This technical talk describes the usage of Apache based open source software (Apache Lucene/SOLR, Apache Nutch, Apache Tika and Apache ServiceMix) within the implementation of an enterprise search and retrieval platform. The platform is the result of years of experience with enterprise search technologies combined with enterprise application integration and semantic (web) technologies, both within commercial and open source based environments. The talk will dive into the conceptual architecture of a typical search solutions based upon a real world use case, and will then present the accompanying framework that makes easy and swift implementations of enterprise search solutions possible, based upon this architecture. The architecture describes an innovative enterprise search solution, specifying all necessary components for collecting and indexing content (known in the architecture as the collection process, which consist of inbound, splitting, validating, filtering, enriching and indexing components) and publishing the content (known in the architecture as the publication process, which consists of inbound, validating, request enriching, searching, grouping, response enriching and presentation components). The framework can be seen as an orchestrator framework and contains all tools, components and default configurations and flow descriptions necessary to build enterprise solutions according to this architecture. The framework is entirely based upon open source technologies and are mainly Apache based
Open source enterprise search and retrieval platformmteutelink
The document discusses how Apache open source software is used in implementing an enterprise search and retrieval platform. It provides an overview of enterprise search, including its key features and challenges. It then outlines the logical architecture of an enterprise search solution, covering the collection and publication processes. The collection process involves pulling or pushing content from various sources, validating, enriching and indexing it. The publication process involves handling search requests, filtering, grouping results and returning responses.
Faster! Optimize Your Cascade Server Experience, by Justin Klingman, Beacon T...hannonhill
In today’s world, we want our online experience to be as fast as possible (who wants to wait?), and our interaction with Cascade Server is no different. In this session, Justin Klingman of Beacon Technologies will cover Cascade Server optimization techniques--including auditing slow sites, index block settings and use, XSLT coding tips, and hardware configuration for optimal performance.
Large Scale Crawling with Apache Nutch and FriendsJulien Nioche
This session will give an overview of Apache Nutch. I will describe its main components and how it fits with other Apache projects such as Hadoop, SOLR, Tika or HBase. The second part of the presentation will be focused on the latest developments in Nutch, the differences between the 1.x and 2.x branch and what we can expect to see in Nutch in the future. This session will cover many practical aspects and should be a good starting point to crawling on a large scale with Apache Nutch and SOLR.
Populate your Search index, NEST 2016-01David Smiley
This document discusses considerations for populating a search index. It covers topics like how to get data into the index, backups, scheduling and monitoring indexing, real-time search requirements, and common software used for crawlers and pipelines. Specific approaches are suggested for bulk indexing, incremental indexing, detecting deletes, and taking backups. The challenges of document transformations and mapping source data to search documents are also addressed. Open-source ETL software options like Clover ETL, Pentaho, and Talend are briefly summarized, with Talend and Apache NiFi receiving more detailed overviews.
From the Fast Feather Track at ApacheCon NA 2010 in Atlanta
This quick talk provides an overview of Apache Tika, looks at a new features and supported file formats. It then shows how to create a new parser, and finishes with using Tika from your own application.
Tika is a toolkit for detecting and extracting metadata and structured text content from various documents such as PDFs, Word, and HTML. It allows parsing of document files into XHTML output and metadata. Tika uses a ContentHandler interface to parse document streams into SAX events and extract metadata using a Parser interface. It supports many file formats through built-in parsers and uses Apache Lucene for type detection.
Large Scale Crawling with Apache Nutch and Friendslucenerevolution
Presented by Julien Nioche, Director, DigitalPebble
This session will give an overview of Apache Nutch. I will describe its main components and how it fits with other Apache projects such as Hadoop, SOLR, Tika or HBase. The second part of the presentation will be focused on the latest developments in Nutch, the differences between the 1.x and 2.x branch and what we can expect to see in Nutch in the future. This session will cover many practical aspects and should be a good starting point to crawling on a large scale with Apache Nutch and SOLR.
This document provides an overview of the search engine capabilities of Apache Solr/Lucene. It begins with an introduction to search engines and their capabilities. It then discusses Apache Lucene as a full-text search library and Apache Solr as an enterprise search platform built on Lucene. Key features of Lucene like indexing, querying, and its architecture are described. The document also explores Solr's features such as caching, SolrCloud, and its architecture. It provides examples of queries in Solr and references for further information.
