Yahoo7 Semantic Web Presentation
•
1 like•477 views
The document discusses using semantic web technologies to solve Yahoo!'s problems of siloed content across sites that doesn't allow for natural browsing. It describes how semantic standards like RDF, RDF Schema and OWL can be used to represent relationships between content as graphs of subject-predicate-object triples stored in a purpose-built graph database. This allows content to be queried and automatically linked based on relationships, breaking down silos and surfacing related content across sites.
Report
Share
Report
Share
Download to read offline
Recommended
Behaviour And Model
The document discusses Behavior Driven Development (BDD) and how it relates to Domain Driven Design (DDD). It explains that while BDD and DDD share concepts like ubiquitous language, they have different goals, with BDD focusing on shared understanding through conversation and DDD focusing on modeling domains. The document also provides references to learn more about BDD from its creators like Dan North and how it can be practiced alongside but separately from DDD.
Naming things isn't that hard
This document discusses the importance of naming systems and different metadata standards like Microdata, RDFa Lite, and Microformats. It provides information on each standard, including their URLs and examples of how they can be used. The document emphasizes that naming systems are important for making CSS readable, maintainable, and scalable.
Semantic Web, Knowledge Graph, and Other Changes to SERPS – A Google Semantic...
A Timeline to Semantic Web Developments at Google, including Google's Second Patent, the Knowledge Graph, Hummingbird and other inventions.
The Social Semantic Web: An Introduction
The document discusses leveraging semantics on social networks to address issues with existing disconnected social media sites. It describes how using common semantic formats like FOAF, SIOC and XFN/hCard to describe users, content and connections could allow interoperability between sites and alleviate problems like having separate profiles on different networks. Social networks could also serve as data sources for semantic applications if they describe objects and relationships in standardized ways.
Web 3.0
The document discusses the evolution of the internet from Web 1.0 to Web 3.0. Web 1.0 consisted of traditional media companies pushing content to passive users, while Web 2.0 enabled user-generated content through platforms that allowed everyone to publish. However, very few people were able to earn a living from publishing on these platforms. Web 3.0 aims to enable user-generated business by providing everyone with professional publishing and business management tools to run their own media businesses and make a living from their creativity.
Java EE 7 from an HTML5 Perspective, JavaLand 2015
This 45 minute session begins by explaining what we mean by the admittedly vague term "HTML5 web application". We use the Cargo Tracker sample Java EE 7 application as the vehicle for this explanation. Diving into the code, we examine the parts of the Java EE 7 family of technologies, and the HTML5 techniques used in the application.
Schema.org Structured data the What, Why, & How
This document discusses Schema.org structured data, including its origins in the Semantic Web and Linked Open Data movements. Schema.org was created in 2011 to provide a common vocabulary for structured data markup on web pages. It allows search engines and other applications to understand the intended meaning and relationships of information on web pages. The document provides examples of using Schema.org structured data and microdata, and recommends applying it across various page types to help search engines better understand websites.
Consuming Linked Data SemTech2010
This is a one hour talk introducing Linked Data and how Linked Data can be consumed by humans and by machines through SPARQL
Recommended
Behaviour And Model
The document discusses Behavior Driven Development (BDD) and how it relates to Domain Driven Design (DDD). It explains that while BDD and DDD share concepts like ubiquitous language, they have different goals, with BDD focusing on shared understanding through conversation and DDD focusing on modeling domains. The document also provides references to learn more about BDD from its creators like Dan North and how it can be practiced alongside but separately from DDD.
Naming things isn't that hard
This document discusses the importance of naming systems and different metadata standards like Microdata, RDFa Lite, and Microformats. It provides information on each standard, including their URLs and examples of how they can be used. The document emphasizes that naming systems are important for making CSS readable, maintainable, and scalable.
Semantic Web, Knowledge Graph, and Other Changes to SERPS – A Google Semantic...
A Timeline to Semantic Web Developments at Google, including Google's Second Patent, the Knowledge Graph, Hummingbird and other inventions.
The Social Semantic Web: An Introduction
The document discusses leveraging semantics on social networks to address issues with existing disconnected social media sites. It describes how using common semantic formats like FOAF, SIOC and XFN/hCard to describe users, content and connections could allow interoperability between sites and alleviate problems like having separate profiles on different networks. Social networks could also serve as data sources for semantic applications if they describe objects and relationships in standardized ways.
Web 3.0
The document discusses the evolution of the internet from Web 1.0 to Web 3.0. Web 1.0 consisted of traditional media companies pushing content to passive users, while Web 2.0 enabled user-generated content through platforms that allowed everyone to publish. However, very few people were able to earn a living from publishing on these platforms. Web 3.0 aims to enable user-generated business by providing everyone with professional publishing and business management tools to run their own media businesses and make a living from their creativity.
Java EE 7 from an HTML5 Perspective, JavaLand 2015
This 45 minute session begins by explaining what we mean by the admittedly vague term "HTML5 web application". We use the Cargo Tracker sample Java EE 7 application as the vehicle for this explanation. Diving into the code, we examine the parts of the Java EE 7 family of technologies, and the HTML5 techniques used in the application.
Schema.org Structured data the What, Why, & How
This document discusses Schema.org structured data, including its origins in the Semantic Web and Linked Open Data movements. Schema.org was created in 2011 to provide a common vocabulary for structured data markup on web pages. It allows search engines and other applications to understand the intended meaning and relationships of information on web pages. The document provides examples of using Schema.org structured data and microdata, and recommends applying it across various page types to help search engines better understand websites.
