University of Mysore Guidelines and Regulations Leading to Master of Library and Information Science (Two Years- Semester Scheme Under Cbcs)
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Rpa Demystified
RPA in Action for Healthcare A Challenging Council Merger DECEMBER-JANUARY 2018 RPA DEMYSTIFIED OPEN EMAIL COPY PASTE REPEAT Print Post Approved: 100002740 Ensuring the Failure of Your Knowledge Management Efforts A records manager’s job is never done..with EzeScan! Ready To Help: 1300 EZESCAN (1300 393 722 ) www.ezescan.com.au Finance looks to a new path to digital According the new Finance Discussion Paper, “In early 2018, Finance undertook a 12-week Demonstration of Concept (the record-keeping nirvana Demonstration) to test the concept of automating records capture and categorisation via machine learning and semantic data technologies. Through the Demonstration, it was concluded that while the Government is best placed to describe its functions, industry is working towards automation and would be best placed to provide digital records management systems that would be compatible with the government developed Australian Government Records Interoperability Framework (AGRIF). One industry vendor responded, “I think this means they have decided it is all too hard and could one or more of you vendors do it for us at your cost but to our theoretical and incomplete design? “I guess it will be one of those government projects that goes on More than three years into its multi-million dollar quest to for years and years costing a fortune and then is finally cancelled revolutionise digital record-keeping practices across Federal because technology has passed it by.” government, Australia’s Department of Finance has announced There is also industry concern that the co-design approach another shift in direction and a “review” of the current (and this whole project overall) puts a disproportionately heavy moratorium on new investment in records management burden on SMEs. -
Efficient Focused Web Crawling Approach for Search Engine
Ayar Pranav et al, International Journal of Computer Science and Mobile Computing, Vol.4 Issue.5, May- 2015, pg. 545-551 Available Online at www.ijcsmc.com International Journal of Computer Science and Mobile Computing A Monthly Journal of Computer Science and Information Technology ISSN 2320–088X IJCSMC, Vol. 4, Issue. 5, May 2015, pg.545 – 551 RESEARCH ARTICLE Efficient Focused Web Crawling Approach for Search Engine 1 2 Ayar Pranav , Sandip Chauhan Computer & Science Engineering, Kalol Institute of Technology and Research Canter, Kalol, Gujarat, India 1 [email protected]; 2 [email protected] Abstract— a focused crawler traverses the web, selecting out relevant pages to a predefined topic and neglecting those out of concern. Collecting domain specific documents using focused crawlers has been considered one of most important strategies to find relevant information. While surfing the internet, it is difficult to deal with irrelevant pages and to predict which links lead to quality pages. However most focused crawler use local search algorithm to traverse the web space, but they could easily trapped within limited a sub graph of the web that surrounds the starting URLs also there is problem related to relevant pages that are miss when no links from the starting URLs. There is some relevant pages are miss. To address this problem we design a focused crawler where calculating the frequency of the topic keyword also calculate the synonyms and sub synonyms of the keyword. The weight table is constructed according to the user query. To check the similarity of web pages with respect to topic keywords and priority of extracted link is calculated. -
OSINT) Analyst Overtly Passive / Covertly Active Surveillance / Reconnaissance Observation / Exploration Eye / Spy
Open Source Intelligence (OSINT) Analyst Overtly Passive / Covertly Active Surveillance / Reconnaissance Observation / Exploration Eye / Spy PREFACE This deskside/pocket smartbook contains information to assist you, the open source intelligence analyst, in carrying out your research responsibilities in a Intelligence Oversightmanner that first of all adhere to intelligence oversight and follow the guide lines of AR 381-10, Executive Order 12333, and unit standard operating procedures (SOP). The second is to practice and implement effective operational security (OPSEC) measures during data and information collection activities online. A fine line exists between collection and acquisition, and examples will be pointed out throughout the handbook. This handout is not written specifically for the military active or passive OSINT Analyst but rather as an all-purpose guide for anyone doing research. The one big advantage for the passive OSINT Analyst is that it does not require interaction with the mark. Therefore, it poses little risk since it does not alert the target to the presence of the analyst. If a technique violates Intelligence Oversight and OPSEC, then common sense must take center stage. For those in the civilian community (law enforcement, journalists, researchers, etc.), you are bound by a different set of rules and have more latitude. One important thing to keep in mind is that when threats are mentioned the majority tend to think they are military in nature. We think of Iran, North Korea, and other countries with a military capability. That is not the case. Threats can be the lone wolf types, a disgruntled worker, someone calling in a bomb threat to a hospital, etc. -
