International Conference on Intelligent Systems Design and Applications 2009

•Als PPT, PDF herunterladen•

0 gefällt mir•355 views

A Business Intelligence process to support Information Retrieval in an Ontology-based Environment

$A Business Intelligence Process to support Information Retrieval in an Ontology-Based Environment Tommaso Federici Tuscia University 01010 Viterbo, Italy [email_address] Filippo Sciarrone, Paolo Starace Open Informatica srl – BI Division Via dei Castelli Romani, 12/A 00040 Pomezia, Italy {f.sciarrone, p.starace}@openinformatica.org$

Introduction ,[object Object],[object Object],[object Object]

[object Object],[object Object],[object Object],Research Question How Business Intelligence and Information Retrieval techniques can be merged to improve the decision support process?

Summary ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

The semantic indexing process unstructured docs ontologies terms set

The overall system dm1 presentation layer structured data index CUSTOM ETL PROCESS data warehouse and datamarts Addictional integrable data dm3 dm2 semantic dictionary

Summary ,[object Object],[object Object],[object Object],[object Object]

Dynamic dimension definition ,[object Object],[object Object],The key idea is to deﬁne ad-hoc ontologies to support analysis on a semantic indexed information system, and the subsequent automatic building of multidimensional schemas.

Dynamic dimension definition dimension table bridge table fact table Unbalanced ontology tree dynamic computation concept_id description parent 1 one 2 two 1 parent subsidiary distance 1 1 0 1 2 1 concept_id other_dim_id measure 1 … … … … …

[object Object],[object Object],Dynamic dimension definition

Integration of the indexed data SELECT * FROM index JOIN op_fact_table ON index.op_fact_id = op_fact_table.id; SELECT * FROM ((index JOIN op_fact_table ON index.op_fact_id = op_fact_table.id) JOIN std_dimension_dt ON op_fact_table.column = std_dimension_dt.column); SELECT * FROM ((index JOIN op_fact_table ON index.op_fact_id = op_fact_table.id) JOIN std_dimension_dt ON op_fact_table.column = std_dimension_dt.column) JOIN ontology_dt ON index.concept = ontology_dt.concept; SELECT ontology_dt.ontology_id, std_dimension_dt.std_dimension_id, sum(op_fact_table.measure) FROM ((index JOIN op_fact_table ON index.op_fact_id = op_fact_table.id) JOIN std_dimension_dt ON op_fact_table.column = std_dimension_dt.column) JOIN ontology_dt ON index.concept = ontology_dt.concept GROUP BY std_dimension_dt.std_dimension_id, ontology_dt.ontology_id;

The Star Schema ,[object Object],[object Object],[object Object]

Conclusions and Future Works ,[object Object],[object Object],[object Object],[object Object]

Thanks to all for your attention Questions?

Weitere ähnliche Inhalte

Was ist angesagt?

Machine learning algorithms may be classified mainly into three main types. Supervised learning constructs a mathematical model from the training data, including input and output labels. The techniques of data categorization and regression are deemed supervised learning. In unsupervised learning, the system constructs a model using just the input characteristics but no output labeling. The classifiers are then trained to search the dataset for a specific pattern. Learn More:https://bit.ly/3sX9xuQ Contact Us: Website: https://www.phdassistance.com/ UK: +44 7537144372 India No:+91-9176966446 Email: info@phdassistance.com

Selecting the Right Type of Algorithm for Various Applications - Phdassistance

PhD Assistance

Data mining environment produces a large amount of data that need to be analyzed. Using traditional databases and architectures, it has become difficult to process, manage and analyze patterns. To gain knowledge about the Big Data a proper architecture should be understood. Classification is an important data mining technique with broad applications to classify the various kinds of data used in nearly every field of our life. Classification is used to classify the item according to the features of the item with respect to the predefined set of classes. This paper put a light on various classification algorithms including j48, C4.5, Naive Bayes using large dataset.

