To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.co¬m-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
Facilitating document annotation using content and querying valueIEEEFINALYEARPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.co¬m-Visit Our Website: www.finalyearprojects.org
JPJ1421 Facilitating Document Annotation Using Content and Querying Valuechennaijp
We are good IEEE java projects development center in Chennai and Pondicherry. We guided advanced java technologies projects of cloud computing, data mining, Secure Computing, Networking, Parallel & Distributed Systems, Mobile Computing and Service Computing (Web Service).
For More Details:
http://jpinfotech.org/final-year-ieee-projects/2014-ieee-projects/java-projects/
Google indexing involves collecting data from web pages, parsing and storing it in Google's index. The index optimizes search speed and performance by allowing Google to quickly find relevant documents for queries without scanning every page. Major factors in designing a search engine index include how data enters the index, how the index is stored and maintained, indexing speed, and fault tolerance.
Similarity Check is a similarity screening service that checks submitted manuscripts against over 59 million publications from Crossref members, 105 million publications from other partners, and 60 billion web pages to generate a report for editors. Between October 2016 to October 2017, over 4.7 million manuscripts were screened using the iThenticate software. For publishers to use the service, they must register content and assign DOIs so it can be indexed in the Turnitin database. As-crawled URLs in DOI metadata are used by Turnitin's crawler to index content. Similarity reports help publishers look for issues like plagiarism, self-plagiarism, unattributed use of others' work, or misrepresentation. Publishers invest significant
Automatic Metadata Generation Charles DuncanJISC CETIS
Slides by Charles Duncan summarising the findings of the automatic metadata generation use cases project, see http://www.intrallect.com/wiki/index.php/AMG-UC
This document discusses Crossref's funding data repository, which standardizes funder names to allow for large-scale analysis of funding information from publications. It provides instructions for publishers to deposit funding metadata through regular metadata deposits or bulk uploads. Accurately depositing full funder names and grant numbers is important so funders can locate published outcomes. Crossref's database is becoming a central source of standardized funding metadata relied on by many organizations.
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
Facilitating document annotation using content and querying valueIEEEFINALYEARPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.co¬m-Visit Our Website: www.finalyearprojects.org
JPJ1421 Facilitating Document Annotation Using Content and Querying Valuechennaijp
We are good IEEE java projects development center in Chennai and Pondicherry. We guided advanced java technologies projects of cloud computing, data mining, Secure Computing, Networking, Parallel & Distributed Systems, Mobile Computing and Service Computing (Web Service).
For More Details:
http://jpinfotech.org/final-year-ieee-projects/2014-ieee-projects/java-projects/
Google indexing involves collecting data from web pages, parsing and storing it in Google's index. The index optimizes search speed and performance by allowing Google to quickly find relevant documents for queries without scanning every page. Major factors in designing a search engine index include how data enters the index, how the index is stored and maintained, indexing speed, and fault tolerance.
Similarity Check is a similarity screening service that checks submitted manuscripts against over 59 million publications from Crossref members, 105 million publications from other partners, and 60 billion web pages to generate a report for editors. Between October 2016 to October 2017, over 4.7 million manuscripts were screened using the iThenticate software. For publishers to use the service, they must register content and assign DOIs so it can be indexed in the Turnitin database. As-crawled URLs in DOI metadata are used by Turnitin's crawler to index content. Similarity reports help publishers look for issues like plagiarism, self-plagiarism, unattributed use of others' work, or misrepresentation. Publishers invest significant
Automatic Metadata Generation Charles DuncanJISC CETIS
Slides by Charles Duncan summarising the findings of the automatic metadata generation use cases project, see http://www.intrallect.com/wiki/index.php/AMG-UC
This document discusses Crossref's funding data repository, which standardizes funder names to allow for large-scale analysis of funding information from publications. It provides instructions for publishers to deposit funding metadata through regular metadata deposits or bulk uploads. Accurately depositing full funder names and grant numbers is important so funders can locate published outcomes. Crossref's database is becoming a central source of standardized funding metadata relied on by many organizations.
Information on how to deposit and link your references with Crossref and participate in our Cited-by service. Presented at Crossref LIVE Yogyakarta, November 2017.