Analysis and Evaluation of the Link and Content Based Focused Treasure-Crawler Ali Seyfi 1,2
Analysis and Evaluation of the Link and Content Based Focused Treasure-Crawler Ali Seyfi 1,2 1Department of Computer Science School of Engineering and Applied Sciences The George Washington University Washington, DC, USA. 2Centre of Software Technology and Management (SOFTAM) School of Computer Science Faculty of Information Science and Technology Universiti Kebangsaan Malaysia (UKM) Kuala Lumpur, Malaysia [email protected] Abstract— Indexing the Web is becoming a laborious task for search engines as the Web exponentially grows in size and distribution. Presently, the most effective known approach to overcome this problem is the use of focused crawlers. A focused crawler applies a proper algorithm in order to detect the pages on the Web that relate to its topic of interest. For this purpose we proposed a custom method that uses specific HTML elements of a page to predict the topical focus of all the pages that have an unvisited link within the current page. These recognized on-topic pages have to be sorted later based on their relevance to the main topic of the crawler for further actual downloads. In the Treasure-Crawler, we use a hierarchical structure called the T-Graph which is an exemplary guide to assign appropriate priority score to each unvisited link. These URLs will later be downloaded based on this priority. This paper outlines the architectural design and embodies the implementation, test results and performance evaluation of the Treasure-Crawler system. The Treasure-Crawler is evaluated in terms of information retrieval criteria such as recall and precision, both with values close to 0.5. Gaining such outcome asserts the significance of the proposed approach. -
Effective Focused Crawling Based on Content and Link Structure Analysis
(IJCSIS) International Journal of Computer Science and Information Security, Vol. 2, No. 1, June 2009 Effective Focused Crawling Based on Content and Link Structure Analysis Anshika Pal, Deepak Singh Tomar, S.C. Shrivastava Department of Computer Science & Engineering Maulana Azad National Institute of Technology Bhopal, India Emails: [email protected] , [email protected] , [email protected] Abstract — A focused crawler traverses the web selecting out dependent ontology, which in turn strengthens the metric used relevant pages to a predefined topic and neglecting those out of for prioritizing the URL queue. The Link-Structure-Based concern. While surfing the internet it is difficult to deal with method is analyzing the reference-information among the pages irrelevant pages and to predict which links lead to quality pages. to evaluate the page value. This kind of famous algorithms like In this paper, a technique of effective focused crawling is the Page Rank algorithm [5] and the HITS algorithm [6]. There implemented to improve the quality of web navigation. To check are some other experiments which measure the similarity of the similarity of web pages w.r.t. topic keywords, a similarity page contents with a specific subject using special metrics and function is used and the priorities of extracted out links are also reorder the downloaded URLs for the next crawl [7]. calculated based on meta data and resultant pages generated from focused crawler. The proposed work also uses a method for A major problem faced by the above focused crawlers is traversing the irrelevant pages that met during crawling to that it is frequently difficult to learn that some sets of off-topic improve the coverage of a specific topic. -
List Created By: Jonathan Kidder (Wizardsourcer.Com) Contact
List created by: Jonathan Kidder (WizardSourcer.com) Contact Finding Extensions: Adorito: Email Lookup for LinkedIn. Aeroleads Prospect Finder: Find Prospects and Send them to AeroLeads. AmazingHiring: Search for social media profiles across the web. This tool helps find personal contact information and so much more. Clearbit Connect: Find contact information on social media profiles. Connectifier: Search for social media profiles and contact information across the web. (Recently acquired by LinkedIn). Connectifier Social Links: Find social media profiles on individual LinkedIn profiles. ContactOut: Find anyone's email and phone number on LinkedIn. Evercontact: Is the highest-rated Contact Management App on Google Apps. Hiretual: A sourcing tool that offers contact information and so much more. Hunter: An extension that helps find corporate email addresses on LinkedIn profiles. Improver: Find contact information from social media profiles. Lead Generator: Get private emails of LinkedIn profiles and check their willingness to change a job. Leadiq.io: Browse LinkedIn Profiles, AngelList Profiles, or grab LinkedIn search results and import into Google Sheets. Lusha: Find contact information on individual LinkedIn profiles. ManyContacts: Check any email address & discover Social Profiles. MightySourcer: Helps find contact info. People.Camp: Social Media Sourcing and Application/Lead Tracking Software. People Finder: Find leads, get emails, phone numbers and other contact data. Save and share your LinkedIn connections. People Search: Find contact information and resumes on social media profiles. Prophet II: Find contact information from social media profiles. SeekOut: Find contact information from social media profiles. Sellhack: Sales Helper - Social profiles add on to gather additional info about leads. SignalHire: Find contact information on individual social media profiles. -