SURVEY ON CLASSIFICATION ALGORITHMS USING BIG DATASET

Editor IJMTER

Selecting the Right Type of Algorithm for Various Applications - Phdassistance

PhD Assistance

Abstract Learning Analytics by nature relies on computational information processing activities intended to extract from raw data some interesting aspects that can be used to obtain insights into the behaviors of learners, the design of learning experiences, etc. There is a large variety of computational techniques that can be employed, all with interesting properties, but it is the interpretation of their results that really forms the core of the analytics process. As a rising subject, data mining and business intelligence are playing an increasingly important role in the decision support activity of every walk of life. The Variance Rover System (VRS) mainly focused on the large data sets obtained from online web visiting and categorizing this into clusters according some similarity and the process of predicting customer behavior and selecting actions to influence that behavior to benefit the company, so as to take optimized and beneficial decisions of business expansion. Keywords: Analytics, Business intelligence, Clustering, Data Mining, Standard K-means, Optimized K-means

Variance rover system

eSAT Journals

IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology

Variance rover system web analytics tool using data

eSAT Publishing House

Data mining techniques a survey paper

eSAT Publishing House

4113ijaia09

Rajkishorepanda

Data mining: Classification and prediction

DataminingTools Inc

A large number of techniques has been developed so far to tell the diversity of machine learning. Machine learning is categorized into supervised, unsupervised and reinforcement learning .Every instance in given data-set used by Machine learning algorithms is represented same set of features .On basis of label of instances it is divided into category. In this review paper our main focus is on Supervised, unsupervised learning techniques and its performance parameters.

A Survey on Machine Learning Algorithms

AM Publications

Data Mining In Market Research

kevinlan

Regression with Microsoft Azure & Ms Excel

Dr. Abdul Ahad Abro

Algorithm and Modeling in Data Analysis Assignment

Lesa Cote

BUILDING A GENERAL CONCEPT OF ANALYTICAL SERVICES FOR ANALYSIS OF STRUCTURED DATA Abstract: In this paper, “Building a common concept of analytical services for analyzing structured data” was proposed to build an analytical service to provide forecasts, descriptive and comparative data summaries using modern Microsoft technologies. This service will allow users to pehttps://www.slideshare.net/uploadrform flexible viewing of information, receive arbitrary data slices and perform analytical operations of drill-down, convolution, pass-through distribution, the comparison in time. With the help of data mining, it is possible to detect previously unknown, non-trivial, practically useful and accessible interpretations of knowledge that are necessary for the organization's decision-making. Also, each client can interact with the service and thus monitor the displayed analytical information. In the process of work the following tasks were solved: investigated the subject area; studied materials relating to systems and technologies for their implementation; designed service architecture and applications to configure the service; selected technologies and tools for the implementation of the system; implemented the main frame of the system; modules for interaction with analysis services, data mining (a priori algorithm) and partially a module of neural networks; a report was written and a presentation of the results was prepared; The developed service will be useful to all organizations that are interested in obtaining analytical reports and other previously unknown information on their accumulated data. For example, organizations can analyze the impact of advertising, customer segmentation, search for signs of profitable customers, analyze product preferences, forecast sales volumes, and more.

BUILDING A GENERAL CONCEPT OF ANALYTICAL SERVICES FOR ANALYSIS OF STRUCTURED ...

Kiogyf

The determination of a number of items in the right number is very essential for a company, but in actual practice, it is not trivial task. There are many factors that influence them such as inventory and sales levels. If a number of the ordering goods is too slight or too much, it will effect in the fulfillment of consumer demand. One of the ways that can be used to predict a number of ordering goods is a Fuzzy Inference System (FIS) using Tsukamoto fuzzy logic method. Three variables that are used in this study, namely sales, inventory, and ordering or purchasing. The sales input variables are divided into 3 categories, namely down, constant, and rise. Then, inventory input variebles are divided into 3 categories, namely a slight, moderate and many, likewise ordering input variables also consists in 3 categories, namely less, constant, and increase. The next step is the combination of rules from all events, then performing inference and defuzzifikasi to find average centered. To prove the applied method against manual calculations are then implemented in the developed system. The results of the system calculation do not much different with the calculation results that are done by manually. This is proven by information in the table of Mean Squared Error (MSE) with error results of under 1. So, without prejudice to accuracy in the calculation, the system can be used to save time in determining the amount of the ordering goods. The proposed method can help for research object, in this case is retail company to determine a number of ordering goods.

