Deep Learning for Domain-Specific Entity Extraction from Unstructured Text wi...Databricks
Entity extraction, also known as named-entity recognition (NER), entity chunking and entity identification, is a subtask of information extraction with the goal of detecting and classifying phrases in a text into predefined categories. While finding entities in an automated way is useful on its own, it often serves as a preprocessing step for more complex tasks, such as relationship extraction. For example, biomedical entity extraction is a critical step for understanding the interactions between different entity types, such as the drug-disease relationship or the gene-protein relationship. Feature generation for such tasks is often complex and time consuming. However, neural networks can obviate the need for feature engineering and use original data as input.
We will demonstrate how to build a domain-specific entity extraction system from unstructured text using deep learning. In the model, domain-specific word embedding vectors are trained with word2vec learning algorithm on a Spark cluster using millions of Medline PubMed abstracts and then used as features to train an LSTM recurrent neural network for entity extraction, using Keras with TensorFlow or CNTK on a GPU-enabled Azure Data Science Virtual Machine (DSVM). Results show that training a domain-specific word embedding model boosts performance when compared to embeddings trained on generic data such as Google News. While we use biomedical data as an example, the pipeline is generic and can be applied to other domains.
Introduction to Natural Language ProcessingPranav Gupta
the presentation gives a gist about the major tasks and challenges involved in natural language processing. In the second part, it talks about one technique each for Part Of Speech Tagging and Automatic Text Summarization
Deep Learning for Domain-Specific Entity Extraction from Unstructured Text wi...Databricks
Entity extraction, also known as named-entity recognition (NER), entity chunking and entity identification, is a subtask of information extraction with the goal of detecting and classifying phrases in a text into predefined categories. While finding entities in an automated way is useful on its own, it often serves as a preprocessing step for more complex tasks, such as relationship extraction. For example, biomedical entity extraction is a critical step for understanding the interactions between different entity types, such as the drug-disease relationship or the gene-protein relationship. Feature generation for such tasks is often complex and time consuming. However, neural networks can obviate the need for feature engineering and use original data as input.
We will demonstrate how to build a domain-specific entity extraction system from unstructured text using deep learning. In the model, domain-specific word embedding vectors are trained with word2vec learning algorithm on a Spark cluster using millions of Medline PubMed abstracts and then used as features to train an LSTM recurrent neural network for entity extraction, using Keras with TensorFlow or CNTK on a GPU-enabled Azure Data Science Virtual Machine (DSVM). Results show that training a domain-specific word embedding model boosts performance when compared to embeddings trained on generic data such as Google News. While we use biomedical data as an example, the pipeline is generic and can be applied to other domains.
Introduction to Natural Language ProcessingPranav Gupta
the presentation gives a gist about the major tasks and challenges involved in natural language processing. In the second part, it talks about one technique each for Part Of Speech Tagging and Automatic Text Summarization
When dealing with over 300 hundred thousand of malware samples every day, we had to deploy the state-of-the-art techniques to combat cyberthreats. And among them - machine learning algorithms.
In this whitepaper, we start from describing the basic approaches and proceed to explaining the key applications of machine learning algorithms to automated malware detection. Learn more about how Kaspersky Lab protects businesses like yours => https://kas.pr/8dxv
CYBERSPACE
CYBER POWER
INTERNET
CYBER-ATTACK
INDIA AND PAKISTAN CYBER ATTACKS
TYPES OF CYBER CRIME
Hypotheses in the Research
Literature on the Influence of Mass Media on Criminal Behavior
Technology-Related Risk Factors for Criminal Behavior
COPYCAT CRIME:
CYBER SECURITY
SAFETY TIPS FOR CYBER CRIME
Malware Detection Using Data Mining Techniques Akash Karwande
Computer programs which have a destructive content and applied to systems from invader, are called malware and the systems on which this program are applied is called victim system .
Malwares are classified into several kinds based on behavior or attack methods.
Ultimately, in a forensic examination, we are investigating the action of a Person
Almost every event or action on a system is the result of a user either doing something
Many events change the state of the Operating System (OS)
OS Forensics helps understand how system changes correlate to events resulting from the action of somebody in the real world
Computer forensics is a very important branch of computer science in relation to computer and Internet related crimes. Earlier, computers were only used to produce data but now it has expanded to all devices related to digital data. The goal of Computer forensics is to perform crime investigations by using evidence from digital data to find who was the responsible for that particular crime.
