Metadata Based Search in LAN METADATA BASED SEARCH in LAN
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Health Sensor Data Management in Cloud
Special Issue - 2015 International Journal of Engineering Research & Technology (IJERT) ISSN: 2278-0181 NCRTS-2015 Conference Proceedings Health Sensor Data Management in Cloud Rashmi Sahu Department of Computer Science and Engineering BMSIT,Avallahalli,Yelahanka,Bangalore Visveswariya Technological University Abstract--Wearable sensor devices with cloud computing uses its software holds 54% of patient records in US and feature have great impact in our daily lives. This 2.5% of patient records in world wide.[9] technology provides services to acquire, consume and share personal health information. Apart from that we can be How resource wastage can be refused by using cloud connected with smart phones through which we can access technology information through sensor devices equipped with our smart phone. Now smartphones has been resulted in the new ways. It is getting embedded with sensor devices such as Suppose there are 3 Hospitals A,B,C.Each hospital cameras, microphones, accelerometers, proximity sensors, maintains their own network database server,they have GPS etc. through which we can track information and management department and softwares,maintainance significant parameter about physiology. Some of the department and softwares.They organizes their own data wearable tech devices are popular today like Jawbone Up and they maintained by their own.But there is resource and Fitbit Flex, HeartMath Inner Balance Sensor, wastage,means three different health organizations Tinke.This paper is survey in area of medical field that utilizing resources having paid and costs three times of represents why cloud technologies used in medical field and single plus waste of data space also.so why can’t we how health data managed in cloud. -
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 ................................................................................................. -
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. -
Using Context to Enhance File Search
Connections: Using Context to Enhance File Search Craig A. N. Soules, Gregory R. Ganger Carnegie Mellon University ABSTRACT Attribute-based naming allows users to classify each file Connections is a file system search tool that combines tradi- with multiple attributes [9, 12, 37]. Once in place, these at- tional content-based search with context information gath- tributes provide additional paths to each file, helping users ered from user activity. By tracing file system calls, Con- locate their files. However, it is unrealistic and inappropri- nections can identify temporal relationships between files ate to require users to proactively provide accurate and use- and use them to expand and reorder traditional content ful classifications. To make these systems viable, they must search results. Doing so improves both recall (reducing false- automatically classify the user's files, and, in fact, this re- positives) and precision (reducing false-negatives). For ex- quirement has led most systems to employ search tools over ample, Connections improves the average recall (from 13% hierarchical file systems rather than change their underlying to 22%) and precision (from 23% to 29%) on the first ten methods of organization. results. When averaged across all recall levels, Connections The most prevalent automated classification method to- improves precision from 17% to 28%. Connections provides day is content analysis: examining the contents and path- these benefits with only modest increases in average query names of files to determine attributes that describe them. time (2 seconds), indexing time (23 seconds daily), and in- Systems using attribute-based naming, such as the Seman- dex size (under 1% of the user's data set). -
Dtsearch Desktop/Dtsearch Network Manual
dtSearch Desktop dtSearch Network Version 7 Copyright 1991-2021 dtSearch Corp. www.dtsearch.com SALES 1-800-483-4637 (301) 263-0731 Fax (301) 263-0781 [email protected] TECHNICAL (301) 263-0731 [email protected] 1 Table of Contents 1. Getting Started _____________________________________________________________ 1 Quick Start 1 Installing dtSearch on a Network 7 Automatic deployment of dtSearch on a Network 8 Command-Line Options 10 Keyboard Shortcuts 11 2. Indexes __________________________________________________________________ 13 What is a Document Index? 13 Creating an Index 13 Caching Documents and Text in an Index 14 Indexing Documents 15 Noise Words 17 Scheduling Index Updates 17 3. Indexing Web Sites _________________________________________________________ 19 Using the Spider to Index Web Sites 19 Spider Options 20 Spider Passwords 21 Login Capture 21 4. Sharing Indexes on a Network _________________________________________________ 23 Creating a Shared Index 23 Sharing Option Settings 23 Index Library Manager 24 Searching Using dtSearch Web 25 5. Working with Indexes _______________________________________________________ 27 Index Manager 27 Recognizing an Existing Index 27 Deleting an Index 27 Renaming an Index 27 Compressing an Index 27 Verifying an Index 27 List Index Contents 28 Merging Indexes 28 6. Searching for Documents _____________________________________________________ 29 Using the Search Dialog Box 29 Browse Words 31 More Search Options 32 Search History 33 i Table of Contents Searching for a List of Words 33 7. -
Comparison of Indexers
Comparison of indexers Beagle, JIndex, metaTracker, Strigi Michal Pryc, Xusheng Hou Sun Microsystems Ltd., Ireland November, 2006 Updated: December, 2006 Table of Contents 1. Introduction.............................................................................................................................................3 2. Indexers...................................................................................................................................................4 3. Test environment ....................................................................................................................................5 3.1 Machine............................................................................................................................................5 3.2 CPU..................................................................................................................................................5 3.3 RAM.................................................................................................................................................5 3.4 Disk..................................................................................................................................................5 3.5 Kernel...............................................................................................................................................5 3.6 GCC..................................................................................................................................................5 -
