt kümelere sorgunun yönlendirilmesini öneriyoruz. Artırımlı olarak yönlendirilen alt kümedeki kaynaklardan gelen sonuçlara sorgu performans tahmini adımını ekleyerek, sorgu performans tahmini değerine göre cevap kalitesini artırmayacağına karar verdiğimiz durumlarda kalan kaynaklara sorgunun gönderilmemesi ile sorgu maliyetinin azaltılmasını hedefliyoruz. Önerdiğimiz ikinci yöntemde ise, sorgu seçilen kaynakların hepsine birden yönlendiriliyor ancak, herhangi bir kaynaktan sonuç gelir gelmez ara listeleri birleştirip, sorgu performans tahmini ile daha sonraki kaynaklardan gelecek cevapların sonuç kalitesini artırmayacağına karar verdiğimiz durumlarda, bu ara listeyi kullanıcıya dönerek sorgu zamanını azaltmayı hedefliyoruz. Yöntemlerimizi FedWeb 2013 verisi üstünde test ettik ve deney sonuçlarından artırımlı sorgu işleme yöntemlerimizin tüm seçilen kaynaklara tek seferde göndermeye göre sorgu maliyetini ve/veya ağ kaynakları kullanımını düşürdüğünü gördük. vii Anahtar Kelimeler: Meta-arama Motorları, Sorgu Performans Ölçümü, Performans Değerlendirmesi viii To My Precious Wife ix ACKNOWLEDGEMENTS I would like to enounce my deep gratitude to my supervisor Assoc. Prof Dr. İsmail Sengör Altıngövde for his valuable supervision, advice, useful critics and discussions throughout this study. I am also grateful to my thesis committee members for their criticism and advices. This research project is jointly supported by Ministry of Science, Industry and Technology of Turkey and Huawei Telekomünikasyon Ltd. Co. under SAN-TEZ funding program with the project number 0441.STZ.2013-2. x TABLE OF CONTENTS ABSTRACT ................................................................................................................. v ÖZ .............................................................................................................................. vii ACKNOWLEDGEMENTS ......................................................................................... x TABLE OF CONTENTS ............................................................................................ xi LIST OF TABLES ..................................................................................................... xv LIST OF FIGURES ................................................................................................ xxxi LIST OF ABBREVATIONS ................................................................................. xxxii CHAPTERS ................................................................................................................. 1 1. INTRODUCTION ................................................................................................ 1 2. RELATED WORK ............................................................................................... 5 3. UTILIZING QUERY PERFORMANCE PREDICTORS FOR EARLY TERMINATION IN META-SEARCH ..................................................................... 11 3.1. QPP Based Adaptive Incremental Query Forwarding in Meta-Search ....... 11 3.2. QPP Based Adaptive Incremental Query Result Merging in Meta-Search . 13 3.3. Resource Selection ...................................................................................... 15 xi 3.3.1. TWF-IRF ................................................................................................. 16 3.3.2. UISP ........................................................................................................ 16 3.3.3. Oracle ...................................................................................................... 16 3.3.4. FedWeb2013 Baseline ............................................................................. 17 3.3.5. ReDDE .................................................................................................... 17 3.3.6. Rank-S ..................................................................................................... 18 3.3.7. Adaptive-k ............................................................................................... 18 3.4. Result Merging ............................................................................................ 18 3.4.1. Oracle Merging ........................................................................................ 19 3.4.2. ISR ........................................................................................................... 19 3.4.3. RRF ......................................................................................................... 19 3.4.4. CombSUM ............................................................................................... 20 3.5. Query Performance Prediction (QPP) ......................................................... 21 3.5.1. SUM QPP ................................................................................................ 21 3.5.2. NDCG QPP ............................................................................................. 21 3.6. Learning to Stop .......................................................................................... 22 3.6.1. Adhoc Stopping Policies ......................................................................... 23 xii 3.6.2. Machine Learning Model ........................................................................ 24 3.6.2.1. QPP Ratio ..................................................................................... 25 3.6.2.2. QPP Difference ............................................................................. 25 4. EXPERIMENTS AND RESULTS ..................................................................... 27 4.1. Data Set ......................................................................................................