1) The document discusses various services for open access literature including institutional archives, metadata harvesting through Celestial, and citation analysis services like Citebase.
2) It describes how Citebase extracts references from texts and stores them in a structured database to enable citation linking and navigation between cited and citing articles.
3) Early download frequency data from arXiv.org is shown to correlate with longer-term citation frequency, indicating web impact may predict future citation impact.
Crossref provides metadata for publishers that includes titles, author names, ISSNs/ISBNs, abstracts, references, funding information, license information, full-text URIs, updates/corrections, ORCID IDs, and peer review reports. People use Crossref metadata for search/discovery, funding tracking, author profiling tools, and collaborative writing tools. National libraries also use it for tracking open access publishing costs and negotiations with publishers. Crossref metadata helps make research more findable, citable, linked, assessable, and reusable.
The document discusses how search engines work by describing their main components and processes. It explains that search engines crawl websites to index their content, then use that index to match users' search queries and return relevant results. The document outlines the key steps search engines go through, including crawling, indexing, processing searches, retrieving matches, ranking results by relevance, and displaying them to users. It also notes some of the challenges of making search engines return high-quality results.
The document discusses federated search engines, which allow simultaneous searching of multiple distributed information sources from a single search interface. Federated search engines provide access to the "deep web" that common search engines cannot index. They work by submitting user queries to various deep web resources and aggregating the results. The document compares features of federated search engines to normal search engines. It also outlines criteria for selecting the best federated search engine, and provides examples like MetaLib and WebFeat.
This document discusses data citation and how to implement it for publishers and data repositories. It covers how publishers can include data citations in their Crossref metadata and how repositories can link datasets to publications. It also introduces the Crossref Event Data service, which captures these data citations and other relationships between DOIs and makes them openly available via APIs. This allows data citations to be more widely discovered and adopted.
The document discusses web crawlers, which are programs that download web pages to help search engines index websites. It explains that crawlers use strategies like breadth-first search and depth-first search to systematically crawl the web. The architecture of crawlers includes components like the URL frontier, DNS lookup, and parsing pages to extract links. Crawling policies determine which pages to download and when to revisit pages. Distributed crawling improves efficiency by using multiple coordinated crawlers.
The document discusses Azure Data Catalog, which allows users to register and discover data sources in an enterprise. It notes current challenges around data awareness, location, documentation and security that Data Catalog addresses. The presentation covers the process of registering and enriching data sources with annotations in Data Catalog. Benefits include exploring, discovering and understanding data. Pricing and a demo of the Data Catalog are also mentioned.
We discuss revise scheduling with streaming files warehouses, which blend the features of traditional files warehouses and also data supply systems. In our setting, external sources push append-only files streams into your warehouse with many inter introduction times. While classic data warehouses are normally refreshed during downtimes, streaming warehouses usually are updated while new files arrive. We design the streaming warehouse revise problem as a scheduling trouble, where jobs correspond to processes which load brand-new data in to tables, and whoever objective is usually to minimize files staleness with time. We next propose the scheduling framework that grips the troubles encountered with a stream manufacturing facility: view hierarchies and also priorities, files consistency, lack of ability to pre-empt changes, heterogeneity connected with update jobs brought on by different inter introduction times and also data quantities among various sources, and also transient clog. A story feature in our framework will be that arranging decisions tend not to depend with properties connected with update jobs such as deadlines, but instead on the effects of revise jobs with data staleness.
This document provides an overview of new metadata developments at Crossref, including:
1) The ability to register preprints and link them to any eventual peer-reviewed articles through metadata.
2) The launch of a new content type for peer review metadata, allowing the full history of a publication's peer review to be recorded and made transparent.
3) Upcoming developments like the ability to register grant IDs and conference IDs through Crossref to provide more context and prevent issues like fake conferences.
New Metadata Developments - Crossref LIVE South AfricaCrossref
Chuck Koscher presents the new metadata developments at Crossref including posted content, peer reviews and relationships. Presented at Crossref LIVE local events in Pretoria and Cape Town, 17th and 19th April 2018.