For better research and investigation, developers have created many computer forensics tools. Police departments and investigation agencies select the tools based on various factors including budget and available experts on the team.
When dealing with over 300 hundred thousand of malware samples every day, we had to deploy the state-of-the-art techniques to combat cyberthreats. And among them - machine learning algorithms.
In this whitepaper, we start from describing the basic approaches and proceed to explaining the key applications of machine learning algorithms to automated malware detection. Learn more about how Kaspersky Lab protects businesses like yours => https://kas.pr/8dxv
CYBERSPACE
CYBER POWER
INTERNET
CYBER-ATTACK
INDIA AND PAKISTAN CYBER ATTACKS
TYPES OF CYBER CRIME
Hypotheses in the Research
Literature on the Influence of Mass Media on Criminal Behavior
Technology-Related Risk Factors for Criminal Behavior
COPYCAT CRIME:
CYBER SECURITY
SAFETY TIPS FOR CYBER CRIME
Malware Detection Using Data Mining Techniques Akash Karwande
Computer programs which have a destructive content and applied to systems from invader, are called malware and the systems on which this program are applied is called victim system .
Malwares are classified into several kinds based on behavior or attack methods.
Ultimately, in a forensic examination, we are investigating the action of a Person
Almost every event or action on a system is the result of a user either doing something
Many events change the state of the Operating System (OS)
OS Forensics helps understand how system changes correlate to events resulting from the action of somebody in the real world
Computer forensics is a very important branch of computer science in relation to computer and Internet related crimes. Earlier, computers were only used to produce data but now it has expanded to all devices related to digital data. The goal of Computer forensics is to perform crime investigations by using evidence from digital data to find who was the responsible for that particular crime.
For better research and investigation, developers have created many computer forensics tools. Police departments and investigation agencies select the tools based on various factors including budget and available experts on the team.
First public presentation of CrawlerLD (we haven't choose the name at this moment =) ) made for the 16th International Conference on Enterprise Information Systems (ICEIS) which we won the best paper award in area Area: Software Agents and Internet Computing
Evolution of the web through the lens of a developer
Tech Talk @ Georgia Gwinnett University,
1000 University Center Lane
Lawrenceville, GA 30043
Talk Schedule :
http://www.ggc.edu/ggc-life/campus-events/icalrepeat.detail/2011/03/09/744/27|25|26/Yjc4Zjg4NjM1NTAyN2JlMzRmNjczZWMzYzA2Y2JhMjU=
Mohedano E, Healy G, McGuinness K, Giró-i-Nieto X, O'Connor N, Smeaton AF. Object segmentation in images using EEG signals. ACM Multimedia 2014. Orlando, Florida (USA)
Presented on Thursday, November 8, 2014.
Abstract:
This paper explores the potential of brain-computer interfaces in segmenting objects from images. Our approach is centered around designing an effective method for displaying the image parts to the users such that they generate measurable brain reactions. When an image region, specifically a block of pixels, is displayed we estimate the probability of the block containing the object of interest using a score based on EEG activity. After several such blocks are displayed, the resulting probability map is binarized and combined with the GrabCut algorithm to segment the image into object and background regions. This study shows that BCI and simple EEG analysis are useful in locating object boundaries in images.
Full paper and video:
https://imatge.upc.edu/web/publications/object-segmentation-images-using-eeg-signals
Information Extraction --- An one hour summaryYunyao Li
This is the deck that I made when taking CS767 at Univ. of Michigan in 2006. While it is a few years' old, it is still a useful deck for people who are new to information extraction.
Open Source Software Development by TLV PartnersRoy Leiser
Our insights about Open Source software development. Trends, leading brands and practices, success stories, important Exists, Pros and Cons and much more.
Open Source Insight: NotPetya Strikes, Patching Is Vital for Risk ManagementBlack Duck by Synopsys
News about NotPetya is rebounding around the world this week as malware experts quickly determined that the resemblence to Petya is superficial. The consensus is now that NotPetya is a wiper, designed to inflict permanent damage, not ransomware as initially reported. Following closely on the heels of WannaCry incidents, NotPetya hit 64 countries by June 28, but with no kill switch available this time. Global cyberattacks such as these highlight the importance of cybersecurity everywhere, staying up to date on patches and ensuring that backups are up-to-date.