Development of Decision Support System for Ordering Goods using Fuzzy Tsukamoto

IJECEIAES

In Industrial environments, huge amount of data is being generated which in turn collected indatabase anddata warehouses from all involved areas such as planning, process design, materials, assembly, production, quality, process control, scheduling, fault detection,shutdown, customer relation management, and so on. Data Mining has become auseful tool for knowledge acquisition for industrial process of Iron and steel making. Due to the rapid growth in Data Mining, various industries started using data mining technology to search the hidden patterns, which might further be used to the system with the new knowledge which might design new models to enhance the production quality, productivity optimum cost and maintenance etc. The continuous improvement of all steel production process regarding the avoidance of quality deficiencies and the related improvement of production yield is an essential task of steel producer. Therefore, zero defect strategy is popular today and to maintain it several quality assurancetechniques areused. The present report explains the methods of data mining and describes its application in the industrial environment and especially, in the steel industry.

A SURVEY ON DATA MINING IN STEEL INDUSTRIES

IJCSES Journal

With the development of database, the data volume stored in database increases rapidly and in the large amounts of data much important information is hidden. If the information can be extracted from the database they will create a lot of profit for the organization. The question they are asking is how to extract this value. The answer is data mining. There are many technologies available to data mining practitioners, including Artificial Neural Networks, Genetics, Fuzzy logic and Decision Trees. Many practitioners are wary of Neural Networks due to their black box nature, even though they have proven themselves in many situations. This paper is an overview of artificial neural networks and questions their position as a preferred tool by data mining practitioners.

Effective data mining for proper

IJDKP

Was ist angesagt? (20)

Selecting the Right Type of Algorithm for Various Applications - Phdassistance

SURVEY ON CLASSIFICATION ALGORITHMS USING BIG DATASET

Selecting the Right Type of Algorithm for Various Applications - Phdassistance

Variance rover system

Variance rover system web analytics tool using data

Data mining techniques a survey paper

4113ijaia09

Data mining: Classification and prediction

A Survey on Machine Learning Algorithms

Data Mining In Market Research

Regression with Microsoft Azure & Ms Excel

Algorithm and Modeling in Data Analysis Assignment

BUILDING A GENERAL CONCEPT OF ANALYTICAL SERVICES FOR ANALYSIS OF STRUCTURED ...

Development of Decision Support System for Ordering Goods using Fuzzy Tsukamoto

A SURVEY ON DATA MINING IN STEEL INDUSTRIES

Effective data mining for proper

Ähnlich wie International Conference on Intelligent Systems Design and Applications 2009

Credit card fraud detection using python machine learning

Sandeep Garg

The visualization of information contained in reports is an important aspect of human-computer interaction, for both the accuracy and the complexity of relationships between data must be preserved. A greater attention has been paid to individual report visualization through different types of standard graphs (Histograms, Pies, etc.). However, this kind of representation provides separate information items and gives no support to visualize their relationships which are extremely important for most decision processes. This paper presents a design methodology exploiting the visual language CoDe [1] based on a logic paradigm. CoDe allows to organize the visualization through the CoDe model which graphically represents relationships between information items and can be considered a conceptual map of the view. The proposed design methodology is composed of four phases: the CoDe Modelingand OLAP Operation pattern definition phases define the CoDe model and underlying metadata information, the OLAP Operation phase physically extracts data from a data warehouse and the Report Visualization phase generates the final visualization. Moreover,a case study on real data is provided. http://kaashivinfotech.com/ http://inplanttrainingchennai.com/ http://inplanttraining-in-chennai.com/ http://internshipinchennai.in/ http://inplant-training.org/ http://kernelmind.com/ http://inplanttraining-in-chennai.com/ http://inplanttrainingchennai.com/

CoDe Modeling of Graph Composition for Data Warehouse Report Visualization

KaashivInfoTech Company

Mis jaiswal-chapter-09

Amit Fogla

Inventory System

Nasir152222

One of the most emerging technologies is finance, becoming more amenable to data-driven modeling as large sets of financial data become available everywhere. So we are applying the data mining techniques in financial information system with Business Intelligence. A Business Intelligence System (BIS) can be described as an interactive, computer-based system designed to help decision-makers to solve unstructured problems. Using a combination of models, analytical techniques, and information retrieval, such systems help develop and evaluate appropriate alternatives.