Azure data catalog your data your way eugene polonichko dataconf 21 04 18Olga Zinkevych
Topic of presentation: Azure Data Catalog: your data, your way
The main points of the presentation:It’s a fully-managed service that lets you—from analyst to data scientist to data developer—register, enrich, discover, understand, and consume data sources
http://dataconf.com.ua/speaker-page/eugene-polonichko.php
https://www.youtube.com/watch?v=wceGzcQcPOo&list=PL5_LBM8-5sLjbRFUtXaUpg84gtJtyc4Pu&t=0s&index=4
Database security have been capturing more and more attention in recent years, even though most of the security issues surrounding the databases existed since the first day commercial database systems were introduced in the market.
Federated Search: The Good, The Bad And The Uglydorishelfer
Presented at the SLA 2007 Annual Conference in Denver, CO to the Science and Technology Division (Sci-Tech) on a program entitled: "Federated Searching: The Good, The Bad and the Ugly." Based on an article in Searcher and with additional contributions from Kathy Dabbour and Lynn Lampert on user and librarian assessment of Federated Searching.
The document appears to be advertising IEEE final year projects from Richbrain Technologies for students in various engineering disciplines such as computer science, IT, electronics, and electrical engineering. It provides contact information and lists several potential project titles in areas like cloud computing, data mining, parallel distribution, and mobile computing that students can select for their final year projects.
2013 2014 ieee finalyear me mtech java projects richbraintechnologiesIEEEFINALYEARPROJECTS
The document appears to be advertising IEEE final year projects from Richbrain Technologies for students in various engineering disciplines such as computer science, IT, electronics, and electrical engineering. It provides contact information and lists several potential project titles in areas like cloud computing, data mining, parallel distribution, and mobile computing that students can select for their final year projects.
This document provides contact information for Richbrain Technologies and lists IEEE final year project titles in various areas including mobile computing, cloud computing, data mining, and more. It contains over 40 project titles in each area along with contact details for the company that provides these projects.
Information on how to deposit and link your references with Crossref and participate in our Cited-by service. Presented at Crossref LIVE Yogyakarta, November 2017.
1) The document discusses various services for open access literature including institutional archives, metadata harvesting through Celestial, and citation analysis services like Citebase.
2) It describes how Citebase extracts references from texts and stores them in a structured database to enable citation linking and navigation between cited and citing articles.
3) Early download frequency data from arXiv.org is shown to correlate with longer-term citation frequency, indicating web impact may predict future citation impact.
Crossref provides metadata for publishers that includes titles, author names, ISSNs/ISBNs, abstracts, references, funding information, license information, full-text URIs, updates/corrections, ORCID IDs, and peer review reports. People use Crossref metadata for search/discovery, funding tracking, author profiling tools, and collaborative writing tools. National libraries also use it for tracking open access publishing costs and negotiations with publishers. Crossref metadata helps make research more findable, citable, linked, assessable, and reusable.
The document discusses how search engines work by describing their main components and processes. It explains that search engines crawl websites to index their content, then use that index to match users' search queries and return relevant results. The document outlines the key steps search engines go through, including crawling, indexing, processing searches, retrieving matches, ranking results by relevance, and displaying them to users. It also notes some of the challenges of making search engines return high-quality results.
The document discusses federated search engines, which allow simultaneous searching of multiple distributed information sources from a single search interface. Federated search engines provide access to the "deep web" that common search engines cannot index. They work by submitting user queries to various deep web resources and aggregating the results. The document compares features of federated search engines to normal search engines. It also outlines criteria for selecting the best federated search engine, and provides examples like MetaLib and WebFeat.
This document discusses data citation and how to implement it for publishers and data repositories. It covers how publishers can include data citations in their Crossref metadata and how repositories can link datasets to publications. It also introduces the Crossref Event Data service, which captures these data citations and other relationships between DOIs and makes them openly available via APIs. This allows data citations to be more widely discovered and adopted.
The document discusses web crawlers, which are programs that download web pages to help search engines index websites. It explains that crawlers use strategies like breadth-first search and depth-first search to systematically crawl the web. The architecture of crawlers includes components like the URL frontier, DNS lookup, and parsing pages to extract links. Crawling policies determine which pages to download and when to revisit pages. Distributed crawling improves efficiency by using multiple coordinated crawlers.