Consuming Linked Data SemTech2010
This is a one hour talk introducing Linked Data and how Linked Data can be consumed by humans and by machines through SPARQL
Knowledge Integration in Practice
Talk at the 2nd Summer Workshop of the Center for Semantic Web Research (January 16, 2016, Santiago, Chile) about the construction of Yahoo's Knowledge Graph and associated research challenges.
Breaking Through The Challenges of Scalable Deep Learning for Video Analytics
Meetup Link: https://www.meetup.com/Cognitive-Computing-Enthusiasts/events/250444108/
Recording Link: https://www.youtube.com/watch?v=4uXg1KTXdQc
When developing a machine learning system, the possibilities are limitless. However, with the recent explosion of Big Data and AI, there are more options than ever to filter through. Which technologies to select, which model topologies to build, and which infrastructure to use for deployment, just to name a few. We have explored these options for our faceted refinement system for video content system (consisting of 100K+ videos) along with their many roadblocks. Three primary areas of focus involve natural language processing, video frame sampling, and infrastructure deployment.
Netflix presentation final
Recognos is a semantic technology company established in 1999 with offices in California and Romania. They have 70 employees conducting research and development into semantic technologies. Their applications include finance, CRM, life sciences, and more. Semantic technology aims to teach machines human reasoning by representing knowledge as statements describing concepts, logic, and relationships. This allows for integrated querying across structured and unstructured data sources. Recognos can help companies like Netflix develop semantic applications such as integrated search across data sources and detecting similarities in film descriptions.
Semantic search: from document retrieval to virtual assistants
This document summarizes a presentation on semantic search given by Peter Mika, a senior research scientist at Yahoo Labs. It discusses the history and goals of semantic search, including improving query understanding and bridging the semantic gap. It also describes Yahoo's research into semantic search applications for web search, including enhancing search results, entity retrieval and recommendations, and question answering. Semantic representations of queries and documents are key to these applications.
"Why the Semantic Web will Never Work" (note the quotes)
This talk refutes some criticisms of the semantic web, but also outlines some research challenges we must overcome if we are to ever realize Tim Berners-Lee's original Semantic Web vision.
Polyglot Persistence with MongoDB and Neo4j
Learn how to enhance your application by using Neo4j and MongoDB together. Polyglot persistence is the concept of taking advantage of the strengths of different database technologies to improve functionality and enhance your application. In this webinar we will examine some use cases where it makes sense to use a document database (MongoDB) with a graph database (Neo4j) in a single application. Specifically, we will show how MongoDB can be used to provide search and browsing functionality for a product catalog while using Neo4j to provide personalized product recommendations. Finally we will look at the Neo4j Doc Manager project which facilitates syncing data from MongoDB to Neo4j to make polyglot persistence with MongoDB and Neo4j much easier.
WTF is Semantic Web?
Presentation given at Barcamp Chiang Mai 4 on the basics of Semantic Web. A simple introduction with examples, aimed for those with a little Web development experience.
Raises questions about the true identity of Tim Berners-Lee.
Knowledge graphs + Chatbots with Neo4j
The document discusses representing knowledge in a graph for chatbots. It describes using natural language processing and information extraction to understand text and create a knowledge graph. The knowledge graph is used to power applications by extracting entities, detecting intents, and probabilistically traversing the graph to answer queries while considering the user context and conversation.
A Day in the Life of a Functional Data Scientist
Video and slides synchronized, mp3 and slide download available at URL http://bit.ly/1tnEpjY.
Richard Minerich explains how ideas and tools from functional programming can save time, prevent subtle mistakes in data science, and how he incorporates them into his everyday workflow. Filmed at qconnewyork.com.
Richard Minerich works tirelessly at Bayard Rock to apply cutting edge research to anti-money laundering and fraud while using typed functional programming whenever possible. As an F# MVP he's been running events, speaking, and writing for over five years.
RDF and OWL : the powerful duo | Tara Raafat
RDF and OWL are powerful tools for making data smart. RDF uses a simple triple format to represent metadata and link data using unique identifiers, allowing for data integration. OWL builds on RDF by adding more formal semantics and defining concepts, properties, and relationships to allow for automated reasoning and inference over data. Combining OWL and RDF results in smart data that computers can understand, enabling intelligent automation and decision making.
Semantic Search with Semantic Web
This document discusses semantic search using the semantic web. It begins by describing limitations of current keyword-based search engines. It then introduces the semantic web, which aims to represent information in a way that is understandable by machines through standards like XML, RDF, RDFS, and OWL. This will allow semantic search engines to better understand the meaning of web pages to improve search results. Examples are provided of representing information about a conference using these semantic web standards to illustrate how machines could infer new facts not explicitly stated.
Sql Data Services
January 24, 2009 presentation to So Cal Code Camp at Cal State Fullerton - A real live web site with SQL Data Services.
Knowledge Graphs and Chatbots with Neo4j and IBM Watson - Christophe Willemsen
Knowledge Graphs are becoming the de-facto solution for managing complex aggregated knowledge and Neo4j is the leading platform for storing and querying connected data.
Christophe Willemsen describes a graph-centric cognitive computing pipeline and detail the process from the ingestion of unstructured text up to the generation of a knowledge graph, queryable using natural language through chatbots built with IBM Watson Conversation.