The Development of Financial Information System and Business Intelligence Usi...

IJERA Editor

4Emerging Trends in Business IntelligenceITS 531.docx

blondellchancy

Machine learning with Python refers to the process of using the Python programming language and its associated libraries and tools to develop and apply machine learning algorithms. Python has become the de facto language for machine learning due to its simplicity, readability, and extensive ecosystem of libraries such as NumPy, Pandas, and Scikit-learn. Machine learning involves the study and development of algorithms that enable computers to learn from data and make predictions or decisions without explicit programming instructions. Python provides a versatile and intuitive platform for implementing various machine learning techniques, including supervised learning, unsupervised learning, and reinforcement learning. VISIT TO LEARN MORE: https://skillup.online/courses/machine-learning-with-python-a-practical-introduction/

MACHINE LEARNING WITH PYTHON PPT.pptx

SkillUp Online

H1803014347

IOSR Journals

Rapid changes in the technology lead to increased variety of data sources. These varied data sources generating data in the large volume and with extremely high speed. To accommodate and use this data in decision making systems is the big challenge. To make fullest use of the valuable data generated by different systems, target users of the analysis systems need to be increased. In general knowledge discovery process using the tools which are available requires the handsome expertise in the domain as well as in the technology. The project ITDA (Integrated Tool for Data Analysis) focuses to provide the complete platform for multidimensional data analysis to enhance the decision making process in every domain. This projects provides all the techniques required to perform multidimensional data analysis and avoids the overheads occurred by the traditional cube architecture followed by most of the analytics system. Modelling the available data in the multidimensional form is the basis and crucial step for multidimensional analysis. This work describes the multidimensional modelling aspect and its implementation using ITDA project.

A Software Infrastructure for Multidimensional Data Analysis: A Data Modellin...

IJCSIS Research Publications

The project is to ask college related queries and get the responses through a chatbot an Artificial Conversational Entity. This System is a web application which provides answer to the query of the student. Students just have to query through the bot which is used for chatting. Students can chat using any format there is no specific format the user has to follow. This system helps the student to be updated about the college activities.

CHATBOT FOR COLLEGE RELATED QUERIES | J4RV4I1008

Journal For Research

Analytics, machine e deep learning, data/event streaming - Big data streaming: abilitare la macchina del tempo - Real time event streaming e nuovi paradigmi concettuali: transazioni distribuite, consistenza eventuale, proiezioni materializzate - Real time event streaming e nuovi paradigmi architetturali: Enterprise service bus, Event store, Database delle proiezioni - Cenni di Domain Driven Design: una visione strategica della modellazione del proprio dominio di business nell'era dei Big Data

Seminario Big Data - 27/11/2017

Ordine Ingegneri Lecco

Analytics, machine e deep learning, data/event streaming Big data streaming: abilitare la macchina del tempo Real time event streaming e nuovi paradigmi concettuali: - Transazioni distribuite - Consistenza eventuale - Proiezioni materializzate Real time event streaming e nuovi paradigmi architetturali: - Enterprise service bus - Event store - Database delle proiezioni Cenni di Domain Driven Design: una visione strategica della modellazione del proprio dominio di business nell'era dei bi Data.

Seminario Big Data

Roberto Messora

Data warehouse designing process takes input from operational system of the organization. Quality of data warehousing solution depends on design of operational system. Often, operational system implementations of organizations have some limitations. Thus, we cannot proceed for data warehouse designing so easily. In this paper, we have tried to investigate operational system of the organization for identifying such limitations and determine role of operational system design in the process of data warehouse design and implementation. We have worked out to find possible methods to handle such limitations and have proposed techniques to get a quality data warehousing solution under such limitations. To make the work based on live example, National Rural Health Mission (NRHM) Project has been taken. It is a national project of health sector, managed by Indian Government across the country. The complex structure and high volume of data makes it an ideal case for data warehouse implementation.