Product security by Blockchain, AI and Security CertsLabSharegroup
Three themes You need to think about Product Security — and some tips for How to Do It
I have been working with software security laboratories and IT security firms for years. I have talked with clients, read and watched dozens of articles/videos and talked with several experts about product security themes, future, technologies.
The three themes are:
Is the blockchain the new technology of trust?
Blockchain has the potential to transform industries. However, some security experts raised questions: If blockchain is broadly used in technology solutions will security standards be adopted? How to protect the cryptographic keys that allow access to the blockchain applications? Although it is true that the potential is huge such as securing IoT nodes, edge devices with authentication, improved confidentiality and data integrity, disrupting current PKI systems, reducing DDoS attacks etc.
AI (Machine Learning, Deep Learning, Reinforcement Learning algorithm) potential in Product Security
Machine learning can help in creating products that analyse threats and respond to attacks and security incidents. There are several repositories on GitHub or open-source codes by IBM available for developers. Deep learning networks are rapidly growing due to cheap cloud GPU services and after Reinforcement learning algorithm’s last success nobody knows the upper limit.
Product Security by International security standards and practices
The present, future, and developmental orientations of independent third party certificates Industry. How can the international standards answer the rapid growth of new technologies and maintain secure applications in IoT, Blockchain or AI-driven industries?
Are IT products reliable, secure and will they stay that way?
I would like to explain Product Security in a simple way. My goal is the introduction of product security for Tech startups, fast-growing Tech firms. Furthermore, I would like to emphasize the benefits of product security certification.
Open Source Insight: Who Owns Linux? TRITON Attack, App Security Testing, Fut...Black Duck by Synopsys
We look at the three reasons you must attend the FLIGHT Amsterdam conference; how to build outstanding projects in the open source community; and why isn’t every app being security tested? Plus, in-depth into the TRITON attack; why 2018 is the year of open source; how open source is driving both IoT and AI and a webinar on the 2018 Open Source Rookies of the Year.
Open Source Insight is your weekly news resource for open source security and cybersecurity news!
Rise of the Open Source Program Office for LinuxCon 2016Gil Yehuda
Open Source Program Offices collaborate on open source, policy, governance, and github to help developers improve successful outcomes for open source strategy. We describe why OSPOs are emerging, how they work, and what this means to the open source industry. We highlight a Linux Foundation sponsored collaboration called the TODOGroup where program office directors are meeting to coordinate efforts and ideas.
The presentation was delivered at LinuxCon and ContainerCon in Tokyo, Japan in July 2016.
Open Source Insight: Hub Detect & DevOps, OSS for Cars & 1.8 M Voter Info LeakedBlack Duck by Synopsys
Black Duck releases Hub Detect, a new feature which allows Black Duck Hub to run seamlessly within any DevOps toolchain regardless of the tools used, and shares its growth plans in an exclusive interview with Xconomy.
Black Duck vice president and general manager Phil Odence shares his thoughts on the quietly accelerating adoption of the AGPL. Vice president of security strategy Mike Pittenger argues that auto manufacturers need to step up their game when it comes to software security.
Vice president of product marketing provides an overview of safety, security and open source in the auto industry. Plus, 1.8 Chicago voting records leaked!
Title: The Trinity in Exponential Technologies: Open Source, Blockchain and Microsoft Azure.
This talk will explore how Open Source, Blockchain and the Microsoft Cloud provide the best combination of emerging technologies by means of a perfect synergy in terms of technological shift as well as ecosystem collaboration, with a special focus on Blockchain enterprise solutions and use cases. It will also provide insightful information about best practices, common mistakes and the use of Azure as a managed Blockchain platform (BaaS – Blockchain as a Service).
During the past few years open source has transformed the tech industry. According to Gartner's survey 85% of companies currently use open source software. In this presentation we will examine what open source is? What are the pros and cons for software developers? How big is the market? How can one make money developing an open source product and which business models companies use? If it doesn’t work – is it possible to witch from and to OS?
This presentation was created in Aug 2013.