Load more

Recommended publications
  • [email protected] [email protected] Izadi [email protected]
    Boolify Safe Search Kids KidzSearch Safe Search Kids KidzSearch Boolify Kid'sSearch KidRex [email protected] [email protected] [email protected] . 1. Chromium Hope . Boolify Dib Dab Doo and Dilly Too 1. Broch 2. Talib, Mahmuddin & Husni 3. Large, Beheshti & Rahman 4. Large, Beheshti 5. Large Ask Kids Yahoo kids KidsClick 1. Huan-ling 2.Vanderschantz, Hinze, & Cunningham 3. Waikato 1. Duarte Torres, Weber & Hiemstra GoGooligans, Kiddle, Searchy Pants, Dmoz, Yahoo Kids (Yahooligans), Study Search, Famhoo, Onekey, SweetSearch KidzSearch Boolify Safe Search Kids Dib Dab Doo and Kidtopia Kid's Search Dilly Too IPL2 for Kids Awesome Library Thinga Cybersleuth kids y s s s r d d d s a i r i i o t h r e h d s k s e o K t B i c k r K b s c a i r s k d e c r r x i a h d N D o i K h r i a t i n l a e b L o p l g a c o r e f u b e o e K y r o e n K R l C r o e a S t - i c a m S i a l r f s d f r M k d i a s m h z i e d p s D ' i y d s i t 2 u r u i o g d o S T d t K c i b e s K i q L A K i n e T A K a e b i S K f P K F D y I u a w C S Q A + - - - - + - - - - - - - - - - + - - + + + + + + + + + + + + + + + + + + + + - - + - - + + + + + + + + + + + + + ry ds ds ds a i i i r er ds k et oo t B i ch K b K ch r i s ks ds ck r er r ia h ds N D i o r h K t i l ex L o li ga a c o ea r f u b e on ea K yb r op n e R l C o e a K t S - i a c S i m l rr f s d f r M k d i s m i h z ea d s D i d y s i t 2 u r u i o d ga op S T d' t K i b e i K A K i n e K T A ac es b i Sq K f PL K F D y I u a w C S Q A + - - + - - + + + + - + + + - + - + + - - - + - - -
    [Show full text]
  • Grade 6 Learning from Home: Day 2 Here Is Your Learning to Complete Whilst You Are at Home Today
    Grade 6 Learning from Home: Day 2 Here is your learning to complete whilst you are at home today. If you have any questions please feel free to send your teacher an email via Compass. Have a wonderful day of learning. Reading Learning Intention: To make a prediction before reading and give evidence from Focus ​ the text Success Criteria: I am successful when I can: Visit the website storybox online. The username and password are below: Activity ​ ​ Username: taylorshill Password: taylorshill Search for the following text: When the Wind Changed by Colin Lane ​ https://storyboxlibrary.com.au/stories/when-the-wind-changed Firstly, using information on the front cover, make a prediction. Don’t forget to activate your prior knowledge. ​ ​ Record your prediction in your Reading Slide on Google Drive. Remember to ​ ​ include the date, title of the text and your response. Then, listen to the story and check if your prediction was correct. Record the ​ ​ reasons why or why not your prediction was correct or incorrect. After this you are to complete 30mins of Independent Reading and complete a Track or work on your Reading Goal. Access Reading Eggspress and complete your assigned activities Writing / Writer’s Notebook / Spelling Learning Intention: To research and develop a plan Focus ​ Success Criteria: I am successful when I can: - Use keywords to research my topic - Find useful and appropriate websites - Put findings into my own words - Develop a user friendly plan - Plan the structure of a persuasive text (Title, opening statement, arguments with evidence and concluding statement) Activity Reflect on the topic you chose yesterday and begin to research, finding evidence to support your arguments .