The document discusses Azure Data Catalog, which allows users to register and discover data sources in an enterprise. It notes current challenges around data awareness, location, documentation and security that Data Catalog addresses. The presentation covers the process of registering and enriching data sources with annotations in Data Catalog. Benefits include exploring, discovering and understanding data. Pricing and a demo of the Data Catalog are also mentioned.
We discuss revise scheduling with streaming files warehouses, which blend the features of traditional files warehouses and also data supply systems. In our setting, external sources push append-only files streams into your warehouse with many inter introduction times. While classic data warehouses are normally refreshed during downtimes, streaming warehouses usually are updated while new files arrive. We design the streaming warehouse revise problem as a scheduling trouble, where jobs correspond to processes which load brand-new data in to tables, and whoever objective is usually to minimize files staleness with time. We next propose the scheduling framework that grips the troubles encountered with a stream manufacturing facility: view hierarchies and also priorities, files consistency, lack of ability to pre-empt changes, heterogeneity connected with update jobs brought on by different inter introduction times and also data quantities among various sources, and also transient clog. A story feature in our framework will be that arranging decisions tend not to depend with properties connected with update jobs such as deadlines, but instead on the effects of revise jobs with data staleness.
This document provides an overview of new metadata developments at Crossref, including:
1) The ability to register preprints and link them to any eventual peer-reviewed articles through metadata.
2) The launch of a new content type for peer review metadata, allowing the full history of a publication's peer review to be recorded and made transparent.
3) Upcoming developments like the ability to register grant IDs and conference IDs through Crossref to provide more context and prevent issues like fake conferences.
New Metadata Developments - Crossref LIVE South AfricaCrossref
Chuck Koscher presents the new metadata developments at Crossref including posted content, peer reviews and relationships. Presented at Crossref LIVE local events in Pretoria and Cape Town, 17th and 19th April 2018.
Azure data catalog your data your way eugene polonichko dataconf 21 04 18Olga Zinkevych
Topic of presentation: Azure Data Catalog: your data, your way
The main points of the presentation:It’s a fully-managed service that lets you—from analyst to data scientist to data developer—register, enrich, discover, understand, and consume data sources
http://dataconf.com.ua/speaker-page/eugene-polonichko.php
https://www.youtube.com/watch?v=wceGzcQcPOo&list=PL5_LBM8-5sLjbRFUtXaUpg84gtJtyc4Pu&t=0s&index=4
Database security have been capturing more and more attention in recent years, even though most of the security issues surrounding the databases existed since the first day commercial database systems were introduced in the market.
Federated Search: The Good, The Bad And The Uglydorishelfer
Presented at the SLA 2007 Annual Conference in Denver, CO to the Science and Technology Division (Sci-Tech) on a program entitled: "Federated Searching: The Good, The Bad and the Ugly." Based on an article in Searcher and with additional contributions from Kathy Dabbour and Lynn Lampert on user and librarian assessment of Federated Searching.
The document appears to be advertising IEEE final year projects from Richbrain Technologies for students in various engineering disciplines such as computer science, IT, electronics, and electrical engineering. It provides contact information and lists several potential project titles in areas like cloud computing, data mining, parallel distribution, and mobile computing that students can select for their final year projects.
2013 2014 ieee finalyear me mtech java projects richbraintechnologiesIEEEFINALYEARPROJECTS
The document appears to be advertising IEEE final year projects from Richbrain Technologies for students in various engineering disciplines such as computer science, IT, electronics, and electrical engineering. It provides contact information and lists several potential project titles in areas like cloud computing, data mining, parallel distribution, and mobile computing that students can select for their final year projects.
This document provides contact information for Richbrain Technologies and lists IEEE final year project titles in various areas including mobile computing, cloud computing, data mining, and more. It contains over 40 project titles in each area along with contact details for the company that provides these projects.