Entity Search: The Last Decade and the Next
Keynote talk given at the 10th Russian Summer School in Information Retrieval (RuSSIR ’16), Saratov, Russia, August 2016.
Note: part of the work is under still review; those slides are not yet included.
Introduction of Knowledge Graphs
This document provides an introduction to knowledge graphs. It discusses:
- The foundation and origins of knowledge graphs in semantic networks from the 1950s-60s.
- Key applications of knowledge graphs at companies like Google, Amazon, Alibaba, and Microsoft.
- Standards for knowledge graphs including RDF, OWL, and SPARQL.
- Research topics related to knowledge graph construction, reasoning, and querying.
- Approaches to constructing knowledge graphs including mapping data from Wikipedia and using machine learning techniques.
- Reasoning with knowledge graphs using description logics, and approximate reasoning techniques.
- Knowledge graph embeddings for tasks like link prediction.
Expanding Your Online Community with Web Accessibility
Donating, volunteering, and being involved in your community is for everyone ... including those with disabilities.
Inaccessible websites keep 15 percent of the population from finding you and your work online. That's millions of potential patrons, volunteers, ambassadors, and even future donors who might not be able to use your website due to small but significant errors.
In this presentation, Knowbility's Jessica Looney and Jillian Fortin will cover
- What accessibility is and why it should be a priority for nonprofits
- The business case for accessibility
- How to get buy-in from stakeholders of your organization
- A few quick website techniques to make your site more accessible today
Eyes and Ears Vol. 2
This document discusses information architecture and layered architectural frameworks. It covers topics like in-memory versus on-disk data representations, the importance of data integrity and security, and how to structure applications into layers like presentation, service, domain, and persistence layers. It also provides examples of common layered architectures for web applications using relational and document databases.
The Future of Search and SEO in Drupal
Stéphane Corlosquet and Nick Veenhof presented on the future of search and SEO. They discussed how search engines like Google are moving towards knowledge graphs that understand relationships between entities rather than just keyword matching. They explained how the Schema.org standard and modules like Schema.org and Rich Snippets for Drupal help structure Drupal content to be understood by search engines and display rich snippets in search results. The presentation demonstrated how these techniques improve search and allow Drupal sites to integrate with non-Drupal data.
Building Entities & Connections in 2020
Entities are machine classified objects and concepts that allow for reliable results, more efficient fact delivery, better UX of web search, and so much more. Basically put - entities are breathtaking! Izzi's talk touches upon entities and the Knowledge Graph within the context of Search over the past 8 years, and how brands and domains can leverage their power to be present and well-represented across SERPs, the risks of doing so, and what this all means for the ecosystem of search.
Brett Ragozzine - Graph Databases and Neo4j
This document discusses graph databases and the graph database Neo4j. It provides an introduction to graph databases, explaining that they are well-suited for storing relationships and sparse data. It then discusses Neo4j and its Cypher query language. Examples using GraphGists are provided and use cases and resources for getting started with Neo4j are listed.
DSSML24_tspann_CodelessGenerativeAIPipelines
Codeless Generative AI Pipelines
(GenAI with Milvus)
https://ml.dssconf.pl/user.html#!/lecture/DSSML24-041a/rate
Discover the potential of real-time streaming in the context of GenAI as we delve into the intricacies of Apache NiFi and its capabilities. Learn how this tool can significantly simplify the data engineering workflow for GenAI applications, allowing you to focus on the creative aspects rather than the technical complexities. I will guide you through practical examples and use cases, showing the impact of automation on prompt building. From data ingestion to transformation and delivery, witness how Apache NiFi streamlines the entire pipeline, ensuring a smooth and hassle-free experience.
Timothy Spann
https://www.youtube.com/@FLaNK-Stack
https://medium.com/@tspann
https://www.datainmotion.dev/
milvus, unstructured data, vector database, zilliz, cloud, vectors, python, deep learning, generative ai, genai, nifi, kafka, flink, streaming, iot, edge
一比一原版(UO毕业证)渥太华大学毕业证如何办理
UO毕业证录取书【微信95270640】购买（渥太华大学毕业证成绩单硕士学历）Q微信95270640代办UO学历认证留信网伪造渥太华大学学位证书精仿渥太华大学本科/硕士文凭证书补办渥太华大学 diplomaoffer,Transcript购买渥太华大学毕业证成绩单购买UO假毕业证学位证书购买伪造渥太华大学文凭证书学位证书,专业办理雅思、托福成绩单，学生ID卡，在读证明，海外各大学offer录取通知书，毕业证书，成绩单，文凭等材料:1:1完美还原毕业证、offer录取通知书、学生卡等各种在读或毕业材料的防伪工艺（包括 烫金、烫银、钢印、底纹、凹凸版、水印、防伪光标、热敏防伪、文字图案浮雕，激光镭射，紫外荧光，温感光标）学校原版上有的工艺我们一样不会少，不论是老版本还是最新版本，都能保证最高程度还原，力争完美以求让所有同学都能享受到完美的品质服务。
文凭办理流程：
1客户提供办理信息：姓名生日专业学位毕业时间等（如信息不确定可以咨询顾问：微信95270640我们有专业老师帮你查询）；
2开始安排制作毕业证成绩单电子图；
3毕业证成绩单电子版做好以后发送给您确认；
4毕业证成绩单电子版您确认信息无误之后安排制作成品；
5成品做好拍照或者视频给您确认；
6快递给客户（国内顺丰国外DHLUPS等快读邮寄）。
7完成交易删除客户资料
高精端提供以下服务：
一：渥太华大学渥太华大学毕业证文凭证书全套材料从防伪到印刷水印底纹到钢印烫金
二：真实使馆认证（留学人员回国证明）使馆存档
三：真实教育部认证教育部存档教育部留服网站可查
四：留信认证留学生信息网站可查
五：与学校颁发的相关证件1:1纸质尺寸制定（定期向各大院校毕业生购买最新版本毕,业证成绩单保证您拿到的是鲁昂大学内部最新版本毕业证成绩单微信95270640）
A.为什么留学生需要操作留信认证?