    [Show full text]
  • Traffic 65788 93.29% 61375 1.22% 2.48 00:00:38 0.00% 0
    Why DO ­ http://why.do Go to this report All Web Site Data All Traffic Dec 18, 2013 ­ Mar 18, 2014 All Visits 100.00% Explorer Summary Visits 1,200 600 January 2014 February 2014 March 2014 Acquisition Behavior Conversions Source / Medium Pages / Goal Goal % New Visits Bounce Avg. Visit Visits New Visits Visit Conversion Completions Goal Value Rate Duration Rate 65,788 93.29% 61,375 1.22% 2.48 00:00:38 0.00% 0 $0.00 % of Total: Site Avg: % of Total: Site Avg: Site Site Avg: Site Avg: % of Total: % of Total: 100.00% (65,786) 93.26% 100.03% (61,355) 1.22% Avg: 00:00:38 0.00% 0.00% (0) 0.00% ($0.00) (0.03%) (0.25%) 2.48 (0.00%) (0.00%) (0.00%) 1. google / organic 46,350 (70.45%) 93.78% 43,467 (70.82%) 0.71% 2.42 00:00:35 0.00% 0 (0.00%) $0.00 (0.00%) 2. (direct) / (none) 12,223 (18.58%) 91.47% 11,180 (18.22%) 3.41% 2.67 00:00:48 0.00% 0 (0.00%) $0.00 (0.00%) 3. bing / organic 3,295 (5.01%) 94.54% 3,115 (5.08%) 0.67% 2.45 00:00:35 0.00% 0 (0.00%) $0.00 (0.00%) 4. yahoo / organic 919 (1.40%) 93.69% 861 (1.40%) 0.44% 2.34 00:00:28 0.00% 0 (0.00%) $0.00 (0.00%) 5. r.search.yahoo.com / referral 362 (0.55%) 95.86% 347 (0.57%) 0.83% 2.20 00:00:28 0.00% 0 (0.00%) $0.00 (0.00%) 6.
    [Show full text]
  • Case Study Aug A5 Revised
    may 2017 Author Fahmi Ramadhiansyah Editor Dirgayuza Setiawan, M.Sc Viyasa Rahyaputra Designer and Layouter Ristyanadya Laksmi Gupita Summary The internet is growing at the rate that is unstoppable. It does not only grow in terms of contents and adaptability, but most importantly, it also grows in terms of users. Children, in particular, have begun to access the internet, and they might be exposed to ‘unsafe’ information swarming all over the internet. Search engines with content fltering features then began to emerge, as a way to ‘protect’ the children. However, this drew backlashes from the proponents of freedom and wise internet usage, claiming the efort to flter contents from children is taking away parts of the children’s rights. This case study is solely dedicated to cover the controversy and will be concluded with where the controversy is heading. introduction The unceasing development of information technology has created a world where the internet becomes an integral part of a child life. Whether for educational purpose or sole entertainment, children nowadays have become increasingly literate in the usage of internet service. Terms such as ‘digital native’ and ‘net generation’ are being used to empha- size the importance of new technologies within the lives of young people.i When it comes to education, the internet is valuable for children both because it enhances the class environment and it introduces children, from early stages of their lives, into today’s information society.ii One of the most essential services of the internet that are used the most by children is the Internet Search Engine (ISE).
