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Building a Scalable Index and a Web Search Engine for Music on the Internet Using Open Source Software
Department of Information Science and Technology Building a Scalable Index and a Web Search Engine for Music on the Internet using Open Source software André Parreira Ricardo Thesis submitted in partial fulfillment of the requirements for the degree of Master in Computer Science and Business Management Advisor: Professor Carlos Serrão, Assistant Professor, ISCTE-IUL September, 2010 Acknowledgments I should say that I feel grateful for doing a thesis linked to music, an art which I love and esteem so much. Therefore, I would like to take a moment to thank all the persons who made my accomplishment possible and hence this is also part of their deed too. To my family, first for having instigated in me the curiosity to read, to know, to think and go further. And secondly for allowing me to continue my studies, providing the environment and the financial means to make it possible. To my classmate André Guerreiro, I would like to thank the invaluable brainstorming, the patience and the help through our college years. To my friend Isabel Silva, who gave me a precious help in the final revision of this document. Everyone in ADETTI-IUL for the time and the attention they gave me. Especially the people over Caixa Mágica, because I truly value the expertise transmitted, which was useful to my thesis and I am sure will also help me during my professional course. To my teacher and MSc. advisor, Professor Carlos Serrão, for embracing my will to master in this area and for being always available to help me when I needed some advice. -
Release Notes for Fedora 15
Fedora 15 Release Notes Release Notes for Fedora 15 Edited by The Fedora Docs Team Copyright © 2011 Red Hat, Inc. and others. The text of and illustrations in this document are licensed by Red Hat under a Creative Commons Attribution–Share Alike 3.0 Unported license ("CC-BY-SA"). An explanation of CC-BY-SA is available at http://creativecommons.org/licenses/by-sa/3.0/. The original authors of this document, and Red Hat, designate the Fedora Project as the "Attribution Party" for purposes of CC-BY-SA. In accordance with CC-BY-SA, if you distribute this document or an adaptation of it, you must provide the URL for the original version. Red Hat, as the licensor of this document, waives the right to enforce, and agrees not to assert, Section 4d of CC-BY-SA to the fullest extent permitted by applicable law. Red Hat, Red Hat Enterprise Linux, the Shadowman logo, JBoss, MetaMatrix, Fedora, the Infinity Logo, and RHCE are trademarks of Red Hat, Inc., registered in the United States and other countries. For guidelines on the permitted uses of the Fedora trademarks, refer to https:// fedoraproject.org/wiki/Legal:Trademark_guidelines. Linux® is the registered trademark of Linus Torvalds in the United States and other countries. Java® is a registered trademark of Oracle and/or its affiliates. XFS® is a trademark of Silicon Graphics International Corp. or its subsidiaries in the United States and/or other countries. MySQL® is a registered trademark of MySQL AB in the United States, the European Union and other countries. All other trademarks are the property of their respective owners. -
PDF-Xchange Viewer
PDF-XChange Viewer © 2001-2011 Tracker Software Products Ltd North/South America, Australia, Asia: Tracker Software Products (Canada) Ltd., PO Box 79 Chemainus, BC V0R 1K0, Canada Sales & Admin Tel: Canada (+00) 1-250-324-1621 Fax: Canada (+00) 1-250-324-1623 European Office: 7 Beech Gardens Crawley Down., RH10 4JB Sussex, United Kingdom Sales Tel: +44 (0) 20 8555 1122 Fax: +001 250-324-1623 http://www.tracker-software.com [email protected] Support: [email protected] Support Forums: http://www.tracker-software.com/forum/ ©2001-2011 TRACKER SOFTWARE PRODUCTS II PDF-XChange Viewer v2.5x Table of Contents INTRODUCTION...................................................................................................... 7 IMPORTANT! FREE vs. PRO version ............................................................................................... 8 What Version Am I Running? ............................................................................................................................. 9 Safety Feature .................................................................................................................................................. 10 Notice! ......................................................................................................................................... 10 Files List ....................................................................................................................................... 10 Latest (available) Release Notes ................................................................................................. -