留信认证全称全国留学生信息服务网认证,隶属于北京中科院。①留信认证门槛条件更低,费用更美丽,并且包过,完单周期短,效率高②留信认证虽然不能去国企,但是一般的公司都没有问题,因为国内很多公司连基本的留学生学历认证都不了解。这对于留学生来说,这就比自己光拿一个证书更有说服力,因为留学学历可以在留信网站上进行查询!
B.为什么我们提供的毕业证成绩单具有使用价值？
查询留服认证是国内鉴别留学生海外学历的唯一途径但认证只是个体行为不是所有留学生都操作所以没有办理认证的留学生的学历在国内也是查询不到的他们也仅仅只有一张文凭。所以这时候我们提供的和学校颁发的一模一样的毕业证成绩单就有了使用价值。只硕大的蛇皮袋手里拎着长铁钩正站在门口朝黑色的屋内张望不好坏人小偷山娃一怔却也灵机一动立马仰起头双手拢在嘴边朝楼上大喊：“爸爸爸——有人找——那人一听朝山娃尴尬地笑笑悻悻地走了山娃立马“嘭的一声将铁门锁死心却咚咚地乱跳当山娃跟父亲说起这事时父亲很吃惊抚摸着山娃的头说还好醒得及时要不家早被人掏空了到时连电视也没得看啰不过父亲还是夸山娃能临危不乱随机应变有胆有谋山娃笑笑说那都是书上学的看童话和小说时多
More Related Content
Similar to Yahoo7 Semantic Web Presentation
Knowledge Integration in Practice
Talk at the 2nd Summer Workshop of the Center for Semantic Web Research (January 16, 2016, Santiago, Chile) about the construction of Yahoo's Knowledge Graph and associated research challenges.
Breaking Through The Challenges of Scalable Deep Learning for Video Analytics
Meetup Link: https://www.meetup.com/Cognitive-Computing-Enthusiasts/events/250444108/
Recording Link: https://www.youtube.com/watch?v=4uXg1KTXdQc
When developing a machine learning system, the possibilities are limitless. However, with the recent explosion of Big Data and AI, there are more options than ever to filter through. Which technologies to select, which model topologies to build, and which infrastructure to use for deployment, just to name a few. We have explored these options for our faceted refinement system for video content system (consisting of 100K+ videos) along with their many roadblocks. Three primary areas of focus involve natural language processing, video frame sampling, and infrastructure deployment.
Netflix presentation final
Recognos is a semantic technology company established in 1999 with offices in California and Romania. They have 70 employees conducting research and development into semantic technologies. Their applications include finance, CRM, life sciences, and more. Semantic technology aims to teach machines human reasoning by representing knowledge as statements describing concepts, logic, and relationships. This allows for integrated querying across structured and unstructured data sources. Recognos can help companies like Netflix develop semantic applications such as integrated search across data sources and detecting similarities in film descriptions.
Semantic search: from document retrieval to virtual assistants
This document summarizes a presentation on semantic search given by Peter Mika, a senior research scientist at Yahoo Labs. It discusses the history and goals of semantic search, including improving query understanding and bridging the semantic gap. It also describes Yahoo's research into semantic search applications for web search, including enhancing search results, entity retrieval and recommendations, and question answering. Semantic representations of queries and documents are key to these applications.
"Why the Semantic Web will Never Work" (note the quotes)
This talk refutes some criticisms of the semantic web, but also outlines some research challenges we must overcome if we are to ever realize Tim Berners-Lee's original Semantic Web vision.
Polyglot Persistence with MongoDB and Neo4j
Learn how to enhance your application by using Neo4j and MongoDB together. Polyglot persistence is the concept of taking advantage of the strengths of different database technologies to improve functionality and enhance your application. In this webinar we will examine some use cases where it makes sense to use a document database (MongoDB) with a graph database (Neo4j) in a single application. Specifically, we will show how MongoDB can be used to provide search and browsing functionality for a product catalog while using Neo4j to provide personalized product recommendations. Finally we will look at the Neo4j Doc Manager project which facilitates syncing data from MongoDB to Neo4j to make polyglot persistence with MongoDB and Neo4j much easier.
WTF is Semantic Web?
Presentation given at Barcamp Chiang Mai 4 on the basics of Semantic Web. A simple introduction with examples, aimed for those with a little Web development experience.
Raises questions about the true identity of Tim Berners-Lee.
Knowledge graphs + Chatbots with Neo4j
The document discusses representing knowledge in a graph for chatbots. It describes using natural language processing and information extraction to understand text and create a knowledge graph. The knowledge graph is used to power applications by extracting entities, detecting intents, and probabilistically traversing the graph to answer queries while considering the user context and conversation.