Pack prediction based cloud bandwidth and cost reduction systemIEEEFINALYEARPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.co¬m-Visit Our Website: www.finalyearprojects.org
Enforcing secure and privacy preserving information brokering in distributed ...IEEEFINALYEARPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.co¬m-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.co¬m-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.co¬m-Visit Our Website: www.finalyearprojects.org
This paper describes a new approach to machine learning that uses crowdsourcing to develop predictive models of behavioral outcomes. Users on a website generate questions to collect data on predictors of an outcome like energy usage or BMI. They also answer questions to provide values for potential predictors. Models are built using this user-generated data to predict individual outcomes. Two experiments successfully built models predicting monthly energy usage and BMI based on questions crowdsourced by users. This demonstrates that non-experts can collectively identify predictive features and provide data to build models of behavioral outcomes through an interactive online process.
Efficient rekeying framework for secure multicast with diverse subscription-p...IEEEFINALYEARPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.co¬m-Visit Our Website: www.finalyearprojects.org
The document proposes a personalized mobile search engine called PMSE that captures user preferences through clickthrough data mining and classifies concepts into content and location categories. PMSE uses an ontology-based user profile to personalize search rankings based on the user's current location provided by GPS. It introduces four entropies to balance weights between content and location facets for query results. The client collects local clickthrough data for privacy while heavy tasks are done on the PMSE server. Two privacy parameters restrict profile information exposed to the server. The system was prototyped on Android and experimental results showed improved precision over baseline methods.
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.co¬m-Visit Our Website: www.finalyearprojects.org
Secure and efficient data transmission for cluster based wireless sensor netw...IEEEFINALYEARPROJECTS
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Annotation Approach for Document with Recommendation ijmpict
An enormous number of organizations generate and share textual descriptions of their products, facilities, and activities. Such collections of textual data comprise a significant amount of controlled information, which residues buried in the unstructured text. Whereas information extraction systems simplify the extraction of structured associations, they are frequently expensive and incorrect, particularly when working on top of text that does not comprise any examples of the targeted structured data. Projected an alternative methodology that simplifies the structured metadata generation by recognizing documents that are possible to contain information of awareness and this data will be beneficial for querying the database. Moreover, we intend algorithms to extract attribute-value pairs, and similarly devise new mechanisms to map such pairs to manually created schemes. We apply clustering technique to the item content information to complement the user rating information, which improves the correctness of collaborative similarity, and solves the cold start problem.
USING GOOGLE’S KEYWORD RELATION IN MULTIDOMAIN DOCUMENT CLASSIFICATIONIJDKP
The document describes a new method for multi-domain document classification using keyword sequences extracted from documents. It introduces the Word AdHoc Network (WANET) system which uses Google's Keyword Relation and a new similarity measurement called Google Purity to classify documents into domains based on their extracted 4-word keyword sequences, without requiring pre-established keyword repositories. Experimental results showed the classification was accurate and efficient, allowing cross-domain classification and management of knowledge from different sources.
A whitepaper from qubole about the Tips on how to choose the best SQL Engine for your use case and data workloads
https://www.qubole.com/resources/white-papers/enabling-sql-access-to-data-lakes
This chapter discusses database basics, anatomy, operations, and applications. It defines a database as a set of logically related files organized to minimize data redundancy and facilitate access by applications. Key points include:
- Databases store large amounts of information easily and allow flexible retrieval and organization of data.
- A database contains files which contain records made of fields. Fields have defined data types like text or numeric.
- Common database operations are browsing, querying, sorting, and generating reports, labels, and letters.
- Specialized database programs exist for contact managers, calendars, maps, and notes. Real-time databases now replace batch processing for immediate user interaction.
1. The paper proposes techniques to extract hidden databases when a user query returns many valid tuples but only some are displayed, with the others hidden.
2. It focuses on interfaces called "TOP-k-COUNT" interfaces that display some tuples and provide the count of other matching tuples.
3. The COUNT-DECISION-TREE algorithm samples the hidden database using a decision tree to generalize the attribute order, allowing different attributes at each level.
professional fuzzy type-ahead rummage around in xml type-ahead search techni...Kumar Goud
Abstract – It is a research venture on the new information-access standard called type-ahead search, in which systems discover responds to a keyword query on-the-fly as users type in the uncertainty. In this paper we learn how to support fuzzy type-ahead search in XML. Underneath fuzzy search is important when users have limited knowledge about the exact representation of the entities they are looking for, such as people records in an online directory. We have developed and deployed several such systems, some of which have been used by many people on a daily basis. The systems received overwhelmingly positive feedbacks from users due to their friendly interfaces with the fuzzy-search feature. We describe the design and implementation of the systems, and demonstrate several such systems. We show that our efficient techniques can indeed allow this search paradigm to scale on large amounts of data.