How to become an awesome Open Source contributorChristos Matskas
The slides from my talk at FullStack 2015 on getting started with Open Source and how to become an awesome contributor or maintainer. You can find some useful links at the end as well
I created this Windows DNA report file I have tried my best to clarify all relevant details of the topics that should be included in the report. Although I initially tried to outline this topic, my efforts and my unconditional commitment to common business ended in success. I sincerely thank those who support me in coaching this topic, thank you for giving me strength, trust in me, and most importantly, every time I want, there will be a hint of this topic. Priyanka Vijay Jadhav "Windows DNA" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, URL: https://www.ijtsrd.compapers/ijtsrd43690.pdf Paper URL: https://www.ijtsrd.comcomputer-science/computer-architecture/43690/windows-dna/priyanka-vijay-jadhav
Open Source Governance in Highly Regulated Companiesiasaglobal
Open source governance is part of IT governance and focuses on the specific issues related to the acquisition, use and management of OSS, and ensuring it is done in alignment with a company?s stated objectives, policies and risk profile. And as open source becomes more common, the need for governance increases dramatically. Without proper controls and processes to ensure compliance and reduce exposure, organizations will be at risk from technical and operational, regulatory, security, legal and brand factors.
Open Source Insight: Happy Birthday Open Source and Application Security for ...Black Duck by Synopsys
Opinions differ on exactly when, but open source turned twenty this year. Most security breaches in 2017 were preventable (you hear that, Equifax?), and it’s time to take a look back to prevent similar breaches in 2018. iPhone source code gets leaked (for a short time). And keeping medical devices, voting machines, automobiles, and critical infrastructure safe in a world of increasing application risk.
Read on for open source security and cybersecurity in Open Source Insight for February 9th, 2018.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfMalak Abu Hammad
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!SOFTTECHHUB
As the digital landscape continually evolves, operating systems play a critical role in shaping user experiences and productivity. The launch of Nitrux Linux 3.5.0 marks a significant milestone, offering a robust alternative to traditional systems such as Windows 11. This article delves into the essence of Nitrux Linux 3.5.0, exploring its unique features, advantages, and how it stands as a compelling choice for both casual users and tech enthusiasts.
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
A machine learning approach to building domain specific search
1. A Machine Learning Approach to Building Domain-Specific Search Engines Presented By: Niharjyoti Sarangi Roll:06/232 8th Semester, B.Tech, IT VSSUT, Burla
2.
3. A major focus of machine learning research is to automatically learn to recognize complex patterns and make intelligent decisions based on data.
4.
5. General Web search engines :- Attempt to index large portions of the World Wide Web using a Web crawler.
6.
7. Potential Benefits over general search engines:-Greater precision due to limited scope Leverage domain knowledge including taxonomies and ontologies Support specific unique user tasks
8. Anatomy of a Search Engine Crawling the web Indexing the web Searching the indices Major Data structures Big Files Repositories Document Index Lexicon Hit Lists Forward Index
9.
10. Other terms for Web crawlers are ants, automatic indexers, bots, and worms or Web spider, Web robot, or—especially in the FOAF community—Web scutter.
11.
