Hoaxy is a tool to visualize the spread of URLs consisting low-credible web-documents. We use features related to propagation . dynamics to classify the duplicates of low-credible claims.
This is a short presentation that explains the famous TextRank papers that used graphs to produce summaries and document indices (keywords).
Link to paper : https://web.eecs.umich.edu/~mihalcea/papers/mihalcea.emnlp04.pdf
Designing of Semantic Nearest Neighbor Search: SurveyEditor IJCATR
Conventional spatial queries, such as range search and nearest neighbor retrieval, involve only conditions on objects’
geometric properties. Today, many modern applications call for novel forms of queries that aim to find objects satisfying both a spatial
predicate, and a predicate on their associated texts. For example, instead of considering all the restaurants, a nearest neighbor query
would instead ask for the restaurant that is the closest among those whose menus contain ―steak, spaghetti, brandy‖ all at the same
time. Currently the best solution to such queries is based on the IR2-tree, which, as shown in this paper, has a few deficiencies that
seriously impact its efficiency. Motivated by this, we develop a new access method called the spatial inverted index that extends the
conventional inverted index to cope with multidimensional data, and comes with algorithms that can answer nearest neighbor queries
with keywords in real time. As verified by experiments, the proposed techniques outperform the IR2-tree in query response time
significantly, often by a factor of orders of magnitude.
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-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
Philly PHP: April '17 Elastic Search Introduction by Aditya BhamidpatiRobert Calcavecchia
Philly PHP April 2017 Meetup: Introduction to Elastic Search as presented by Aditya Bhamidpati on April 19, 2017.
These slides cover an introduction to using Elastic Search
Efficiently searching nearest neighbor in documents using keywordseSAT Journals
Abstract Conservative spatial queries, such as range search and nearest neighbor reclamation, involve only conditions on objects’ numerical properties. Today, many modern applications call for novel forms of queries that aim to find objects satisfying both a spatial predicate, and a predicate on their associated texts. For example, instead of considering all the restaurants, a nearest neighbor query would instead ask for the restaurant that is the closest among those whose menus contain “steak, spaghetti, brandy” all at the same time. Currently the best solution to such queries is based on the InformationRetrieval2-tree, which, has a few deficiencies that seriously impact its efficiency. Motivated by this, there is a development of a new access method called the spatial inverted index that extends the conventional inverted index to cope with multidimensional data, and comes with algorithms that can answer nearest neighbor queries with keywords in real time. As verified by experiments, the proposed techniques outperform the InformationRetrieval2-tree in query response time significantly, often by a factor of orders of magnitude Keywords: Information retrieval, spatial index, keyword search
Hoaxy is a tool to visualize the spread of URLs consisting low-credible web-documents. We use features related to propagation . dynamics to classify the duplicates of low-credible claims.
This is a short presentation that explains the famous TextRank papers that used graphs to produce summaries and document indices (keywords).
Link to paper : https://web.eecs.umich.edu/~mihalcea/papers/mihalcea.emnlp04.pdf
Designing of Semantic Nearest Neighbor Search: SurveyEditor IJCATR
Conventional spatial queries, such as range search and nearest neighbor retrieval, involve only conditions on objects’
geometric properties. Today, many modern applications call for novel forms of queries that aim to find objects satisfying both a spatial
predicate, and a predicate on their associated texts. For example, instead of considering all the restaurants, a nearest neighbor query
would instead ask for the restaurant that is the closest among those whose menus contain ―steak, spaghetti, brandy‖ all at the same
time. Currently the best solution to such queries is based on the IR2-tree, which, as shown in this paper, has a few deficiencies that
seriously impact its efficiency. Motivated by this, we develop a new access method called the spatial inverted index that extends the
conventional inverted index to cope with multidimensional data, and comes with algorithms that can answer nearest neighbor queries
with keywords in real time. As verified by experiments, the proposed techniques outperform the IR2-tree in query response time
significantly, often by a factor of orders of magnitude.
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-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
Philly PHP: April '17 Elastic Search Introduction by Aditya BhamidpatiRobert Calcavecchia
Philly PHP April 2017 Meetup: Introduction to Elastic Search as presented by Aditya Bhamidpati on April 19, 2017.