Index Terms - type-ahead, large data set, server side, online directory, search technique.
This document provides an overview of fundamentals of database design. It discusses what a database is, the difference between data and information, and the purpose of database systems. It also covers database definitions and fundamental building blocks like tables and records. Additionally, the document discusses selecting an appropriate database system, database development steps, and considerations for quality control and data entry.
The document provides an overview of fundamentals of database design including definitions of key concepts like data, information, and databases. It discusses the purpose of databases and database management systems. It also covers topics like selecting a database system, database development best practices, and data entry considerations.
This document discusses strategies for applying metadata to content in SharePoint. It covers manual tagging by end users, automatic tagging using SharePoint's built-in capabilities, and using third party tools that employ rules-based or semantic-based tagging. Semantic tagging uses natural language processing and machine learning to understand meanings and apply tags without predefined taxonomies or rules. The document also describes a specific semantic tagging tool called Termset that provides entity extraction, sentiment analysis, summarization and more.
This document provides an overview of fundamentals of database design. It discusses what a database is, the difference between data and information, why databases are needed, how to select a database system, basic database definitions and building blocks, quality control considerations, and data entry methods. The overall purpose of a database management system is to transform data into information, information into knowledge, and knowledge into action.
This document provides an overview of fundamentals of database design. It discusses what a database is, the difference between data and information, why databases are needed, how to select a database system, basic database definitions and building blocks, quality control considerations, and data entry methods. The overall purpose of a database management system is to transform data into information, information into knowledge, and knowledge into action.
The document describes an experiment comparing three big data analysis platforms: Apache Hive, Apache Spark, and R. Seven identical analyses of clickstream data were performed on each platform, and the time taken to complete each operation was recorded. The results showed that Spark was faster for queries involving transformations of big data, while R was faster for operations involving actions on big data. The document provides details on the hardware, software, data, and specific analytical tasks used in the experiment.
A Review of Data Access Optimization Techniques in a Distributed Database Man...Editor IJCATR
In today's computing world, accessing and managing data has become one of the most significant elements. Applications as
varied as weather satellite feedback to military operation details employ huge databases that store graphics images, texts and other
forms of data. The main concern in maintaining this information is to access them in an efficient manner. Database optimization
techniques have been derived to address this issue that may otherwise limit the performance of a database to an extent of vulnerability.
We therefore discuss the aspects of performance optimization related to data access in distributed databases. We further looked at the
effect of these optimization techniques
A Review of Data Access Optimization Techniques in a Distributed Database Man...Editor IJCATR
In today's computing world, accessing and managing data has become one of the most significant elements. Applications as
varied as weather satellite feedback to military operation details employ huge databases that store graphics images, texts and other
forms of data. The main concern in maintaining this information is to access them in an efficient manner. Database optimization
techniques have been derived to address this issue that may otherwise limit the performance of a database to an extent of vulnerability.
We therefore discuss the aspects of performance optimization related to data access in distributed databases. We further looked at the
effect of these optimization techniques.
Methodology for Optimizing Storage on Cloud Using Authorized De-Duplication –...IRJET Journal
This document summarizes a research paper that proposes a methodology for optimizing storage on the cloud using authorized de-duplication. It discusses how de-duplication works to eliminate duplicate data and optimize storage. The key steps are chunking files into blocks, applying secure hash algorithms like SHA-512 to generate unique hashes for each block, and comparing hashes to reference duplicate blocks instead of storing multiple copies. It also discusses using cryptographic techniques like ciphertext-policy attribute-based encryption for authentication and security on public clouds. The proposed approach aims to optimize storage while providing authorized de-duplication functionality.
A database management system (DBMS) is a software system that is used to create and manage databases. It allows users to define, create, maintain and control access to the database. There are four main types of DBMS: hierarchical, network, relational and object-oriented. A DBMS provides advantages like improved data sharing, security and integration. It also enables better access to data and decision making. However, DBMS also have disadvantages such as increased costs, management complexity and the need to constantly maintain and upgrade the system.