A Day in the Life of a Functional Data Scientist
Video and slides synchronized, mp3 and slide download available at URL http://bit.ly/1tnEpjY.
Richard Minerich explains how ideas and tools from functional programming can save time, prevent subtle mistakes in data science, and how he incorporates them into his everyday workflow. Filmed at qconnewyork.com.
Richard Minerich works tirelessly at Bayard Rock to apply cutting edge research to anti-money laundering and fraud while using typed functional programming whenever possible. As an F# MVP he's been running events, speaking, and writing for over five years.
RDF and OWL : the powerful duo | Tara Raafat
RDF and OWL are powerful tools for making data smart. RDF uses a simple triple format to represent metadata and link data using unique identifiers, allowing for data integration. OWL builds on RDF by adding more formal semantics and defining concepts, properties, and relationships to allow for automated reasoning and inference over data. Combining OWL and RDF results in smart data that computers can understand, enabling intelligent automation and decision making.
Semantic Search with Semantic Web
This document discusses semantic search using the semantic web. It begins by describing limitations of current keyword-based search engines. It then introduces the semantic web, which aims to represent information in a way that is understandable by machines through standards like XML, RDF, RDFS, and OWL. This will allow semantic search engines to better understand the meaning of web pages to improve search results. Examples are provided of representing information about a conference using these semantic web standards to illustrate how machines could infer new facts not explicitly stated.
Sql Data Services
January 24, 2009 presentation to So Cal Code Camp at Cal State Fullerton - A real live web site with SQL Data Services.
Knowledge Graphs and Chatbots with Neo4j and IBM Watson - Christophe Willemsen
Knowledge Graphs are becoming the de-facto solution for managing complex aggregated knowledge and Neo4j is the leading platform for storing and querying connected data.
Christophe Willemsen describes a graph-centric cognitive computing pipeline and detail the process from the ingestion of unstructured text up to the generation of a knowledge graph, queryable using natural language through chatbots built with IBM Watson Conversation.
Entity Search: The Last Decade and the Next
Keynote talk given at the 10th Russian Summer School in Information Retrieval (RuSSIR ’16), Saratov, Russia, August 2016.
Note: part of the work is under still review; those slides are not yet included.
Introduction of Knowledge Graphs
This document provides an introduction to knowledge graphs. It discusses:
- The foundation and origins of knowledge graphs in semantic networks from the 1950s-60s.
- Key applications of knowledge graphs at companies like Google, Amazon, Alibaba, and Microsoft.
- Standards for knowledge graphs including RDF, OWL, and SPARQL.
- Research topics related to knowledge graph construction, reasoning, and querying.
- Approaches to constructing knowledge graphs including mapping data from Wikipedia and using machine learning techniques.
- Reasoning with knowledge graphs using description logics, and approximate reasoning techniques.
- Knowledge graph embeddings for tasks like link prediction.
Expanding Your Online Community with Web Accessibility
Donating, volunteering, and being involved in your community is for everyone ... including those with disabilities.
Inaccessible websites keep 15 percent of the population from finding you and your work online. That's millions of potential patrons, volunteers, ambassadors, and even future donors who might not be able to use your website due to small but significant errors.
In this presentation, Knowbility's Jessica Looney and Jillian Fortin will cover
- What accessibility is and why it should be a priority for nonprofits
- The business case for accessibility
- How to get buy-in from stakeholders of your organization
- A few quick website techniques to make your site more accessible today
Eyes and Ears Vol. 2
This document discusses information architecture and layered architectural frameworks. It covers topics like in-memory versus on-disk data representations, the importance of data integrity and security, and how to structure applications into layers like presentation, service, domain, and persistence layers. It also provides examples of common layered architectures for web applications using relational and document databases.
The Future of Search and SEO in Drupal
Stéphane Corlosquet and Nick Veenhof presented on the future of search and SEO. They discussed how search engines like Google are moving towards knowledge graphs that understand relationships between entities rather than just keyword matching. They explained how the Schema.org standard and modules like Schema.org and Rich Snippets for Drupal help structure Drupal content to be understood by search engines and display rich snippets in search results. The presentation demonstrated how these techniques improve search and allow Drupal sites to integrate with non-Drupal data.
Building Entities & Connections in 2020
Entities are machine classified objects and concepts that allow for reliable results, more efficient fact delivery, better UX of web search, and so much more. Basically put - entities are breathtaking! Izzi's talk touches upon entities and the Knowledge Graph within the context of Search over the past 8 years, and how brands and domains can leverage their power to be present and well-represented across SERPs, the risks of doing so, and what this all means for the ecosystem of search.
Brett Ragozzine - Graph Databases and Neo4j
This document discusses graph databases and the graph database Neo4j. It provides an introduction to graph databases, explaining that they are well-suited for storing relationships and sparse data. It then discusses Neo4j and its Cypher query language. Examples using GraphGists are provided and use cases and resources for getting started with Neo4j are listed.