    [Show full text]
  • Motori Di Ricerca E Portali, Dei
    2 Repertorio Il testo è un repertorio di oltre 180 motori di ricerca e portali, dei escluse le piattaforme commerciali come Amazon, iTunes, ecc. motori I motori di ricerca sicuri e consigliati, quali SearX, Qwant, Startpage e DuckDuckGo, sono stati omessi, così come Google (analizzato esclusivamente per il carattere quasi monopolistico), in quanto di Repertorio dei trattati nel volume Motori di ricerca, Trovare informazioni in rete. ricer Strumenti per le ricerche sul web. Il catalogo è articolato per macro-aree tematiche relative alle ca. motori di ricerca possibili ricerche: privacy e sicurezza, tipologia di contenuti e T risultati, musica, video, foto, immagini, icone, eBook, documenti. r ovar Il capitolo primo tratta i motori di ricerca sicuri e a tutela della Trovare informazioni in rete privacy. e Il capitolo secondo riporta i motori di ricerca focalizzati sulla infor Strumenti per le ricerche sul web tipologia di contenuti e risultati. Un esempio sono CC Search, per la ricerca di contenuti multimediali non coperti da copyright, mazioni oppure FindSounds per l’individuazione di suoni in fonti aperte. I capitoli successivi hanno come oggetto le risorse per la ricerca di contenuti documentali e multimediali. Flavio Gallucci in Il capitolo terzo raccoglie le risorse per la ricerca di foto, immagini r e icone. TinEye merita attenzione per la tecnica di reverse image ete. search, ovvero la ricerca a partire dal caricamento di una foto. Strumenti Il capitolo quarto elenca strumenti e risorse per la ricerca di brani musicali, l’ascolto di musica in streaming e l’individuazione di eventi. Il capitolo quinto propone i portali dedicati alla ricerca di video.
    [Show full text]
  • Analysis of Various Kids Search Engines
    JOURNAL OF COMPUTATION IN BIOSCIENCES AND ENGINEERING Journal homepage: http://scienceq.org/Journals/JCLS.php Review Open Access Analysis of Various Kids Search Engines Deepshikha Patel1*, Prashant Kumar Singh2 1. Dr. K. N. Modi University, 2. ISC Software Pvt Ltd, *Corresponding author: Deepshikha Patel Dr. K. N. Modi University, Newai, Rajasthan, India. E-mail: [email protected] Received: December 30, 2013, Accepted: January 6, 2014, Published: January 8, 2014. ABSTRACT Web is the most commonly used resource type for finding information these days. Most search engines results are not kids oriented that’s why there are several search engines available in the market to fulfill the need of kids. In this paper we will analyze various search engines on different points like design, interactivity, ease of access, technology used, graphics etc. Keywords: Search Engines; Web Search Engines; Meta Search Engines; Searching; Kids, Kids Search. INTRODUCTION Kids are active information seeker these days. The age Boolify of surfing the web is decreasing day by day. Kids use internet Website: http://www.boolify.com/ for their school project work, playing games, watching cartoons This is based on Google’s customized search. Boolify[1] etc. World Wide Web is enormous in size and it contains lots of helps children to bridge the gap by visualizing the process and information that may not be appropriate for the kids. To protect letting them interact with the concept behind the search process kids from this inappropriate information need of search engines in a hand-on way. Boolify’s primary audience is elementary specific to kids arose.
    [Show full text]
  • So Many Choices!
    LESSON PLAN Level: Grades K to 3 About the Author: Thierry Plante, Media Education Specialist, MediaSmarts Duration: 45 minutes So Many Choices! This lesson is part of USE, UNDERSTAND & CREATE: A Digital Literacy Framework for Canadian Schools: http:// mediasmarts.ca/teacher-resources/digital-literacy-framework. Overview This lesson introduces the students to the first steps in finding information on the Internet. Specifically, this lesson helps students understand the basic good practices of searching for something online: be accompanied by a trusted adult, start with a safe site and understand the use and power of using good links and keywords to find what they are looking for and to avoid bad results. Learning Outcomes Students demonstrate: knowledge of where to go to do safe searches online how to use links and keywords an understanding of the need for an adult presence when they go online Preparation and Materials Print copies of the What’s My Name Again? handout for each student and bookmark the following sites: https://kids.nationalgeographic.com/animals/ http://www.kidrex.org/ http://www.kiddle.co https://www.kidzsearch.com/ https://www.factmonster.com/ www.mediasmarts.ca 1 © 2019 MediaSmarts So Many Choices! ● Lesson Plan ● Grades K-3 Procedure Ask students: “Who here has looked for something on the Internet? Did you do it on your own or did you get help from someone like your older brother or your mom? How did you do the search?” (Depending on the age of the student, answers might include “On my Mom’s computer”, “my Dad’s phone” or “Google”.) Write the answers on the board.