These slides cover an introduction to using Elastic Search
Efficiently searching nearest neighbor in documents using keywordseSAT Journals
Abstract Conservative spatial queries, such as range search and nearest neighbor reclamation, involve only conditions on objects’ numerical properties. Today, many modern applications call for novel forms of queries that aim to find objects satisfying both a spatial predicate, and a predicate on their associated texts. For example, instead of considering all the restaurants, a nearest neighbor query would instead ask for the restaurant that is the closest among those whose menus contain “steak, spaghetti, brandy” all at the same time. Currently the best solution to such queries is based on the InformationRetrieval2-tree, which, has a few deficiencies that seriously impact its efficiency. Motivated by this, there is a development of a new access method called the spatial inverted index that extends the conventional inverted index to cope with multidimensional data, and comes with algorithms that can answer nearest neighbor queries with keywords in real time. As verified by experiments, the proposed techniques outperform the InformationRetrieval2-tree in query response time significantly, often by a factor of orders of magnitude Keywords: Information retrieval, spatial index, keyword search
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
Technical Whitepaper: A Knowledge Correlation Search Engines0P5a41b
For the technically oriented reader, this brief paper describes the technical foundation of the Knowledge Correlation Search Engine - patented by Make Sence, Inc.
This slide deck talks about Elasticsearch and its features.
When you talk about ELK stack it just means you are talking
about Elasticsearch, Logstash, and Kibana. But when you talk
about Elastic stack, other components such as Beats, X-Pack
are also included with it.
what is the ELK Stack?
ELK vs Elastic stack
What is Elasticsearch used for?
How does Elasticsearch work?
What is an Elasticsearch index?
Shards
Replicas
Nodes
Clusters
What programming languages does Elasticsearch support?
Amazon Elasticsearch, its use cases and benefits
This presentation contains differences between Elasticsearch and relational Databases. Along with that it also has some Glossary Of Elasticsearch and its basic operation.
Data Con LA 2022 - Pre- Recorded - OpenSearch: Everything You Need to Know Ab...Data Con LA
Seth Muthukaruppan, Consultant at Instacluster
Data Engineering
OpenSearch is an incredibly powerful search engine and analytics suite for ingesting, searching, visualizing, and analyzing your data and it is fully open source. This Apache 2.0-licensed and community-driven collection of technologies harnesses an architecture that combines the powers of Elasticsearch 7.10.2, Kibana 7.10.2 and Apache Lucene. With OpenSearch, users gain a distributed framework featuring particularly powerful scalability, high availability, and database-like capabilities. Attendees at this DataCon LA presentation will come away understanding OpenSearch's architecture and its building-block technology components, including: -- Apache Lucene utilization. Learn how this high-performance Java-based search library utilizes Lucene's inverted search index to delivers incredibly fast search results (while supporting natural language, wildcard, fuzzy, and proximity searches). -- OpenSearch cluster architecture. An OpenSearch cluster is a distributed and horizontally-scalable collection of nodes, which are differentiated based on the operations they perform. Attendees will learn the specific functions of master, master-eligible, data, client, ingest nodes. -- Data organization. Understand how OpenSearch organizes data into indices (which contain documents, which contain fields). -- Internal data structures. Get an in-depth look at how OpenSearch achieves scalability and reliability by breaking up indices into shards and segments, and utilizes translogs. -- Aggregations. See how OpenSearch enables its advanced built-in analytics capabilities through the power of aggregations.
3.Implementation with NOSQL databases Document Databases (Mongodb).pptxRushikeshChikane2
this Chapter gives information about Document Based Database and Graph based Database. It gives their basic structures, Features,applications ,Limitations and use cases
A brief presentation outlining the basics of elasticsearch for beginners. Can be used to deliver a seminar on elasticsearch.(P.S. I used it) Would Recommend the presenter to fiddle with elasticsearch beforehand.
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...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.
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 tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
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.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIVladimir Iglovikov, Ph.D.
Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
This presentation delves into the journey of Albumentations.ai, a highly successful open-source library for data augmentation.
Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentations
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
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.
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
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.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
2. What is Search Engine?
Search Engine - a set of applications designed to search for information. Usually
is part of the search engine.
The main criteria for the quality of the search engine is the relevance (degree of
compliance with the request and found that the relevance of results), fullness
index, accounting morphology of the language.
Most search services: Sphinx, Solr, ElasticSearch, etc...
3. Elasticsearch
Elasticsearch - search engine from json rest api, uses Lucene and written in Java.
Apache Lucene - a free library of open-source full-text search. Implemented in
Java, supported by the Apache Software Foundation and is produced under
license Apache Software.
Libraries: Java, C #, Python, JavaScript, PHP, Perl, Ruby
4. Requirements
In developing heavy websites or corporate systems often have trouble developing
fast and easy search engine. The following are the most important, in my opinion,
the requirements for this service:
◆ Speed
◆ Easy installation and configuration
◆ Price (preferably free and open source)
◆ Information exchange format JSON (over HTTP)
◆ Indexing in real time
◆ Multi-tenancy (flexible settings for individual user)
5. Index
Index - a database, document - a table in it, by understandable terms.
The document is a document format JSON, which is stored in elasticsearch. It's like a row in
a relational database. Each document is stored in the index, and is the type and ID. The
document is a JSON object (also known in other languages as hash / HashMap / associative
array) that contains zero or more fields or key-value pairs. The original JSON document
indexing will be stored in the field _source that returns a default receipt or document search.
6. Analysis
Analysis is the process of converting text, like the body of any email, into tokens or
terms which are added to the inverted index for searching. Analysis is performed
by an analyzer which can be either a built-in analyzer or a custom analyzer
defined per index.
7. Elasticsearch Mapping
Mapping is the process of defining how a document, and the fields it contains, are
stored and indexed. For instance, use mappings to define:
◆which string fields should be treated as full text fields.
◆which fields contain numbers, dates, or geolocations.
◆whether the values of all fields in the document should be indexed into the catch-all _all field.
◆the format of date values.
◆custom rules to control the mapping for dynamically added fields.
8. Elasticsearch Mapping
Each field has a data type which can be:
◆a simple type like text, keyword, date, long, double, boolean or ip.
◆a type which supports the hierarchical nature of JSON such as object or nested.
◆or a specialised type like geo_point, geo_shape, or completion.
9. Documents CRUD
Often, we use the terms object and document interchangeably. However, there is a distinction. An object
is just a JSON object—similar to what is known as a hash, hashmap, dictionary, or associative array.
Objects may contain other objects. In Elasticsearch, the term document has a specific meaning. It refers
to the top-level, or root object that is serialized into JSON and stored in Elasticsearch under a unique ID.
10. Query and filter context
The behaviour of a query clause depends on whether it is used in query context or in filter context:
1. Query context
A query clause used in query context answers the question “How well does this document match this query clause?”
Besides deciding whether or not the document matches, the query clause also calculates a _score representing how well
the document matches, relative to other documents.
1. Filter context
In filter context, a query clause answers the question “Does this document match this query clause?” The answer is a
simple Yes or No — no scores are calculated. Filter context is mostly used for filtering structured data, e.g.
13. Geolocation Filter
Elasticsearch offers two ways of representing geolocations: latitude-longitude points using the geo_point field type, and
complex shapes defined in GeoJSON, using the geo_shape field type.
Geo-points allow you to find points within a certain distance of another point, to calculate distances between two points for
sorting or relevance scoring, or to aggregate into a grid to display on a map. Geo-shapes, on the other hand, are used
purely for filtering. They can be used to decide whether two shapes overlap, or whether one shape completely contains
other shapes.
Four geo-point filters can be used to include or exclude documents by geolocation:
● geo_bounding_box
Find geo-points that fall within the specified rectangle.
● geo_distance
Find geo-points within the specified distance of a central point.
● geo_distance_range
Find geo-points within a specified minimum and maximum distance from a central point.
● geo_polygon
Find geo-points that fall within the specified polygon. This filter is very expensive. If you find yourself wanting to use
it, you should be looking at geo-shapes instead.