1. Database management systems (DBMS) allow users to define, create, query, update, and administer databases.
2. A DBMS interacts with users, applications, and the database itself to capture and analyze data stored in the database.
3. Well-known DBMS are tools like MySQL, Oracle, SQL Server, and PostgreSQL. They allow defining, creating, querying, updating and managing databases.
Odam an optimized distributed association rule mining algorithm (synopsis)Mumbai Academisc
This document proposes ODAM, an optimized distributed association rule mining algorithm. It aims to discover rules based on higher-order associations between items in distributed textual documents that are neither vertically nor horizontally distributed, but rather a hybrid of the two. Modern organizations have geographically distributed data stored locally at each site, making centralized data mining infeasible due to high communication costs. Distributed data mining emerged to address this challenge. ODAM reduces communication costs compared to previous distributed ARM algorithms by mining patterns across distributed databases without requiring data consolidation.
I was invited to speak at OMCap Berlin 2014 about the close relationship between search engines and user experience with prescriptive guidance to gain higher rankings and more conversions.
Study on potential capabilities of a nodb systemijitjournal
There is a need of optimal data to query processing technique to handle the increasing database size,
complexity, diversity of use. With the introduction of commercial website, social network, expectations are
that the high scalability, more flexible database will replace the RDBMS. Complex application and Big
Table require highly optimized queries. Users are facing the increasing bottlenecks in their data analysis. A
growing part of the database community recognizes the need for significant and fundamental changes to
database design. A new philosophy for creating database systems called noDB aims at minimizing the datato-
query time, most prominently by removing the need to load data before launching queries. That will
process queries without any data preparation or loading steps. There may not need to store data. User can
pipe raw data from websites, DBs, excel sheets into two promise sample inputs without storing anything.
This study is based on PostgreSQL systems. A series of the baseline experiment are executed to evaluate the
Performance of this system as per -a. Data loading cost, b-Query processing timing, c-Avoidance of
Collision and Deadlock, d-Enabling the Big data storage and e-Optimize query processing etc. The study
found significant possible capabilities of noDB system over the traditional database management system.
Similar to Facilitating document annotation using content and querying value (20)
Scalable face image retrieval using attribute enhanced sparse codewordsIEEEFINALYEARPROJECTS
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Scalable face image retrieval using attribute enhanced sparse codewordsIEEEFINALYEARPROJECTS
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Reversible watermarking based on invariant image classification and dynamic h...IEEEFINALYEARPROJECTS
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To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.co¬m-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.co¬m-Visit Our Website: www.finalyearprojects.org
Noise reduction based on partial reference, dual-tree complex wavelet transfo...IEEEFINALYEARPROJECTS
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Local directional number pattern for face analysis face and expression recogn...IEEEFINALYEARPROJECTS
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An access point based fec mechanism for video transmission over wireless la nsIEEEFINALYEARPROJECTS
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Spoc a secure and privacy preserving opportunistic computing framework for mo...IEEEFINALYEARPROJECTS
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Privacy preserving back propagation neural network learning over arbitrarily ...IEEEFINALYEARPROJECTS
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To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.co¬m-Visit Our Website: www.finalyearprojects.org
Geo community-based broadcasting for data dissemination in mobile social netw...IEEEFINALYEARPROJECTS
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Enabling data dynamic and indirect mutual trust for cloud computing storage s...IEEEFINALYEARPROJECTS
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Dynamic resource allocation using virtual machines for cloud computing enviro...IEEEFINALYEARPROJECTS
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A secure protocol for spontaneous wireless ad hoc networks creationIEEEFINALYEARPROJECTS
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Utility privacy tradeoff in databases an information-theoretic approachIEEEFINALYEARPROJECTS
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Ocean lotus Threat actors project by John Sitima 2024 (1).pptxSitimaJohn
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Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
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Interested in deploying an integration with Salesforce for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
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https://www.wask.co/ebooks/digital-marketing-trends-in-2024
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Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
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Facilitating document annotation using content and querying value
1. Facilitating Document Annotation Using Content And Querying
Value
Abstract:
A large number of organizations today generate and share textual descriptions of
their products, services, and actions .Such collections of textual data contain
significant amount of structured information, which remains buried in the
unstructured text. While information extraction algorithms facilitate the extraction
of structured relations, they are often expensive and inaccurate, especially when
operating on top of text that does not contain any instances of the targeted
structured information. We present a novel alternative approach that facilitates
the generation of the structured metadata by identifying documents that are likely
to contain information of interest and this information is going to be subsequently
useful for querying the database. Our approach relies on the idea that humans are
more likely to add the necessary metadata during creation time, if prompted by
the interface; or that it is much easier for humans (and/or algorithms) to identify
the metadata when such information actually exists in the document, instead of
naively prompting users to fill in forms with information that is not available in the
document. As a major contribution of this paper, we present algorithms that
identify structured attributes that are likely to appear within the document ,by
jointly utilizing the content of the text and the query workload. Our experimental
evaluation shows that our approach generates superior results compared to
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2. approaches that rely only on the textual content or only on the query workload, to
identify attributes of interest.