Open source enterprise search and retrieval platformmteutelink
The document discusses how Apache open source software is used in implementing an enterprise search and retrieval platform. It provides an overview of enterprise search, including its key features and challenges. It then outlines the logical architecture of an enterprise search solution, covering the collection and publication processes. The collection process involves pulling or pushing content from various sources, validating, enriching and indexing it. The publication process involves handling search requests, filtering, grouping results and returning responses.
Faster! Optimize Your Cascade Server Experience, by Justin Klingman, Beacon T...hannonhill
In today’s world, we want our online experience to be as fast as possible (who wants to wait?), and our interaction with Cascade Server is no different. In this session, Justin Klingman of Beacon Technologies will cover Cascade Server optimization techniques--including auditing slow sites, index block settings and use, XSLT coding tips, and hardware configuration for optimal performance.
Large Scale Crawling with Apache Nutch and FriendsJulien Nioche
This session will give an overview of Apache Nutch. I will describe its main components and how it fits with other Apache projects such as Hadoop, SOLR, Tika or HBase. The second part of the presentation will be focused on the latest developments in Nutch, the differences between the 1.x and 2.x branch and what we can expect to see in Nutch in the future. This session will cover many practical aspects and should be a good starting point to crawling on a large scale with Apache Nutch and SOLR.
Populate your Search index, NEST 2016-01David Smiley
This document discusses considerations for populating a search index. It covers topics like how to get data into the index, backups, scheduling and monitoring indexing, real-time search requirements, and common software used for crawlers and pipelines. Specific approaches are suggested for bulk indexing, incremental indexing, detecting deletes, and taking backups. The challenges of document transformations and mapping source data to search documents are also addressed. Open-source ETL software options like Clover ETL, Pentaho, and Talend are briefly summarized, with Talend and Apache NiFi receiving more detailed overviews.
From the Fast Feather Track at ApacheCon NA 2010 in Atlanta
This quick talk provides an overview of Apache Tika, looks at a new features and supported file formats. It then shows how to create a new parser, and finishes with using Tika from your own application.
Tika is a toolkit for detecting and extracting metadata and structured text content from various documents such as PDFs, Word, and HTML. It allows parsing of document files into XHTML output and metadata. Tika uses a ContentHandler interface to parse document streams into SAX events and extract metadata using a Parser interface. It supports many file formats through built-in parsers and uses Apache Lucene for type detection.
Large Scale Crawling with Apache Nutch and Friendslucenerevolution
Presented by Julien Nioche, Director, DigitalPebble
This session will give an overview of Apache Nutch. I will describe its main components and how it fits with other Apache projects such as Hadoop, SOLR, Tika or HBase. The second part of the presentation will be focused on the latest developments in Nutch, the differences between the 1.x and 2.x branch and what we can expect to see in Nutch in the future. This session will cover many practical aspects and should be a good starting point to crawling on a large scale with Apache Nutch and SOLR.
This document provides an overview of the search engine capabilities of Apache Solr/Lucene. It begins with an introduction to search engines and their capabilities. It then discusses Apache Lucene as a full-text search library and Apache Solr as an enterprise search platform built on Lucene. Key features of Lucene like indexing, querying, and its architecture are described. The document also explores Solr's features such as caching, SolrCloud, and its architecture. It provides examples of queries in Solr and references for further information.
The document discusses ProjectHub, a software that crawls, indexes, and allows searching of software project data using various tools like Droids, Tika, Solr, and Hadoop. It describes the architecture which gathers information from different sources like JIRA, mailing lists, code repositories, and indexes it using Solr for faceted search, spellchecking, autocomplete and other features. It also discusses performance monitoring, analytics and future plans.
Talk about Apache Nutch on ApacheCon Europe 2014:
http://sched.co/1nyYa7b
http://events.linuxfoundation.org/sites/events/files/slides/aceu2014-snagel-web-crawling-nutch.pdf
Storm-Crawler is a collection of resources for building low-latency, large scale web crawlers on Apache Storm. We will compare with similar projects like Apache Nutch and present several use cases where the storm-crawler is being used. In particular we will see how the Storm-crawler can be used with ElasticSearch and Kibana for crawling and indexing web pages.
A search engine crawls websites to build an index of web pages, then uses algorithms to rank pages for relevant search results. Meta search engines submit queries to multiple other search engines and aggregate the results into a single summary. Registration involves providing basic site details to be included in a search engine's index. Key factors in rankings include meta titles, keywords, and incoming links. Search engines regularly update their algorithms and indexes.