Similar to Yahoo7 Semantic Web Presentation (20)
Breaking Through The Challenges of Scalable Deep Learning for Video Analytics
Breaking Through The Challenges of Scalable Deep Learning for Video Analytics
Semantic search: from document retrieval to virtual assistants
Semantic search: from document retrieval to virtual assistants
"Why the Semantic Web will Never Work" (note the quotes)
"Why the Semantic Web will Never Work" (note the quotes)
Knowledge Graphs and Chatbots with Neo4j and IBM Watson - Christophe Willemsen
Knowledge Graphs and Chatbots with Neo4j and IBM Watson - Christophe Willemsen
Expanding Your Online Community with Web Accessibility
Expanding Your Online Community with Web Accessibility
Recently uploaded
DSSML24_tspann_CodelessGenerativeAIPipelines
Codeless Generative AI Pipelines
(GenAI with Milvus)
https://ml.dssconf.pl/user.html#!/lecture/DSSML24-041a/rate
Discover the potential of real-time streaming in the context of GenAI as we delve into the intricacies of Apache NiFi and its capabilities. Learn how this tool can significantly simplify the data engineering workflow for GenAI applications, allowing you to focus on the creative aspects rather than the technical complexities. I will guide you through practical examples and use cases, showing the impact of automation on prompt building. From data ingestion to transformation and delivery, witness how Apache NiFi streamlines the entire pipeline, ensuring a smooth and hassle-free experience.
Timothy Spann
https://www.youtube.com/@FLaNK-Stack
https://medium.com/@tspann
https://www.datainmotion.dev/
milvus, unstructured data, vector database, zilliz, cloud, vectors, python, deep learning, generative ai, genai, nifi, kafka, flink, streaming, iot, edge
一比一原版(UO毕业证)渥太华大学毕业证如何办理
UO毕业证录取书【微信95270640】购买（渥太华大学毕业证成绩单硕士学历）Q微信95270640代办UO学历认证留信网伪造渥太华大学学位证书精仿渥太华大学本科/硕士文凭证书补办渥太华大学 diplomaoffer,Transcript购买渥太华大学毕业证成绩单购买UO假毕业证学位证书购买伪造渥太华大学文凭证书学位证书,专业办理雅思、托福成绩单，学生ID卡，在读证明，海外各大学offer录取通知书，毕业证书，成绩单，文凭等材料:1:1完美还原毕业证、offer录取通知书、学生卡等各种在读或毕业材料的防伪工艺（包括 烫金、烫银、钢印、底纹、凹凸版、水印、防伪光标、热敏防伪、文字图案浮雕，激光镭射，紫外荧光，温感光标）学校原版上有的工艺我们一样不会少，不论是老版本还是最新版本，都能保证最高程度还原，力争完美以求让所有同学都能享受到完美的品质服务。
文凭办理流程：
1客户提供办理信息：姓名生日专业学位毕业时间等（如信息不确定可以咨询顾问：微信95270640我们有专业老师帮你查询）；
2开始安排制作毕业证成绩单电子图；
3毕业证成绩单电子版做好以后发送给您确认；
4毕业证成绩单电子版您确认信息无误之后安排制作成品；
5成品做好拍照或者视频给您确认；
6快递给客户（国内顺丰国外DHLUPS等快读邮寄）。
7完成交易删除客户资料
高精端提供以下服务：
一：渥太华大学渥太华大学毕业证文凭证书全套材料从防伪到印刷水印底纹到钢印烫金
二：真实使馆认证（留学人员回国证明）使馆存档
三：真实教育部认证教育部存档教育部留服网站可查
四：留信认证留学生信息网站可查
五：与学校颁发的相关证件1:1纸质尺寸制定（定期向各大院校毕业生购买最新版本毕,业证成绩单保证您拿到的是鲁昂大学内部最新版本毕业证成绩单微信95270640）
A.为什么留学生需要操作留信认证?
留信认证全称全国留学生信息服务网认证,隶属于北京中科院。①留信认证门槛条件更低,费用更美丽,并且包过,完单周期短,效率高②留信认证虽然不能去国企,但是一般的公司都没有问题,因为国内很多公司连基本的留学生学历认证都不了解。这对于留学生来说,这就比自己光拿一个证书更有说服力,因为留学学历可以在留信网站上进行查询!
B.为什么我们提供的毕业证成绩单具有使用价值？
查询留服认证是国内鉴别留学生海外学历的唯一途径但认证只是个体行为不是所有留学生都操作所以没有办理认证的留学生的学历在国内也是查询不到的他们也仅仅只有一张文凭。所以这时候我们提供的和学校颁发的一模一样的毕业证成绩单就有了使用价值。只硕大的蛇皮袋手里拎着长铁钩正站在门口朝黑色的屋内张望不好坏人小偷山娃一怔却也灵机一动立马仰起头双手拢在嘴边朝楼上大喊：“爸爸爸——有人找——那人一听朝山娃尴尬地笑笑悻悻地走了山娃立马“嘭的一声将铁门锁死心却咚咚地乱跳当山娃跟父亲说起这事时父亲很吃惊抚摸着山娃的头说还好醒得及时要不家早被人掏空了到时连电视也没得看啰不过父亲还是夸山娃能临危不乱随机应变有胆有谋山娃笑笑说那都是书上学的看童话和小说时多
End-to-end pipeline agility - Berlin Buzzwords 2024
We describe how we achieve high change agility in data engineering by eliminating the fear of breaking downstream data pipelines through end-to-end pipeline testing, and by using schema metaprogramming to safely eliminate boilerplate involved in changes that affect whole pipelines.