Architecture:
EXISTING SYSTEM:
Many systems, though, do not even have the basic “attribute-value” annotation
that would make a “pay-as-you-go” querying feasible. Existing work on query
forms can beleveraged in creating the CADS adaptive query forms. They propose
an algorithm to extract a query form that represents most of the queries in the
database using the ”querability” of the columns, while they extend their work
discussing forms customization. Some people use the schema information to auto-
complete attribute or value names in query forms. In keyword queries are used to
select the most appropriate query forms.
3. PROPOSED SYSTEM:
In this paper, we propose CADS (Collaborative Adaptive Data Sharing platform),
which is an “annotate-as-you-create” infrastructure that facilitates fielded data
annotation .A key contribution of our system is the direct use of the query
workload to direct the annotation process, in addition to examining the content of
the document. In other words, we are trying to prioritize the annotation of
documents towards generating attribute values for attributes that are often used
by querying users.
Modules :
1. Registration
2. Login
3. Document Upload
4. Search Techniques
5. Download Document
Modules Description
Registration:
In this module an Author(Creater) or User have to register
first,then only he/she has to access the data base.
Login:
In this module,any of the above mentioned person have
to login,they should login by giving their emailid and password .
4. Document Upload:
In this
module Owner uploads an unstructured document as file(along with meta data)
into database,with the help of this metadata and its contents,the end user has to
download the file.He/She has to enter content/query for download the file.
Search Techniques:
Here we are using two techniques for searching the document
1)Content Search,2)Query Search.
Content Search:
It means that the document will be downloaded by giving the
content which is present in the corresponding document.If its present the
corresponding document will be downloaded,Otherwise it won’t.
Query Search:
It means that the document will be downloaded by using query
which has given in the base paper.If its input matches the document will get
download otherwise it won’t.
Download Document:
The User has to download the document using query/content
values which have given in the base paper.He/She enters the correct data in the
text boxes, if its correct it will download the file.Otherwise it won’t.
5. System Configuration:-
H/W System Configuration:-
Processor - Pentium –III
Speed - 1.1 GHz
RAM - 256 MB (min)
Hard Disk - 20 GB
Floppy Drive - 1.44 MB
Key Board - Standard Windows Keyboard
Mouse - Two or Three Button Mouse
Monitor - SVGA
S/W System Configuration:-
Operating System :Windows95/98/2000/XP
Application Server : Tomcat5.0/6.X
Front End : HTML, Java, Jsp
Scripts : JavaScript.
Server side Script : Java Server Pages.
Database : My sql
Database Connectivity : JDBC.
6. Conclusion:
We proposed adaptive techniques to suggest relevant at-tributes to
annotate a document, while trying to satisfy the user querying needs. Our solution
is based on a probabilistic framework that considers the evidence in the document
content and the query workload. We present two ways to combine these two
pieces of evidence, content value and Querying value: a model that considers both
components conditionally independent and a linear weighted model. Experiments
shows that using our techniques, we can suggest attributes that improve the
visibility of the documents with respect to the query workload by up to 50%. That
is, we show that using the query workload can greatly improve the annotation
process and increase the utility of shared data.