    [Show full text]
  • Comparative Study of Search Engines
    “COMPARATIVE STUDY OF SEARCH ENGINES USEFUL FOR LIBRARIANS” A Dissertation Submitted to the Tilak Maharashtra Vidyapeeth, Pune For Master of Philosophy (M.Phil.) In LIBRARY AND INFORMATION SCIENCE Submitted By Mr. SUSHANT KORE Under the Guidance of Dr. N. B. DAHIBHATE Principal Technical Officer Information Division (DIRC) National Chemical Laboratory, Pune TILAK MAHARASHTRA VIDYAPETH DEPARTMENT OF LIBRARY AND INFORMATION SCIENCE PUNE - 411 037. December, 2014 DECLARATION I hereby declare that the dissertation entitled “Comparative study of search engines useful for librarians” completed by me for the degree of Master of Philosophy in library and Information Science. The entire work embodied in this thesis has been carried out by me under the guidance of Dr. N.B. Dahibhate, National Chemical Laboratory, and Digital Information Resource Center (DIRC), Pune. (Mr. Sushant Kore) Research Student (M.Phil.) Place: Pune Date: 26th December, 2014 CERTIFICATE This is to certify that the thesis entitled “Comparative study of search engines useful for librarians” which is being submitted herewith for the award of the Degree of Master of Philosophy (M.Phil.) in Library and Information Science of Tilak Maharashtra Vidyapeeth, Pune is the result of original research work completed by Mr. Sushant Kore under my supervision and guidance. To the best of my knowledge and belief the work incorporated in this thesis has not formed the basis for award of any Degree or similar title of this or any other University or examining body. (Dr. N.B. Dahibhate) Principal Technical Officer Information Division (DIRC) NCL, Pune Place: Pune Date: 26th December , 2014 ACKNOWLEDGEMENT I am very thankful to my respectable parents for their kind support in my life as well as completing my dissertation and bringing me to this stage in the educational field.
    [Show full text]
  • OSINT Handbook September 2020
    OPEN SOURCE INTELLIGENCE TOOLS AND RESOURCES HANDBOOK 2020 OPEN SOURCE INTELLIGENCE TOOLS AND RESOURCES HANDBOOK 2020 Aleksandra Bielska Noa Rebecca Kurz, Yves Baumgartner, Vytenis Benetis 2 Foreword I am delighted to share with you the 2020 edition of the OSINT Tools and Resources Handbook. Once again, the Handbook has been revised and updated to reflect the evolution of this discipline, and the many strategic, operational and technical challenges OSINT practitioners have to grapple with. Given the speed of change on the web, some might question the wisdom of pulling together such a resource. What’s wrong with the Top 10 tools, or the Top 100? There are only so many resources one can bookmark after all. Such arguments are not without merit. My fear, however, is that they are also shortsighted. I offer four reasons why. To begin, a shortlist betrays the widening spectrum of OSINT practice. Whereas OSINT was once the preserve of analysts working in national security, it now embraces a growing class of professionals in fields as diverse as journalism, cybersecurity, investment research, crisis management and human rights. A limited toolkit can never satisfy all of these constituencies. Second, a good OSINT practitioner is someone who is comfortable working with different tools, sources and collection strategies. The temptation toward narrow specialisation in OSINT is one that has to be resisted. Why? Because no research task is ever as tidy as the customer’s requirements are likely to suggest. Third, is the inevitable realisation that good tool awareness is equivalent to good source awareness. Indeed, the right tool can determine whether you harvest the right information.