A quick poll on agility in changing pipelines from end to end indicated a huge span in capabilities. For the question "How long time does it take for all downstream pipelines to be adapted to an upstream change," the median response was 6 months, but some respondents could do it in less than a day. When quantitative data engineering differences between the best and worst are measured, the span is often 100x-1000x, sometimes even more.
A long time ago, we suffered at Spotify from fear of changing pipelines due to not knowing what the impact might be downstream. We made plans for a technical solution to test pipelines end-to-end to mitigate that fear, but the effort failed for cultural reasons. We eventually solved this challenge, but in a different context. In this presentation we will describe how we test full pipelines effectively by manipulating workflow orchestration, which enables us to make changes in pipelines without fear of breaking downstream.
Making schema changes that affect many jobs also involves a lot of toil and boilerplate. Using schema-on-read mitigates some of it, but has drawbacks since it makes it more difficult to detect errors early. We will describe how we have rejected this tradeoff by applying schema metaprogramming, eliminating boilerplate but keeping the protection of static typing, thereby further improving agility to quickly modify data pipelines without fear.
原版一比一弗林德斯大学毕业证(Flinders毕业证书)如何办理
原版制作【微信:41543339】【弗林德斯大学毕业证(Flinders毕业证书)】【微信:41543339】《成绩单、外壳、雅思、offer、真实留信官方学历认证（永久存档/真实可查）》采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路）我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信41543339】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信41543339】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
University of New South Wales degree offer diploma Transcript
澳洲UNSW毕业证书制作新南威尔士大学假文凭定制Q微168899991做UNSW留信网教留服认证海牙认证改UNSW成绩单GPA做UNSW假学位证假文凭高仿毕业证申请新南威尔士大学University of New South Wales degree offer diploma Transcript
在线办理(英国UCA毕业证书)创意艺术大学毕业证在读证明一模一样
学校原件一模一样【微信：741003700 】《(英国UCA毕业证书)创意艺术大学毕业证》【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
【主营项目】
一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【q/微741003700】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
一比一原版(CU毕业证)卡尔顿大学毕业证如何办理
原件一模一样【微信：95270640】【卡尔顿大学毕业证CU学位证成绩单】【微信：95270640】（留信学历认证永久存档查询）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信：95270640】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信：95270640】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份【微信：95270640】
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
→ 【关于价格问题（保证一手价格）
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：可来公司面谈，可签订合同，会陪同客户一起到教育部认证窗口递交认证材料，客户在教育部官方认证查询网站查询到认证通过结果后付款，不成功不收费！
办理卡尔顿大学毕业证本科学位证成绩单CU学位证【微信：95270640 】外观非常精致，由特殊纸质材料制成，上面印有校徽、校名、毕业生姓名、专业等信息。
办理卡尔顿大学毕业证CU学位证本科学位证成绩单【微信：95270640 】格式相对统一，各专业都有相应的模板。通常包括以下部分：
校徽：象征着学校的荣誉和传承。
校名:学校英文全称
授予学位：本部分将注明获得的具体学位名称。
毕业生姓名：这是最重要的信息之一，标志着该证书是由特定人员获得的。
颁发日期：这是毕业正式生效的时间，也代表着毕业生学业的结束。
其他信息：根据不同的专业和学位，可能会有一些特定的信息或章节。
办理卡尔顿大学毕业证本科学位证成绩单CU学位证【微信：95270640 】价值很高，需要妥善保管。一般来说，应放置在安全、干燥、防潮的地方，避免长时间暴露在阳光下。如需使用，最好使用复印件而不是原件，以免丢失。
综上所述，办理卡尔顿大学毕业证本科学位证成绩单CU学位证【微信：95270640 】是证明身份和学历的高价值文件。外观简单庄重，格式统一，包括重要的个人信息和发布日期。对持有人来说，妥善保管是非常重要的。
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data Lake
Dynamic policy enforcement is becoming an increasingly important topic in today’s world where data privacy and compliance is a top priority for companies, individuals, and regulators alike. In these slides, we discuss how LinkedIn implements a powerful dynamic policy enforcement engine, called ViewShift, and integrates it within its data lake. We show the query engine architecture and how catalog implementations can automatically route table resolutions to compliance-enforcing SQL views. Such views have a set of very interesting properties: (1) They are auto-generated from declarative data annotations. (2) They respect user-level consent and preferences (3) They are context-aware, encoding a different set of transformations for different use cases (4) They are portable; while the SQL logic is only implemented in one SQL dialect, it is accessible in all engines.
#SQL #Views #Privacy #Compliance #DataLake
Intelligence supported media monitoring in veterinary medicine
Media monitoring in veterinary medicien
Experts live - Improving user adoption with AI
Bekijk de slides van onze sessie Enhancing Modern Workplace Efficiency op Experts Live 2024.