Role of Operational System Design in Data Warehouse Implementation: Identifyi...

iosrjce

H017634452

IOSR Journals

integrating-cognitive-services-into-your-devops-strategy

Karthik Jaganathan

Integrating cognitive services in to your devops strategy

Aspire Systems

Data science technology overview

Soojung Hong

Anwar kamal .pdf.pptx

Luminous8

Why Big Data Automation is Important for Your Business.pdf

Data Science Council of America

Why Big Data Automation is Important for Your Business.pdf

Data Science Council of America

Ähnlich wie International Conference on Intelligent Systems Design and Applications 2009 (20)

Credit card fraud detection using python machine learning

CoDe Modeling of Graph Composition for Data Warehouse Report Visualization

Mis jaiswal-chapter-09

Inventory System

The Development of Financial Information System and Business Intelligence Usi...

4Emerging Trends in Business IntelligenceITS 531.docx

MACHINE LEARNING WITH PYTHON PPT.pptx

H1803014347

A Software Infrastructure for Multidimensional Data Analysis: A Data Modellin...

CHATBOT FOR COLLEGE RELATED QUERIES | J4RV4I1008

Seminario Big Data - 27/11/2017

Seminario Big Data

Role of Operational System Design in Data Warehouse Implementation: Identifyi...

H017634452

integrating-cognitive-services-into-your-devops-strategy

Integrating cognitive services in to your devops strategy

Data science technology overview

Anwar kamal .pdf.pptx

Why Big Data Automation is Important for Your Business.pdf

Kürzlich hochgeladen

Strategies for Landing an Oracle DBA Job as a Fresher

Remote DBA Services

Tata AIG General Insurance Company - Insurer Innovation Award 2024

The Digital Insurer

Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024

The Digital Insurer

Automating Google Workspace (GWS) & more with Apps Script

wesley chun

A Principled Technologies deployment guide Conclusion Deploying VMware Cloud Foundation 5.1 on next gen Dell PowerEdge servers brings together critical virtualization capabilities and high-performing hardware infrastructure. Relying on our hands-on experience, this deployment guide offers a comprehensive roadmap that can guide your organization through the seamless integration of advanced VMware cloud solutions with the performance and reliability of Dell PowerEdge servers. In addition to the deployment efficiency, the Cloud Foundation 5.1 and PowerEdge solution delivered strong performance while running a MySQL database workload. By leveraging VMware Cloud Foundation 5.1 and PowerEdge servers, you could help your organization embrace cloud computing with confidence, potentially unlocking a new level of agility, scalability, and efficiency in your data center operations.

Deploy with confidence: VMware Cloud Foundation 5.1 on next gen Dell PowerEdg...

Principled Technologies

Discord is a free app offering voice, video, and text chat functionalities, primarily catering to the gaming community. It serves as a hub for users to create and join servers tailored to their interests. Discord’s ecosystem comprises servers, each functioning as a distinct online community with its own channels dedicated to specific topics or activities. Users can engage in text-based discussions, voice calls, or video chats within these channels. Understanding Discord Servers Discord servers are virtual spaces where users congregate to interact, share content, and build communities. Servers may revolve around gaming, hobbies, interests, or fandoms, providing a platform for like-minded individuals to connect. Communication Features Discord offers a range of communication tools, including text channels for messaging, voice channels for real-time audio conversations, and video channels for face-to-face interactions. These features facilitate seamless communication and collaboration. What Does NSFW Mean? The acronym NSFW stands for “Not Safe For Work,” indicating content that may be inappropriate for professional or public settings. NSFW Content NSFW content encompasses material that is sexually explicit, violent, or otherwise graphic in nature. It often includes nudity, profanity, or depictions of sensitive topics.

Understanding Discord NSFW Servers A Guide for Responsible Users.pdf

UK Journal

Abhishek Deb(1), Mr Abdul Kalam(2) M. Des (UX) , School of Design, DIT University , Dehradun. This paper explores the future potential of AI-enabled smartphone processors, aiming to investigate the advancements, capabilities, and implications of integrating artificial intelligence (AI) into smartphone technology. The research study goals consist of evaluating the development of AI in mobile phone processors, analyzing the existing state as well as abilities of AI-enabled cpus determining future patterns as well as chances together with reviewing obstacles as well as factors to consider for more growth.