Technology Tips and Tricks for the Legal Practitioner
New Lawyer Column Technology Tips and Tricks for the Legal Practitioner By Israel F. Piedra ingly, apply text recognition, and allow you Outlook’s Rules & Alerts settings. The rel- it relatively intuitive, DocFetcher does have a to save/email the document as a PDF. Among evant “rule” option is to “defer delivery by a learning curve. Second, the software does not While computers can be exasperating at the most popular of these apps for iPhone and number of minutes.” apply its own PDF text recognition – mean- times, they can also be extraordinary tools. Android are Scanbot, Scannable, and Scan- After this rule is in place, emails you ing that PDFs must be made searchable be- With the New Hampshire Supreme Court ner Pro. One practical use for lawyers: mak- send will remain in your outbox for the speci- fore they can be indexed by the program. and Superior Court ing quick PDFs of documents from a court fi ed amount of time before disappearing into transitioning to e- fi le at the clerk’s offi ce. cyberspace. If you want to re-read or revise, Webpage Screenshot Add-ons fi ling, it is more you merely open the email from the outbox In a variety of contexts, it is becom- important than ever Microsoft Word shortcuts and re-send when it’s ready. There are some ing increasingly important to preserve in- that Bar attorneys Though they will only save you a few drawbacks and the function does take some ternet information such as Facebook pages, are profi cient with seconds at most, these two Microsoft Word getting used to. -
LIST of NOSQL DATABASES [Currently 150]
Your Ultimate Guide to the Non - Relational Universe! [the best selected nosql link Archive in the web] ...never miss a conceptual article again... News Feed covering all changes here! NoSQL DEFINITION: Next Generation Databases mostly addressing some of the points: being non-relational, distributed, open-source and horizontally scalable. The original intention has been modern web-scale databases. The movement began early 2009 and is growing rapidly. Often more characteristics apply such as: schema-free, easy replication support, simple API, eventually consistent / BASE (not ACID), a huge amount of data and more. So the misleading term "nosql" (the community now translates it mostly with "not only sql") should be seen as an alias to something like the definition above. [based on 7 sources, 14 constructive feedback emails (thanks!) and 1 disliking comment . Agree / Disagree? Tell me so! By the way: this is a strong definition and it is out there here since 2009!] LIST OF NOSQL DATABASES [currently 150] Core NoSQL Systems: [Mostly originated out of a Web 2.0 need] Wide Column Store / Column Families Hadoop / HBase API: Java / any writer, Protocol: any write call, Query Method: MapReduce Java / any exec, Replication: HDFS Replication, Written in: Java, Concurrency: ?, Misc: Links: 3 Books [1, 2, 3] Cassandra massively scalable, partitioned row store, masterless architecture, linear scale performance, no single points of failure, read/write support across multiple data centers & cloud availability zones. API / Query Method: CQL and Thrift, replication: peer-to-peer, written in: Java, Concurrency: tunable consistency, Misc: built-in data compression, MapReduce support, primary/secondary indexes, security features. -
Bitcurator and Bitcurator Access
Bringing Bits to the User: BitCurator and BitCurator Access Christopher (Cal) Lee UNC School of Information and Library Science Coalition for Networked Information (CNI) Membership Meeting December 14-15, 2015 Washington, DC The Andrew W. Mellon Foundation What are we to do with this stuff? Source: “Digital Forensics and creation of a narrative.” Da Blog: ULCC Digital Archives Blog. http://dablog.ulcc.ac.uk/2011/07/04/forensics/ Goals When Acquiring Materials Ensure integrity of materials Allow users to make sense of materials and understand their context Prevent inadvertent disclosure of sensitive data Fundamental Archival Principles Provenance • Reflect “life history” of records • Records from a common origin or source should be managed together as an aggregate unit Original Order Organize and manage records in ways that reflect their arrangement within the creation/use environment Chain of • “Succession of offices or persons who have held Custody materials from the moment they were created”1 • Ideal recordkeeping system would provide “an unblemished line of responsible custody”2 1. Pearce-Moses, Richard. A Glossary of Archival and Records Terminology. Chicago, IL: Society of American Archivists, 2005. 2. Hilary Jenkinson, A Manual of Archive Administration: Including the Problems of War Archives and Archive Making (Oxford: Clarendon Press, 1922), 11. Bit digital is different. See: Lee, Christopher A. “Digital Curation as Communication Mediation.” In Handbook of Technical Communication, edited by Alexander Mehler, Laurent Romary, -