    [Show full text]
  • Stay on the Path Lesson One: Searching for Treasure
    LESSON PLAN Level: Grades 5 to 6 About the Author: MediaSmarts The lesson is part of the Stay on the Path: Teaching Kids to be Safe and Ethical Online lesson series. Stay on the Path Lesson One: Searching for Treasure This lesson is part of USE, UNDERSTAND & CREATE: A Digital Literacy Framework for Canadian Schools: http:// mediasmarts.ca/teacher-resources/digital-literacy-framework. Overview This four-lesson unit on search skills and critical thinking teaches students how to target and specify their online searches to avoid unwanted results, how to judge whether a link, search result or website is legitimate or phony and how to find legitimate sources online for media works such as music, videos and movies. In this first lesson students learn how to create well-defined search strings and to use tools and techniques such as bookmarking, browser filters and search engine preferences to avoid unwanted material. Learning Outcomes Students will: learn how to avoid unwanted search results learn how to target and specify their searches learn about the basic, automated internet filters use advanced search techniques Preparation and Materials Arrange for computer and internet access for all students Read the Search Skills Teacher Backgrounder Photocopy the following handouts: Introducing Search Skills Narrowing Your Search Search String Practice Sheet Lost Internet treasure: Clues www.mediasmarts.ca 1 © 2019 MediaSmarts Stay on the Path Lesson One: Searching for Treasure ● Lesson Plan ● Grades 5-6 Procedure Broad search terms Ask students: “What kind of websites would come up if I typed only the word ‘cats’ in a search engine?” (Answers might include pages about the animal, pictures of the animal, videos of the animal, news, etc.
    [Show full text]
  • Online Searching and Learning: YUM and Other Search Tools for Children and Teachers
    Inf Retrieval J (2017) 20:524–545 DOI 10.1007/s10791-017-9310-1 SEARCH AS LEARNING Online searching and learning: YUM and other search tools for children and teachers 1 1 1 Ion Madrazo Azpiazu • Nevena Dragovic • Maria Soledad Pera • Jerry Alan Fails1 Received: 29 October 2016 / Accepted: 8 July 2017 / Published online: 21 July 2017 Ó Springer Science+Business Media, LLC 2017 Abstract Information discovery tasks using online search tools are performed on a regular basis by school-age children. However, these tools are not necessarily designed to both explicitly facilitate the retrieval of resources these young users can comprehend and aid low-literacy searchers. This is of particular concern for educational environments, as there is an inherent expectation that these tools facilitate effective learning. In this manuscript we present an initial assessment conducted over (1) children-oriented search tools based on queries generated by K-9 students, analyzing features such as readability and adequacy of retrieved results, and (2) tools used by teachers in their classrooms, analyzing their main purpose and target audience’s age range. Among the examined tools, we include YouUnderstood.Me, an enhanced search environment, which is the result of our ongoing efforts on the development of a search environment tailored to 5-15 year-olds that can foster learning through the retrieval of materials that not only satisfy the information needs of these users but also match their reading abilities. The results of these studies highlight the fact that search results presented to children have average reading levels that do not match the target audience.
    [Show full text]
  • ICS E-Safety Guide for Parents March 2020
    ICS E-safety Guide for Parents March 2020 The thoughts of what your child might come across online can be worrying. Check out our top internet safety advice to make sure going online is a positive experience for you and your child: 1. Discover the Internet together Be the one to introduce your child to the internet. For both parent and child, it is an advantage to discover the internet together. Try to find websites that are exciting and fun so that together you achieve a positive attitude to internet exploration. This could make it easier to share both positive and negative experiences in the future. 2. Agree with your child rules for Internet Try to reach an agreement with your child on the guidelines which apply to Internet use in your household. Here are some tips to get started: ● Discuss when and for how long it is acceptable for your child to use the Internet ● Agree how to treat personal information (name, address, telephone, e-mail) ● Discuss how to behave towards others when gaming, chatting, e-mailing or messaging ● Agree what type of sites and activities are OK or not OK in our family ● Follow the rules yourself! Or at least explain why the rules are different for adults. 3. Encourage your child to be careful when disclosing personal information A simple rule for younger children should be that the child should not give out their name, phone number or photo without your approval. Older children using social networking sites like Facebook should be encouraged to be selective about what personal information and photos they post to online spaces.
    [Show full text]