Exploring the Future Potential of AI-Enabled Smartphone Processors

debabhi2

ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke

Product Anonymous

Building Digital Trust in a Digital Economy Veronica Tan, Director - Cyber Security Agency of Singapore Apidays Singapore 2024: Connecting Customers, Business and Technology (April 17 & 18, 2024) ------ Check out our conferences at https://www.apidays.global/ Do you want to sponsor or talk at one of our conferences? https://apidays.typeform.com/to/ILJeAaV8 Learn more on APIscene, the global media made by the community for the community: https://www.apiscene.io Explore the API ecosystem with the API Landscape: https://apilandscape.apiscene.io/

Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...

apidays

GenAI Risks & Security Meetup 01052024.pdf

lior mazor

As privacy and data protection regulations evolve rapidly, organizations operating in multiple jurisdictions face mounting challenges to ensure compliance and safeguard customer data. With state-specific privacy laws coming up in multiple states this year, it is essential to understand what their unique data protection regulations will require clearly. How will data privacy evolve in the US in 2024? How to stay compliant? Our panellists will guide you through the intricacies of these states' specific data privacy laws, clarifying complex legal frameworks and compliance requirements. This webinar will review: - The essential aspects of each state's privacy landscape and the latest updates - Common compliance challenges faced by organizations operating in multiple states and best practices to achieve regulatory adherence - Valuable insights into potential changes to existing regulations and prepare your organization for the evolving landscape

TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments

TrustArc

Scaling API-first – The story of a global engineering organization

Radu Cotescu

Increase engagement and revenue with Muvi Live Paywall! In this presentation, we will explore the five key benefits of using Muvi Live Paywall to monetize your live streams. You'll learn how Muvi Live Paywall can help you: Monetize your live content easily: Set up pay-per-view access to your live streams and start generating revenue from your content. Increase audience engagement: Provide exclusive, premium content behind the paywall to keep your viewers engaged. Gain valuable viewer insights: Track viewer data and analytics to better understand your audience and tailor your content accordingly. Reduce content piracy: Muvi Live Paywall's security features help protect your content from unauthorized distribution. Streamline your workflow: The all-in-one platform simplifies the process of managing and monetizing your live streams. With Muvi Live Paywall, you can take control of your live stream monetization and create a sustainable business model for your content. Learn more about Muvi Live Paywall and start generating revenue from your live streams today!

Top 5 Benefits OF Using Muvi Live Paywall For Live Streams

Roshan Dwivedi

Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024

The Digital Insurer

A Domino Admins Adventures (Engage 2024)

Gabriella Davis

The 7 Things I Know About Cyber Security After 25 Years | April 2024

Rafal Los

With more memory available, system performance of three Dell devices increased, which can translate to a better user experience Conclusion When your system has plenty of RAM to meet your needs, you can efficiently access the applications and data you need to finish projects and to-do lists without sacrificing time and focus. Our test results show that with more memory available, three Dell PCs delivered better performance and took less time to complete the Procyon Office Productivity benchmark. These advantages translate to users being able to complete workflows more quickly and multitask more easily. Whether you need the mobility of the Latitude 5440, the creative capabilities of the Precision 3470, or the high performance of the OptiPlex Tower Plus 7010, configuring your system with more RAM can help keep processes running smoothly, enabling you to do more without compromising performance.