STUDY and SURVEY of BIG DATA for INDUSTRY Surbhi Verma*, Sai Rohit
ISSN: 2277-9655 [Verma* et al., 5(11): November, 2016] Impact Factor: 4.116 IC™ Value: 3.00 CODEN: IJESS7 IJESRT INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY STUDY AND SURVEY OF BIG DATA FOR INDUSTRY Surbhi Verma*, Sai Rohit DOI: 10.5281/zenodo.166840 ABSTRACT Now-a-days we rarely observe any company or any industry who don’t have any database. Industries with huge amounts of data are finding it difficult to manage. They all are in search of some technology which can make their work easy and fast. The primary purpose of this paper is to provide an in-depth analysis of different platforms available for performing big data over local data and how they differ with each other. This paper surveys different hardware platforms available for big data and local data and assesses the advantages and drawbacks of each of these platforms. KEYWORDS: Big data, Local data, HadoopBase, Clusterpoint, Mongodb, Couchbase, Database. INTRODUCTION This is an era of Big Data. Big Data is making radical changes in traditional data analysis platforms. To perform any kind of analysis on such huge and complex data, scaling up the hardware platforms becomes imminent and choosing the right hardware/software platforms becomes very important. In this research we are showing how big data has been improvising over the local databases and other technologies. Present day, big data is making a huge turnaround in technological world and so to manage and access data there must be some kind of linking between big data and local data which is not done yet. -
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. -
Lookeen Desktop Search
Lookeen Desktop Search Find your files faster! User Benefits Save time by simultaneously searching for documents on your hard drive, in file servers and the network. Lookeen can also search Outlook archives, the Exchange Search with fast and reliable Server and Public Folders. Advanced filters and wildcard options make search more Lookeen technology powerful. With Lookeen you’ll turn ‘search’ into ‘find’. You’ll be able to manage and organize large amounts of data efficiently. Employees will save valuable time usually Find your information in record spent searching to work on more important tasks. time thanks to real-time indexing Lookeen desktop search can also Search your desktop, Outlook be integrated into Outlook The search tool for Windows files and Exchange folders 10, 8, 7 and Vista simultaneously Ctrl+Ctrl is back: instantly launch Edit and save changes to Lookeen from documents in Lookeen preview anywhere on your desktop Save and re-use favorite queries and access them with short keys View all correspondence with individuals or groups at the push of a button Create one-click summaries of email correspondences Start saving time and money immediately For Companies Features Business Edition Desktop search software compatible with Powerful search in virtual environments like Compatible with standard and virtual Windows 10, 8, 7 and Vista Citrix and VMware desktops like Citrix, VMware and Terminal Servers. Simplified roll out through exten- Optional add-in to Microsoft Outlook 2016, Simple, user friendly interface gives users a sive group directives and ADM files. 2013, 2010, 2007 or 2003 and Office 365 unified view over multiple data sources Automatic indexing of all files on the hard Clear presentation of search results drive, network, file servers, Outlook PST/OST- Enterprise Edition Full fidelity preview option archives, Public Folders and the Exchange Scans additional external indexes. -
Towards the Ontology Web Search Engine