In this session, we will look first at the rich metadata that documents in your repository have, how to control the mapping of this on to your content model, and some of the interesting things this can deliver. We'll then move on to the content transformation and rendition services, and see how you can easily and powerfully generate a wide range of media from the content you already have.
This talk will give an overview of Apache Nutch, its main components, how it fits with other Apache projects and its latest developments.
Apache Nutch was started exactly 10 years ago and was the starting point for what later became Apache Hadoop and also Apache Tika. Nutch is nowadays the tool of reference for large scale web crawling.
In this talk I will give an overview of Apache Nutch and describe its main components and how Nutch fits with other Apache projects such as Hadoop, SOLR or Tika.
The second part of the presentation will be focused on the latest developments in Nutch and the changes introduced by the 2.x branch with the use of Apache GORA as a front end to various NoSQL datastores.
Apache Lucene: Searching the Web and Everything Else (Jazoon07)dnaber
Apache Lucene is a free and open-source search library that provides indexing and searching capabilities. It includes Lucene Java, a core Java library, Solr, a search server with web administration, and Nutch, an open-source web crawler and search engine. Lucene Java provides indexing and searching capabilities, Solr adds web-based administration and HTTP access, and Nutch crawls websites and indexes content.
The document provides an overview and agenda for an Apache Solr crash course. It discusses topics such as information retrieval, inverted indexes, metrics for evaluating IR systems, Apache Lucene, the Lucene and Solr APIs, indexing, searching, querying, filtering, faceting, highlighting, spellchecking, geospatial search, and Solr architectures including single core, multi-core, replication, and sharding. It also provides tips on performance tuning, using plugins, and developing a Solr-based search engine.
Apache Solr is the popular, blazing fast open source enterprise search platform; it uses
Lucene as its core search engine. Solr’s major features include powerful full-text search, hit
highlighting, faceted search, dynamic clustering, database integration, and complex queries.
Solr is highly scalable, providing distributed search and index replication, and it powers the
search and navigation features of many of the world's largest internet sites.
Apache Tika aims to make it easier to extract metadata and structured text content from all kinds of files. Tika is a subproject of Apache Lucene, and leverages libraries like Apache POI and Apache PDFBox to provide a powerful yet simple interface for parsing dozens of document formats. This makes Tika an ideal companion for Apache Lucene, or for any search engine that needs to be able to index metadata and content from many different types of files. This presentation introduces Apache Tika and shows how it's being used in projects like Apache Solr and Apache Jackrabbit. You will learn how to integrate Tika with your application and how to configure and extend Tika to best suit your needs.
En este webminar exploramos el nuevo sistema de búsquedas del portal del Museo Reina Sofía y diseccionamos su implementación basada en Drupal y Apache Solr.
Tika is a toolkit for extracting metadata and text from various document formats. It allows developers to parse documents and extract metadata and text content in 3 main steps. Tika shields systems like Alfresco from needing to integrate many individual parsing components. Alfresco uses Tika to index content from various formats by passing file streams through Tika's parsers rather than using multiple custom transformers.
Building Enterprise Search Engines using Open Source TechnologiesRahul Singh
Enterprise Search is a challenging problem for most organizations. Public search technologies such as Google can index content and use link popularity to rank content in addition to the basic keyword matches. Enterprise Search is different. Sometimes it requires specially designed indexes as well as several processing steps.
At the U.S. Patent & Trademark Office, part of the Department of Commerce, a team of professionals is building the next generation of search tools using open source technologies. Like any large undertaking, it’s not a simple plug and play project.
Main topics to be covered in this talk:
+ Architectures for Large Scale Enterprise Search
+ Leveraging Apache Cassandra & Spark
+ Customizing / Configuring Apache SolR and Indexing
+ Writing a custom Parser for SolR in Scala
Este documento describe Apache Solr, un motor de búsqueda de código abierto que puede indexar y buscar documentos basándose en características especificadas. Solr permite búsquedas de texto completo, resaltado de términos, búsquedas por facetas y correcciones ortográficas. Se utiliza comúnmente para sistemas con grandes volúmenes de datos donde la búsqueda por múltiples parámetros es importante. Solr es independiente del lenguaje de programación, la aplicación o la plataforma y puede
SOLR es el nuevo motor de indexación que incorpora Alfresco en su versión 4.0, no obstante, se puede seguir usando Lucene. En este webinar de una hora de duración, junto a Baratz (Partner Gold de Alfresco), vamos a aprender qué es SOLR, cómo funciona y cómo está soportado, como configurarlo y migrar de Lucene a Solr, qué efectos tiene en el repositorio y que mejoras nos aporta.