12. foodscience.com-Job2 JobTitle: Ice Cream Guru Employer: foodscience.com JobCategory: Travel/Hospitality JobFunction: Food Services JobLocation: Upper Midwest Contact Phone: 800-488-2611 DateExtracted: January 8, 2001 Source: www.foodscience.com/jobs_midwest.html OtherCompanyJobs: foodscience.com-Job1 Information Extraction
13. Information Extraction (contd.) As a task: As a task: Filling slots in a database from sub-segments of text. Filling slots in a database from sub-segments of text. October 14, 2002, 4:00 a.m. PT For years, Microsoft Corporation CEO Bill Gates railed against the economic philosophy of open-source software with Orwellian fervor, denouncing its communal licensing as a "cancer" that stifled technological innovation. Today, Microsoft claims to "love" the open-source concept, by which software code is made public to encourage improvement and development by outside programmers. Gates himself says Microsoft will gladly disclose its crown jewels--the coveted code behind the Windows operating system--to select customers. "We can be open source. We love the concept of shared source," said Bill Veghte, a Microsoft VP. "That's a super-important shift for us in terms of code access.“ Richard Stallman, founder of the Free Software Foundation, countered saying… October 14, 2002, 4:00 a.m. PT For years, Microsoft Corporation CEO Bill Gates railed against the economic philosophy of open-source software with Orwellian fervor, denouncing its communal licensing as a "cancer" that stifled technological innovation. Today, Microsoft claims to "love" the open-source concept, by which software code is made public to encourage improvement and development by outside programmers. Gates himself says Microsoft will gladly disclose its crown jewels--the coveted code behind the Windows operating system--to select customers. "We can be open source. We love the concept of shared source," said Bill Veghte, a Microsoft VP. "That's a super-important shift for us in terms of code access.“ Richard Stallman, founder of the Free Software Foundation, countered saying… NAME TITLE ORGANIZATION NAME TITLE ORGANIZATION
14. Information Extraction (contd.) As a task: Filling slots in a database from sub-segments of text. October 14, 2002, 4:00 a.m. PT For years, Microsoft CorporationCEOBill Gates railed against the economic philosophy of open-source software with Orwellian fervor, denouncing its communal licensing as a "cancer" that stifled technological innovation. Today, Microsoft claims to "love" the open-source concept, by which software code is made public to encourage improvement and development by outside programmers. Gates himself says Microsoft will gladly disclose its crown jewels--the coveted code behind the Windows operating system--to select customers. "We can be open source. We love the concept of shared source," said Bill Veghte, a MicrosoftVP. "That's a super-important shift for us in terms of code access.“ Richard Stallman, founder of the Free Software Foundation, countered saying… IE NAME TITLE ORGANIZATION Bill GatesCEOMicrosoft Bill VeghteVPMicrosoft Richard StallmanfounderFree Soft..
15. Information Extraction (contd.) As a familyof techniques: Information Extraction = segmentation + classification + clustering + association October 14, 2002, 4:00 a.m. PT For years, Microsoft CorporationCEOBill Gates railed against the economic philosophy of open-source software with Orwellian fervor, denouncing its communal licensing as a "cancer" that stifled technological innovation. Today, Microsoft claims to "love" the open-source concept, by which software code is made public to encourage improvement and development by outside programmers. Gates himself says Microsoft will gladly disclose its crown jewels--the coveted code behind the Windows operating system--to select customers. "We can be open source. We love the concept of shared source," said Bill Veghte, a MicrosoftVP. "That's a super-important shift for us in terms of code access.“ Richard Stallman, founder of the Free Software Foundation, countered saying… Microsoft Corporation CEO Bill Gates Microsoft Gates Microsoft Bill Veghte Microsoft VP Richard Stallman founder Free Software Foundation
16. Information Extraction (contd.) As a familyof techniques: Information Extraction = segmentation + classification + association + clustering October 14, 2002, 4:00 a.m. PT For years, Microsoft CorporationCEOBill Gates railed against the economic philosophy of open-source software with Orwellian fervor, denouncing its communal licensing as a "cancer" that stifled technological innovation. Today, Microsoft claims to "love" the open-source concept, by which software code is made public to encourage improvement and development by outside programmers. Gates himself says Microsoft will gladly disclose its crown jewels--the coveted code behind the Windows operating system--to select customers. "We can be open source. We love the concept of shared source," said Bill Veghte, a MicrosoftVP. "That's a super-important shift for us in terms of code access.“ Richard Stallman, founder of the Free Software Foundation, countered saying… Microsoft Corporation CEO Bill Gates Microsoft Gates Microsoft Bill Veghte Microsoft VP Richard Stallman founder Free Software Foundation