TOWARDS THE ONTOLOGY WEB SEARCH ENGINE Olegs Verhodubs [email protected] Abstract. The project of the Ontology Web Search Engine is presented in this paper. The main purpose of this paper is to develop such a project that can be easily implemented. Ontology Web Search Engine is software to look for and index ontologies in the Web. OWL (Web Ontology Languages) ontologies are meant, and they are necessary for the functioning of the SWES (Semantic Web Expert System). SWES is an expert system that will use found ontologies from the Web, generating rules from them, and will supplement its knowledge base with these generated rules. It is expected that the SWES will serve as a universal expert system for the average user. Keywords: Ontology Web Search Engine, Search Engine, Crawler, Indexer, Semantic Web I. INTRODUCTION The technological development of the Web during the last few decades has provided us with more information than we can comprehend or manage effectively [1]. Typical uses of the Web involve seeking and making use of information, searching for and getting in touch with other people, reviewing catalogs of online stores and ordering products by filling out forms, and viewing adult material. Keyword-based search engines such as YAHOO, GOOGLE and others are the main tools for using the Web, and they provide with links to relevant pages in the Web. Despite improvements in search engine technology, the difficulties remain essentially the same [2]. Firstly, relevant pages, retrieved by search engines, are useless, if they are distributed among a large number of mildly relevant or irrelevant pages. -
An Activity Based Data Model for Desktop Querying (Extended Abstract)?
An activity based data model for desktop querying (Extended Abstract)? Sibel Adalı1 and Maria Luisa Sapino2 1 Rensselaer Polytechnic Institute, 110 8th Street, Troy, NY 12180, USA, [email protected], 2 Universit`adi Torino, Corso Svizzera, 185, I-10149 Torino, Italy [email protected] 1 Introduction With the introduction of a variety of desktop search systems by popular search engines as well as the Mac OS operating system, it is now possible to conduct keyword search across many types of documents. However, this type of search only helps the users locate a very specific piece of information that they are looking for. Furthermore, it is possible to locate this information only if the document contains some keywords and the user remembers the appropriate key- words. There are many cases where this may not be true especially for searches involving multimedia documents. However, a personal computer contains a rich set of associations that link files together. We argue that these associations can be used easily to answer more complex queries. For example, most files will have temporal and spatial information. Hence, files created at the same time or place may have relationships to each other. Similarly, files in the same directory or people addressed in the same email may be related to each other in some way. Furthermore, we can define a structure called “activities” that makes use of these associations to help user accomplish more complicated information needs. Intu- itively, we argue that a person uses a personal computer to store information relevant to various activities she or he is involved in. -
Improved Methods for Mining Software Repositories to Detect Evolutionary Couplings
IMPROVED METHODS FOR MINING SOFTWARE REPOSITORIES TO DETECT EVOLUTIONARY COUPLINGS A dissertation submitted to Kent State University in partial fulfillment of the requirements for the degree of Doctor of Philosophy by Abdulkareem Alali August, 2014 Dissertation written by Abdulkareem Alali B.S., Yarmouk University, USA, 2002 M.S., Kent State University, USA, 2008 Ph.D., Kent State University, USA, 2014 Approved by Dr. Jonathan I. Maletic Chair, Doctoral Dissertation Committee Dr. Feodor F. Dragan Members, Doctoral Dissertation Committee Dr. Hassan Peyravi Dr. Michael L. Collard Dr. Joseph Ortiz Dr. Declan Keane Accepted by Dr. Javed Khan Chair, Department of Computer Science Dr. James Blank Dean, College of Arts and Sciences ii TABLE OF CONTENTS TABLE OF CONTENTS ............................................................................................... III LIST OF FIGURES ..................................................................................................... VIII LIST OF TABLES ....................................................................................................... XIII ACKNOWLEDGEMENTS ..........................................................................................XX CHAPTER 1 INTRODUCTION ................................................................................... 22 1.1 Motivation and Problem .......................................................................................... 24 1.2 Research Overview ................................................................................................