Requirements for XML Document Database Systems Airi Salminen Frank Wm
Requirements for XML Document Database Systems Airi Salminen Frank Wm. Tompa Dept. of Computer Science and Information Systems Department of Computer Science University of Jyväskylä University of Waterloo Jyväskylä, Finland Waterloo, ON, Canada +358-14-2603031 +1-519-888-4567 ext. 4675 [email protected] [email protected] ABSTRACT On the other hand, XML will also be used in ways SGML and The shift from SGML to XML has created new demands for HTML were not, most notably as the data exchange format managing structured documents. Many XML documents will be between different applications. As was the situation with transient representations for the purpose of data exchange dynamically created HTML documents, in the new areas there is between different types of applications, but there will also be a not necessarily a need for persistent storage of XML documents. need for effective means to manage persistent XML data as a Often, however, document storage and the capability to present database. In this paper we explore requirements for an XML documents to a human reader as they are or were transmitted is database management system. The purpose of the paper is not to important to preserve the communications among different parties suggest a single type of system covering all necessary features. in the form understood and agreed to by them. Instead the purpose is to initiate discussion of the requirements Effective means for the management of persistent XML data as a arising from document collections, to offer a context in which to database are needed. We define an XML document database (or evaluate current and future solutions, and to encourage the more generally an XML database, since every XML database development of proper models and systems for XML database must manage documents) to be a collection of XML documents management. -
List of Search Engines
A blog network is a group of blogs that are connected to each other in a network. A blog network can either be a group of loosely connected blogs, or a group of blogs that are owned by the same company. The purpose of such a network is usually to promote the other blogs in the same network and therefore increase the advertising revenue generated from online advertising on the blogs.[1] List of search engines From Wikipedia, the free encyclopedia For knowing popular web search engines see, see Most popular Internet search engines. This is a list of search engines, including web search engines, selection-based search engines, metasearch engines, desktop search tools, and web portals and vertical market websites that have a search facility for online databases. Contents 1 By content/topic o 1.1 General o 1.2 P2P search engines o 1.3 Metasearch engines o 1.4 Geographically limited scope o 1.5 Semantic o 1.6 Accountancy o 1.7 Business o 1.8 Computers o 1.9 Enterprise o 1.10 Fashion o 1.11 Food/Recipes o 1.12 Genealogy o 1.13 Mobile/Handheld o 1.14 Job o 1.15 Legal o 1.16 Medical o 1.17 News o 1.18 People o 1.19 Real estate / property o 1.20 Television o 1.21 Video Games 2 By information type o 2.1 Forum o 2.2 Blog o 2.3 Multimedia o 2.4 Source code o 2.5 BitTorrent o 2.6 Email o 2.7 Maps o 2.8 Price o 2.9 Question and answer . -
XML Normal Form (XNF)
Ryan Marcotte www.cs.uregina.ca/~marcottr CS 475 (Advanced Topics in Databases) March 14, 2011 Outline Introduction to XNF and motivation for its creation Analysis of XNF’s link to BCNF Algorithm for converting a DTD to XNF Example March 14, 2011 Ryan Marcotte 2 March 14, 2011 Ryan Marcotte 3 Introduction XML is used for data storage and exchange Data is stored in a hierarchical fashion Duplicates and inconsistencies may exist in the data store March 14, 2011 Ryan Marcotte 4 Introduction Relational databases store data according to some schema XML also stores data according to some schema, such as a Document Type Definition (DTD) Obviously, some schemas are better than others A normal form is needed that reduces the amount of storage needed while ensuring consistency and eliminating redundancy March 14, 2011 Ryan Marcotte 5 Introduction XNF was proposed by Marcelo Arenas and Leonid Libkin (University of Toronto) in a 2004 paper titled “A Normal Form for XML Documents” Recognized a need for good XML data design as “a lot of data is being put on the web” “Once massive web databases are created, it is very hard to change their organization; thus, there is a risk of having large amounts of widely accessible, but at the same time poorly organized legacy data.” March 14, 2011 Ryan Marcotte 6 Introduction XNF provides a set of rules that describe well-formed DTDs Poorly-designed DTDs can be transformed into well- formed ones (through normalization – just like relational databases!) Well-formed DTDs avoid redundancies and update -
Model-Based XML to Relational Database Mapping Choices
International Journal of Recent Technology and Engineering (IJRTE) ISSN: 2277-3878, Volume-8 Issue-3S, October 2019 Model-based XML to Relational Database Mapping Choices Emyliana Song, Su-Cheng Haw, Fang-Fang Chua Type Definition file (DTD) or XML schema to define Abstract— Extensible Markup Language (XML) technology structure of XML document. For model-based mapping, is widely used for data exchange and data representation in both DTD and XML schema is not needed. online and offline mode. This structured format language able to be transformed into other formats and share information The rest of the paper is organized as follows. Existing and across platforms. XML is simple; however, it is designed to related approaches on model-based mapping schemes are accommodate changes. For this paper, a study on reviewed in section 2. Section 3 discussed the performance transformation of XML document into relational database is evaluation carried out in the experiment of selected conducted. Crucial part of this process is how to maintain the approaches. Experimental results and analysis of the hierarchy and relationships between data in the document into findings are presented in section 4. And lastly, Section 5 database. Approaches that are discussed in this paper each uses own unique way of data storing technique and database design. conclude the paper. Therefore, each algorithm is assessed with three datasets constitute of small, medium and large size XML file. The II. LITERATURE REVIEW efficiency of the algorithms is being tested on time taken for data storing and query execution process. At the end of the Throughout the years, numerous mapping schemes have evaluation, we discuss factors that affect algorithm performance been proposed to resolve issues on transforming XML to and present suggestions to improve mapping scheme for future relational database structure.