17. Information Extraction (contd.) As a familyof techniques: Information Extraction = segmentation + classification+ association + clustering October 14, 2002, 4:00 a.m. PT For years, Microsoft CorporationCEOBill Gates railed against the economic philosophy of open-source software with Orwellian fervor, denouncing its communal licensing as a "cancer" that stifled technological innovation. Today, Microsoft claims to "love" the open-source concept, by which software code is made public to encourage improvement and development by outside programmers. Gates himself says Microsoft will gladly disclose its crown jewels--the coveted code behind the Windows operating system--to select customers. "We can be open source. We love the concept of shared source," said Bill Veghte, a MicrosoftVP. "That's a super-important shift for us in terms of code access.“ Richard Stallman, founder of the Free Software Foundation, countered saying… Microsoft Corporation CEO Bill Gates Microsoft Gates Microsoft Bill Veghte Microsoft VP Richard Stallman founder Free Software Foundation
18. NAME TITLE ORGANIZATION Bill Gates CEO Microsoft Bill Veghte VP Microsoft Free Soft.. Richard Stallman founder Information Extraction (contd.) As a familyof techniques: Information Extraction = segmentation + classification+ association+ clustering October 14, 2002, 4:00 a.m. PT For years, Microsoft CorporationCEOBill Gates railed against the economic philosophy of open-source software with Orwellian fervor, denouncing its communal licensing as a "cancer" that stifled technological innovation. Today, Microsoft claims to "love" the open-source concept, by which software code is made public to encourage improvement and development by outside programmers. Gates himself says Microsoft will gladly disclose its crown jewels--the coveted code behind the Windows operating system--to select customers. "We can be open source. We love the concept of shared source," said Bill Veghte, a MicrosoftVP. "That's a super-important shift for us in terms of code access.“ Richard Stallman, founder of the Free Software Foundation, countered saying… Microsoft Corporation CEO Bill Gates Microsoft Gates Microsoft Bill Veghte Microsoft VP Richard Stallman founder Free Software Foundation * * * *
19. Context of Extraction Create ontology Spider Filter by relevance IE Segment Classify Associate Cluster Database Load DB Query, Search Documentcollection Train extraction models Data mine Label training data
20. IE Techniques Classify Pre-segmentedCandidates Lexicons Sliding Window Abraham Lincoln was born in Kentucky. Abraham Lincoln was born in Kentucky. Abraham Lincoln was born in Kentucky. member? Classifier Classifier Alabama Alaska … Wisconsin Wyoming which class? which class? Try alternatewindow sizes: Context Free Grammars Finite State Machines Boundary Models Abraham Lincoln was born in Kentucky. Abraham Lincoln was born in Kentucky. Abraham Lincoln was born in Kentucky. Most likely state sequence? NNP V P NP V NNP Most likely parse? Classifier PP which class? VP NP VP BEGIN END BEGIN END S …and beyond Any of these models can be used to capture words, formatting or both.
21. Sliding Window GRAND CHALLENGES FOR MACHINE LEARNING Jaime Carbonell School of Computer Science Carnegie Mellon University 3:30 pm 7500 Wean Hall Machine learning has evolved from obscurity in the 1970s into a vibrant and popular discipline in artificial intelligence during the 1980s and 1990s. As a result of its success and growth, machine learning is evolving into a collection of related disciplines: inductive concept acquisition, analytic learning in problem solving (e.g. analogy, explanation-based learning), learning theory (e.g. PAC learning), genetic algorithms, connectionist learning, hybrid systems, and so on. CMU UseNet Seminar Announcement
22. Sliding Window GRAND CHALLENGES FOR MACHINE LEARNING Jaime Carbonell School of Computer Science Carnegie Mellon University 3:30 pm 7500 Wean Hall Machine learning has evolved from obscurity in the 1970s into a vibrant and popular discipline in artificial intelligence during the 1980s and 1990s. As a result of its success and growth, machine learning is evolving into a collection of related disciplines: inductive concept acquisition, analytic learning in problem solving (e.g. analogy, explanation-based learning), learning theory (e.g. PAC learning), genetic algorithms, connectionist learning, hybrid systems, and so on. CMU UseNet Seminar Announcement