The Google Search Engine
University of Business and Technology in Kosovo UBT Knowledge Center Theses and Dissertations Student Work Summer 6-2010 The Google search engine Ganimete Perçuku Follow this and additional works at: https://knowledgecenter.ubt-uni.net/etd Part of the Computer Sciences Commons Faculty of Computer Sciences and Engineering The Google search engine (Bachelor Degree) Ganimete Perçuku – Hasani June, 2010 Prishtinë Faculty of Computer Sciences and Engineering Bachelor Degree Academic Year 2008 – 2009 Student: Ganimete Perçuku – Hasani The Google search engine Supervisor: Dr. Bekim Gashi 09/06/2010 This thesis is submitted in partial fulfillment of the requirements for a Bachelor Degree Abstrakt Përgjithësisht makina kërkuese Google paraqitet si sistemi i kompjuterëve të projektuar për kërkimin e informatave në ueb. Google mundohet t’i kuptojë kërkesat e njerëzve në mënyrë “njerëzore”, dhe t’iu kthej atyre përgjigjen në formën të qartë. Por, ky synim nuk është as afër ideales dhe realizimi i tij sa vjen e vështirësohet me zgjerimin eksponencial që sot po përjeton ueb-i. Google, paraqitet duke ngërthyer në vetvete shqyrtimin e pjesëve që e përbëjnë, atyre në të cilat sistemi mbështetet, dhe rrethinave tjera që i mundësojnë sistemit të funksionojë pa probleme apo të përtërihet lehtë nga ndonjë dështim eventual. Procesi i grumbullimit të të dhënave ne Google dhe paraqitja e tyre në rezultatet e kërkimit ngërthen në vete regjistrimin e të dhënave nga ueb-faqe të ndryshme dhe vendosjen e tyre në rezervuarin e sistemit, përkatësisht në bazën e të dhënave ku edhe realizohen pyetësorët që kthejnë rezultatet e radhitura në mënyrën e caktuar nga algoritmi i Google. -
Finding OGC Web Services in the Digital Earth
Finding OGC Web Services in the Digital Earth Aneta J. Florczyk1, Patrick Mau´e2, Francisco J. L´opez-Pellicer1, and Javier Nogueras-Iso1 1 Departamento de Inform´atica e Ingenier´ıa de Sistemas, Universidad de Zaragoza, Spain {florczyk,fjlopez,jnog}@unizar.es 2 Institute for Geoinformatics (ifgi), University of Muenster, Germany [email protected] Abstract. The distribution of OGC Web Catalogues (CSW) across pro- fessional communities, the expert profile of the catalogue user and also the low coverage of OGC Web Services (OWS) in standard search engines reduce the possibility of discovery and sharing geographic information. This paper presents an approach to simple spatio-temporal search of OWS retrieved from the web by a specialized crawler. The Digital Earth could benefit from this solution as it overcomes technical boundaries and solves the limitation of CSW acceptance only within professional com- munity. Keywords: OWS, discovery, open search 1 Introduction The concept of the Digital Earth envisions easy-to-use applications to support non-expert users to interact with various kinds of geographic information. Users are expected to search, load, and visualize spatial data without being challenged by the plethora of file formats and methods to access and download the data. The Open Geospatial Consortium (OGC) standards specify well-defined interfaces for spatial data services to ensure interoperability across information communities. Embedded in Spatial Data Infrastructures (SDI), OGC services are mainly (but not only) used by the public administration to publish their data on the Web. On-going initiatives such as the Global Earth Observation System of Systems (GEOSS) or the European Shared Environmental Information Space (SEIS) form an important backbone to the vision of the Digital Earth. -
Optimizing Click-Through in Online Rankings for Partially Anonymous Consumers∗
Optimizing Click-through in Online Rankings for Partially Anonymous Consumers∗ Babur De los Santosy Sergei Koulayevz November 15, 2014 First Version: December 21, 2011 Abstract Consumers incur costly search to evaluate the increasing number of product options avail- able from online retailers. Presenting the best alternatives first reduces search costs associated with a consumer finding the right product. We use rich data on consumer click-stream behavior from a major web-based hotel comparison platform to estimate a model of search and click. We propose a method of determining the hotel ordering that maximizes consumers' click-through rates (CTRs) based on partial information available to the platform at that time of the con- sumer request, its assessment of consumers' preferences, and the expected consumer type based on request parameters from the current visit. Our method has two distinct advantages. First, rankings are targeted to anonymous consumers by relating price sensitivity to request param- eters, such as the length of stay, number of guests, and day of the week of the stay. Second, we take into account consumer response to new product ordering through the use of search refinement tools, such as sorting and filtering of product options. Product ranking and search actions together shape the consideration set from which clicks are made. We find that predicted CTR under our proposed ranking are almost double those under the online platform's default ranking. Keywords: consumer search, hotel industry, popularity rankings, platform, -