Boost PC performance: How more available memory can improve productivity

Principled Technologies

Data Cloud, More than a CDP by Matt Robison

Anna Loughnan Colquhoun

💉💊+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHABI}}+971581248768 +971581248768 Mtp-Kit (500MG) Prices » Dubai [(+971581248768**)] Abortion Pills For Sale In Dubai, UAE, Mifepristone and Misoprostol Tablets Available In Dubai, UAE CONTACT DR.Maya Whatsapp +971581248768 We Have Abortion Pills / Cytotec Tablets /Mifegest Kit Available in Dubai, Sharjah, Abudhabi, Ajman, Alain, Fujairah, Ras Al Khaimah, Umm Al Quwain, UAE, Buy cytotec in Dubai +971581248768''''Abortion Pills near me DUBAI | ABU DHABI|UAE. Price of Misoprostol, Cytotec” +971581248768' Dr.DEEM ''BUY ABORTION PILLS MIFEGEST KIT, MISOPROTONE, CYTOTEC PILLS IN DUBAI, ABU DHABI,UAE'' Contact me now via What's App…… abortion Pills Cytotec also available Oman Qatar Doha Saudi Arabia Bahrain Above all, Cytotec Abortion Pills are Available In Dubai / UAE, you will be very happy to do abortion in Dubai we are providing cytotec 200mg abortion pill in Dubai, UAE. Medication abortion offers an alternative to Surgical Abortion for women in the early weeks of pregnancy. We only offer abortion pills from 1 week-6 Months. We then advise you to use surgery if its beyond 6 months. Our Abu Dhabi, Ajman, Al Ain, Dubai, Fujairah, Ras Al Khaimah (RAK), Sharjah, Umm Al Quwain (UAQ) United Arab Emirates Abortion Clinic provides the safest and most advanced techniques for providing non-surgical, medical and surgical abortion methods for early through late second trimester, including the Abortion By Pill Procedure (RU 486, Mifeprex, Mifepristone, early options French Abortion Pill), Tamoxifen, Methotrexate and Cytotec (Misoprostol). The Abu Dhabi, United Arab Emirates Abortion Clinic performs Same Day Abortion Procedure using medications that are taken on the first day of the office visit and will cause the abortion to occur generally within 4 to 6 hours (as early as 30 minutes) for patients who are 3 to 12 weeks pregnant. When Mifepristone and Misoprostol are used, 50% of patients complete in 4 to 6 hours; 75% to 80% in 12 hours; and 90% in 24 hours. We use a regimen that allows for completion without the need for surgery 99% of the time. All advanced second trimester and late term pregnancies at our Tampa clinic (17 to 24 weeks or greater) can be completed within 24 hours or less 99% of the time without the need surgery. The procedure is completed with minimal to no complications. Our Women's Health Center located in Abu Dhabi, United Arab Emirates, uses the latest medications for medical abortions (RU-486, Mifeprex, Mifegyne, Mifepristone, early options French abortion pill), Methotrexate and Cytotec (Misoprostol). The safety standards of our Abu Dhabi, United Arab Emirates Abortion Doctors remain unparalleled. They consistently maintain the lowest complication rates throughout the nation. Our Physicians and staff are always available to answer questions and care for women in one of the most difficult times in their lives. The decision to have an abortion at the Abortion Cl

+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...

?#DUbAI#??##{{(☎️+971_581248768%)**%*]'#abortion pills for sale in dubai@

Axa Assurance Maroc - Insurer Innovation Award 2024

The Digital Insurer

Kürzlich hochgeladen (20)

Strategies for Landing an Oracle DBA Job as a Fresher

Tata AIG General Insurance Company - Insurer Innovation Award 2024

Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024

Automating Google Workspace (GWS) & more with Apps Script

Deploy with confidence: VMware Cloud Foundation 5.1 on next gen Dell PowerEdg...

Understanding Discord NSFW Servers A Guide for Responsible Users.pdf

Exploring the Future Potential of AI-Enabled Smartphone Processors

ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke

Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...

GenAI Risks & Security Meetup 01052024.pdf

TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments

Scaling API-first – The story of a global engineering organization

Top 5 Benefits OF Using Muvi Live Paywall For Live Streams

Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024

A Domino Admins Adventures (Engage 2024)

The 7 Things I Know About Cyber Security After 25 Years | April 2024

Boost PC performance: How more available memory can improve productivity

Data Cloud, More than a CDP by Matt Robison

+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...