23. Sliding Window GRAND CHALLENGES FOR MACHINE LEARNING Jaime Carbonell School of Computer Science Carnegie Mellon University 3:30 pm 7500 Wean Hall Machine learning has evolved from obscurity in the 1970s into a vibrant and popular discipline in artificial intelligence during the 1980s and 1990s. As a result of its success and growth, machine learning is evolving into a collection of related disciplines: inductive concept acquisition, analytic learning in problem solving (e.g. analogy, explanation-based learning), learning theory (e.g. PAC learning), genetic algorithms, connectionist learning, hybrid systems, and so on. CMU UseNet Seminar Announcement
24. Sliding Window GRAND CHALLENGES FOR MACHINE LEARNING Jaime Carbonell School of Computer Science Carnegie Mellon University 3:30 pm 7500 Wean Hall Machine learning has evolved from obscurity in the 1970s into a vibrant and popular discipline in artificial intelligence during the 1980s and 1990s. As a result of its success and growth, machine learning is evolving into a collection of related disciplines: inductive concept acquisition, analytic learning in problem solving (e.g. analogy, explanation-based learning), learning theory (e.g. PAC learning), genetic algorithms, connectionist learning, hybrid systems, and so on. CMU UseNet Seminar Announcement
25. P(“Wean Hall Rm 5409” = LOCATION) = Prior probabilityof start position Prior probabilityof length Probabilityprefix words Probabilitycontents words Probabilitysuffix words Try all start positions and reasonable lengths Estimate these probabilities by (smoothed) counts from labeled training data. If P(“Wean Hall Rm 5409” = LOCATION)is above some threshold, extract it. Naïve Bayes Model 00 : pm Place : Wean Hall Rm 5409 Speaker : Sebastian Thrun … w t-m w t-1 w t w t+n w t+n+1 w t+n+m prefix contents suffix
26. Hidden Markov Model HMMs are the standard sequence modeling tool in genomics, music, speech, NLP, … Graphical model Finite state model S S S transitions t - 1 t t+1 ... ... observations ... Generates: State sequence Observation sequence O O O t t +1 - t 1 o1 o2 o3 o4 o5 o6 o7 o8 Parameters: for all states S={s1,s2,…} Start state probabilities: P(st ) Transition probabilities: P(st|st-1 ) Observation (emission) probabilities: P(ot|st ) Training: Maximize probability of training observations (w/ prior) Usually a multinomial over atomic, fixed alphabet
27. IE with HMM Given a sequence of observations: Yesterday Lawrence Saul spoke this example sentence. and a trained HMM: Find the most likely state sequence: (Viterbi) YesterdayLawrence Saulspoke this example sentence. Any words said to be generated by the designated “person name” state extract as a person name: Person name: Lawrence Saul
28. Limitations of HMM HMM/CRF models have a linearstructure. Web documents have a hierarchicalstructure.
29. Tree Based Models Extracting from one web site Use site-specificformatting information: e.g., “the JobTitle is a bold-faced paragraph in column 2” For large well-structured sites, like parsing a formal language Extracting from many web sites: Need general solutions to entity extraction, grouping into records, etc. Primarily use content information Must deal with a wide range of ways that users present data. Analogous to parsing natural language Problems are complementary: Site-dependent learning can collect training data for a site-independent learner
31. Wrapster Common representations for web pages include: a rendered image a DOMtree(tree of HTML markup & text) gives some of the power of hierarchical decomposition a sequence of tokens a bag of words, a sequence of characters, a node in a directed graph, . . . Questions: How can we engineer a system to generalize quickly? How can we explorerepresentational choices easily?
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33. Provo, UThead body … p p “WasBang.com .. info:” ul “Currently..” li li a a “Pittsburgh, PA” “Provo, UT”
42. References [Bikel et al 1997] Bikel, D.; Miller, S.; Schwartz, R.; and Weischedel, R. Nymble: a high-performance learning name-finder. In Proceedings of ANLP’97, p194-201. [Califf & Mooney 1999], Califf, M.E.; Mooney, R.: Relational Learning of Pattern-Match Rules for Information Extraction, in Proceedings of the Sixteenth National Conference on Artificial Intelligence (AAAI-99). [Cohen, Hurst, Jensen, 2002] Cohen, W.; Hurst, M.; Jensen, L.: A flexible learning system for wrapping tables and lists in HTML documents. Proceedings of The Eleventh International World Wide Web Conference (WWW-2002) [Cohen, Kautz, McAllester 2000] Cohen, W; Kautz, H.; McAllester, D.: Hardening soft information sources. Proceedings of the Sixth International Conference on Knowledge Discovery and Data Mining (KDD-2000). [Cohen, 1998] Cohen, W.: Integration of Heterogeneous Databases Without Common Domains Using Queries Based on Textual Similarity, in Proceedings of ACM SIGMOD-98. [Cohen, 2000a] Cohen, W.: Data Integration using Similarity Joins and a Word-based Information Representation Language, ACM Transactions on Information Systems, 18(3). [Cohen, 2000b] Cohen, W. Automatically Extracting Features for Concept Learning from the Web, Machine Learning: Proceedings of the Seventeeth International Conference (ML-2000).