Download Download
International Journal of Management & Information Systems – Fourth Quarter 2011 Volume 15, Number 4 History Of Search Engines Tom Seymour, Minot State University, USA Dean Frantsvog, Minot State University, USA Satheesh Kumar, Minot State University, USA ABSTRACT As the number of sites on the Web increased in the mid-to-late 90s, search engines started appearing to help people find information quickly. Search engines developed business models to finance their services, such as pay per click programs offered by Open Text in 1996 and then Goto.com in 1998. Goto.com later changed its name to Overture in 2001, and was purchased by Yahoo! in 2003, and now offers paid search opportunities for advertisers through Yahoo! Search Marketing. Google also began to offer advertisements on search results pages in 2000 through the Google Ad Words program. By 2007, pay-per-click programs proved to be primary money-makers for search engines. In a market dominated by Google, in 2009 Yahoo! and Microsoft announced the intention to forge an alliance. The Yahoo! & Microsoft Search Alliance eventually received approval from regulators in the US and Europe in February 2010. Search engine optimization consultants expanded their offerings to help businesses learn about and use the advertising opportunities offered by search engines, and new agencies focusing primarily upon marketing and advertising through search engines emerged. The term "Search Engine Marketing" was proposed by Danny Sullivan in 2001 to cover the spectrum of activities involved in performing SEO, managing paid listings at the search engines, submitting sites to directories, and developing online marketing strategies for businesses, organizations, and individuals. -
An Intelligent Meta Search Engine for Efficient Web Document Retrieval
IOSR Journal of Computer Engineering (IOSR-JCE) e-ISSN: 2278-0661,p-ISSN: 2278-8727, Volume 17, Issue 2, Ver. V (Mar – Apr. 2015), PP 45-54 www.iosrjournals.org An Intelligent Meta Search Engine for Efficient Web Document Retrieval 1 2 Keerthana.I.P , Aby Abahai.T 1(Dept. of CSE, Mar Athanasius College of Engineering, Kothamangalam , Kerala, India) 2(Dept. of CSE, Assistant Professor, Mar Athanasius College of Engineering, Kothamangalam, Kerala, India) Abstract: In daily use of internet, when searching information we face lots of difficulty due to the rapid growth of Information Resources. This is because of the fact that a single search engine cannot index the entire web of resources. A Meta Search Engine is a solution for this, which submits the query to many other search engines and returns summary of the results. Therefore, the search results receive are an aggregate result of multiple searches. This strategy gives our search a boarder scope than searching a single search engine, but the results are not always better. Because the Meta Search Engine must use its own algorithm to choose the best results from multiple search engines. In this paper we proposed a new Meta Search Engine to overcome these drawbacks. It uses a new page rank algorithm called modified ranking for ranking and optimizing the search results in an efficient way. It is a two phase ranking algorithm used for ordering the web pages based on their relevance and popularity. This Meta Search Engine is developed in such a way that it will produce more efficient results than traditional search engines. -
Inclusiva-Net Nuevas Dinámicas Artísticas En Modo Web 2
Inclusiva-net Nuevas dinámicas artísticas en modo web 2 Primer encuentro Inclusiva-net Dirigido por Juan Martín Prada Julio, 2007. MEDIALAB-PRADO · Madrid www.medialab-prado.es ISBN: 978-84-96102-35-4 Edita: Área de las Artes. Dirección General de Promoción y Proyectos Culturales. Madrid. 2007 © de esta edición electrónica 2007: Ayuntamiento de Madrid © Textos e imágenes: los autores ÍNDICE Prefacio Juan Martín Prada 5 La “Web 2.0” como nuevo contexto para las prácticas artísticas Juan Martín Prada 6 Isubmit, Youprofile, WeRank La deconstrucción del mito de la Web 2.0 Geert Lovink 23 Telepatía colectiva 2.0 (Teoría de las multitudes interconectadas) José Luis Brea 39 Deslices de un avatar: prestidigitación y praxis artística en Second Life Mario-Paul Martínez Fabre y Tatiana Sentamans 55 Escenarios emergentes en las prácticas sociales y artísticas con tecnologías móviles Efraín Foglia 82 El artista como generador de swarmings. Cuestionando la sociedad red Carlos Seda 93 Procesos culturales en red Perspectivas para una política cultural digital Ptqk (Maria Perez) 110 Fósiles y monstruos: comunidades y redes sociales artísticas en el Estado Español Lourdes Cilleruelo 126 Tempus Fugit Cuando arte y tecnología encuentran a la persona equivocada Raquel Herrera 138 Impacto de las tecnologías web 2.0 En la comunicación cultural Javier Celaya 149 “No List Available” Web 2.0 para rescatar a los museos libios del olvido institucional. Prototipo para el Museo Jamahiriya de Trípoli lamusediffuse 158 “Arquitecturapública”: El concurso de arquitectura