Axa Assurance Maroc - Insurer Innovation Award 2024

International Conference on Intelligent Systems Design and Applications 2009

1. A Business Intelligence Process to support Information Retrieval in an Ontology-Based Environment Tommaso Federici Tuscia University 01010 Viterbo, Italy [email_address] Filippo Sciarrone, Paolo Starace Open Informatica srl – BI Division Via dei Castelli Romani, 12/A 00040 Pomezia, Italy {f.sciarrone, p.starace}@openinformatica.org

5. The semantic indexing process unstructured docs ontologies terms set

6. The overall system dm1 presentation layer structured data index CUSTOM ETL PROCESS data warehouse and datamarts Addictional integrable data dm3 dm2 semantic dictionary

9. Dynamic dimension definition dimension table bridge table fact table Unbalanced ontology tree dynamic computation concept_id description parent 1 one 2 two 1 parent subsidiary distance 1 1 0 1 2 1 concept_id other_dim_id measure 1 … … … … …

10.

11.

12. Integration of the indexed data SELECT * FROM index JOIN op_fact_table ON index.op_fact_id = op_fact_table.id; SELECT * FROM ((index JOIN op_fact_table ON index.op_fact_id = op_fact_table.id) JOIN std_dimension_dt ON op_fact_table.column = std_dimension_dt.column); SELECT * FROM ((index JOIN op_fact_table ON index.op_fact_id = op_fact_table.id) JOIN std_dimension_dt ON op_fact_table.column = std_dimension_dt.column) JOIN ontology_dt ON index.concept = ontology_dt.concept; SELECT ontology_dt.ontology_id, std_dimension_dt.std_dimension_id, sum(op_fact_table.measure) FROM ((index JOIN op_fact_table ON index.op_fact_id = op_fact_table.id) JOIN std_dimension_dt ON op_fact_table.column = std_dimension_dt.column) JOIN ontology_dt ON index.concept = ontology_dt.concept GROUP BY std_dimension_dt.std_dimension_id, ontology_dt.ontology_id;

13.

14.

15.

16.

17. Thanks to all for your attention Questions?

Hinweis der Redaktion

Today the power of a company depends on how fast it take decisions about its business. Currently BI processes, to support companies business, rely only on traditional keywords searching. We think that is a good thing to extend this way to do with a semantic approach
Presentation breaks down as follow: Firstly i will introduce the semantic indexing process over this one we have developed our system. Secondly i will illustrate the dynamic dimension definition process, ranging from the working hypotheses, to the treatment of Bridge Tables and the automatic generation of OLAP dimensions. After i will explain the processes lying behind the integration of the indexed data, pointing out the most signiﬁcant SQL code parts. Last of all I will present a simple case study to summarize all the presented concepts.
Presentation breaks down as follow: Firstly i will introduce the semantic indexing process over this one we have developed our system. Secondly i will illustrate the dynamic dimension definition process, ranging from the working hypotheses, to the treatment of Bridge Tables and the automatic generation of OLAP dimensions. After i will explain the processes lying behind the integration of the indexed data, pointing out the most signiﬁcant SQL code parts. Last of all I will present a simple case study to summarize all the presented concepts.
Presentation breaks down as follow: Firstly i will introduce the semantic indexing process over this one we have developed our system. Secondly i will illustrate the dynamic dimension definition process, ranging from the working hypotheses, to the treatment of Bridge Tables and the automatic generation of OLAP dimensions. After i will explain the processes lying behind the integration of the indexed data, pointing out the most signiﬁcant SQL code parts. Last of all I will present a simple case study to summarize all the presented concepts.
Presentation breaks down as follow: Firstly i will introduce the semantic indexing process over this one we have developed our system. Secondly i will illustrate the dynamic dimension definition process, ranging from the working hypotheses, to the treatment of Bridge Tables and the automatic generation of OLAP dimensions. After i will explain the processes lying behind the integration of the indexed data, pointing out the most signiﬁcant SQL code parts. Last of all I will present a simple case study to summarize all the presented concepts.
This aspect is now left to the user’s capacity of developing consistent schemas, but it is our intention to introduce a management system based on weighted trees

International Conference on Intelligent Systems Design and Applications 2009

Empfohlen

Empfohlen

Weitere ähnliche Inhalte

Was ist angesagt?

Was ist angesagt? (20)

Ähnlich wie International Conference on Intelligent Systems Design and Applications 2009

Ähnlich wie International Conference on Intelligent Systems Design and Applications 2009 (20)

Kürzlich hochgeladen

Kürzlich hochgeladen (20)

International Conference on Intelligent Systems Design and Applications 2009

Hinweis der Redaktion