一比一原版(harvard毕业证书）哈佛大学毕业证如何办理
一模一样【微信：A575476】【(harvard毕业证书）哈佛大学毕业证成绩单Offer】【微信：A575476】（留信学历认证永久存档查询）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信：A575476】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信：A575476】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
→ 【关于价格问题（保证一手价格）
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：可来公司面谈，可签订合同，会陪同客户一起到教育部认证窗口递交认证材料，客户在教育部官方认证查询网站查询到认证通过结果后付款，不成功不收费！
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
by
Timothy Spann
Principal Developer Advocate
https://budapestdata.hu/2024/en/
https://budapestml.hu/2024/en/
tim.spann@zilliz.com
https://www.linkedin.com/in/timothyspann/
https://x.com/paasdev
https://github.com/tspannhw
https://www.youtube.com/@flank-stack
milvus
vector database
gen ai
generative ai
deep learning
machine learning
apache nifi
apache pulsar
apache kafka
apache flink
原版一比一多伦多大学毕业证(UofT毕业证书)如何办理
原版制作【微信:41543339】【多伦多大学毕业证(UofT毕业证书)】【微信:41543339】《成绩单、外壳、雅思、offer、真实留信官方学历认证（永久存档/真实可查）》采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路）我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信41543339】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信41543339】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
原版制作(unimelb毕业证书)墨尔本大学毕业证Offer一模一样
学校原件一模一样【微信：741003700 】《(unimelb毕业证书)墨尔本大学毕业证》【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
【主营项目】
一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【q/微741003700】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
一比一原版兰加拉学院毕业证(Langara毕业证书)学历如何办理
原版办【微信号:BYZS866】【兰加拉学院毕业证(Langara毕业证书)】【微信号:BYZS866】《成绩单、外壳、雅思、offer、真实留信官方学历认证（永久存档/真实可查）》采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路）我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信号BYZS866】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信号BYZS866】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...
"Join us for STATATHON, a dynamic 2-day event dedicated to exploring statistical knowledge and its real-world applications. From theory to practice, participants engage in intensive learning sessions, workshops, and challenges, fostering a deeper understanding of statistical methodologies and their significance in various fields."
"Financial Odyssey: Navigating Past Performance Through Diverse Analytical Lens"
Embark on a captivating financial journey with 'Financial Odyssey,' our hackathon project. Delve deep into the past performance of two companies as we employ an array of financial statement analysis techniques. From ratio analysis to trend analysis, uncover insights crucial for informed decision-making in the dynamic world of finance."
Recently uploaded (20)
End-to-end pipeline agility - Berlin Buzzwords 2024
End-to-end pipeline agility - Berlin Buzzwords 2024
University of New South Wales degree offer diploma Transcript
University of New South Wales degree offer diploma Transcript
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data Lake
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data Lake
Intelligence supported media monitoring in veterinary medicine
Intelligence supported media monitoring in veterinary medicine
A presentation that explain the Power BI Licensing
A presentation that explain the Power BI Licensing
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
DATA COMMS-NETWORKS YR2 lecture 08 NAT & CLOUD.docx
DATA COMMS-NETWORKS YR2 lecture 08 NAT & CLOUD.docx
STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...
STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...
"Financial Odyssey: Navigating Past Performance Through Diverse Analytical Lens"
"Financial Odyssey: Navigating Past Performance Through Diverse Analytical Lens"
Yahoo7 Semantic Web Presentation
- 1. Semantic Web Paul White
- 2. Yahoo!7 Proprietary and Confidential
- 3. The Problems ● Yahoo!7 is known for having great breadth of content, but not depth
- 4. The Problems ● Content is silo’d across different sites and knowledge domains ● Users get stuck in these property silos
- 5. The Problems ● Site structure doesn’t allow for natural human browsing patterns ● Visitors browse by content, not type
- 6. The Tech ● So, what do we use to solve these problems? It’s all about relationships! ● Resource Description Framework (RDF) ○ Basic building block of the Semantic Web ○ Consistent format for representing data ○ Triples: Subject -> Predicate -> Object Predicate:Portrays Predicate:Character In
- 7. The Tech ● RDF Schema ○ Basic data types ○ Classes/Subclasses ○ Property (Predicates) ● Web Ontology Language (OWL) ○ Ontologies - everything else! ○ What is a TV Show ○ What is an Actor ○ What is a Sporting Event ○ What are their relationships?
- 8. The Tech ● Graphs Yahoo!7 TV Portrays Character In Winners and Losers Melbourne Cup Carnival is a born in TV Show Legend Predicate Subject / Object Sporting Event Social Event Yahoo!7 Sport Yahoo!7 Lifestyle Derby Day Crown Oaks spouse Adelaide Matt Kingston DBPedia is a Attended is a an event in
- 9. The Tech ● Storage ● Built specifically for storing and reading graph data ● Stores everything - data, metadata, schemas, ontologies ● Allows for inferencing - e.g. ○ Sporting Event subclassOf Event ○ Melbourne Cup Festival subclassOf Sporting Event therefore ○ Melbourne Cup Festival subclassOf Event
- 10. The Tech predicate ● Query Language ● Designed for querying triples CONSTRUCT { ?Actor portrays ?Character } WHERE { ?Actor portrays ?Character } Results in Melanie Vallejo portrays Sophie Wong ; Ray Meagher portrays Alf Stewart ; Hayden Christensen portrays Anakin Skywalker ; Hayden Christensen portrays Darth Vader . Legend ?Variable
- 11. The Tech ● Named Entity Recognition ● Specialised branch of Natural Language Processing ● Generate annotations that link from this thing to that thing ● Two steps ○ Name Recognition ○ Entity Classification
- 12. The Results ● Show Silos broken down X-Factor Content Stream - Luke Jacobz Home and Away Content Stream - Luke Jacobz
- 13. The Results ● Sites are now structured to surface related content
- 14. The Results ● Automatic Discovery and hyperlinking of Named Entities
- 15. Questions?