In this session, we will look first at the rich metadata that documents in your repository have, how to control the mapping of this on to your content model, and some of the interesting things this can deliver. We’ll then move on to the content transformation and rendition services, and see how you can easily and powerfully generate a wide range of media from the content you already have. Finally, we’ll look at how to extend these services to support additional formats.
Este documento introduce Solr, un servidor de búsqueda y indexación de texto completo. Explica que Solr se comunica a través de HTTP, soporta formatos XML y JSON, y está basado en Lucene, una librería de búsqueda de texto completo. También describe algunos conceptos fundamentales como documentos, campos y términos, e incluye ejemplos de cómo instalar y usar Solr.
Este documento describe cómo extender Solr mediante la implementación de componentes de búsqueda y transformadores de documentos. Explica cómo crear un componente de búsqueda para limitar el número máximo de documentos devueltos y cómo crear un transformador de documentos para añadir o quitar campos de la respuesta antes de la serialización. También cubre conceptos como parámetros de configuración, excepciones Solr y la inicialización de componentes.
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
AI 101: An Introduction to the Basics and Impact of Artificial IntelligenceIndexBug
Imagine a world where machines not only perform tasks but also learn, adapt, and make decisions. This is the promise of Artificial Intelligence (AI), a technology that's not just enhancing our lives but revolutionizing entire industries.
The document discusses ProjectHub, a software that crawls, indexes, and allows searching of software project data using various tools like Droids, Tika, Solr, and Hadoop. It describes the architecture which gathers information from different sources like JIRA, mailing lists, code repositories, and indexes it using Solr for faceted search, spellchecking, autocomplete and other features. It also discusses performance monitoring, analytics and future plans.
Talk about Apache Nutch on ApacheCon Europe 2014:
http://sched.co/1nyYa7b
http://events.linuxfoundation.org/sites/events/files/slides/aceu2014-snagel-web-crawling-nutch.pdf
Storm-Crawler is a collection of resources for building low-latency, large scale web crawlers on Apache Storm. We will compare with similar projects like Apache Nutch and present several use cases where the storm-crawler is being used. In particular we will see how the Storm-crawler can be used with ElasticSearch and Kibana for crawling and indexing web pages.
A search engine crawls websites to build an index of web pages, then uses algorithms to rank pages for relevant search results. Meta search engines submit queries to multiple other search engines and aggregate the results into a single summary. Registration involves providing basic site details to be included in a search engine's index. Key factors in rankings include meta titles, keywords, and incoming links. Search engines regularly update their algorithms and indexes.
In this session, we will look first at the rich metadata that documents in your repository have, how to control the mapping of this on to your content model, and some of the interesting things this can deliver. We'll then move on to the content transformation and rendition services, and see how you can easily and powerfully generate a wide range of media from the content you already have.
This talk will give an overview of Apache Nutch, its main components, how it fits with other Apache projects and its latest developments.
Apache Nutch was started exactly 10 years ago and was the starting point for what later became Apache Hadoop and also Apache Tika. Nutch is nowadays the tool of reference for large scale web crawling.
In this talk I will give an overview of Apache Nutch and describe its main components and how Nutch fits with other Apache projects such as Hadoop, SOLR or Tika.
The second part of the presentation will be focused on the latest developments in Nutch and the changes introduced by the 2.x branch with the use of Apache GORA as a front end to various NoSQL datastores.
Apache Lucene: Searching the Web and Everything Else (Jazoon07)dnaber
Apache Lucene is a free and open-source search library that provides indexing and searching capabilities. It includes Lucene Java, a core Java library, Solr, a search server with web administration, and Nutch, an open-source web crawler and search engine. Lucene Java provides indexing and searching capabilities, Solr adds web-based administration and HTTP access, and Nutch crawls websites and indexes content.
The document provides an overview and agenda for an Apache Solr crash course. It discusses topics such as information retrieval, inverted indexes, metrics for evaluating IR systems, Apache Lucene, the Lucene and Solr APIs, indexing, searching, querying, filtering, faceting, highlighting, spellchecking, geospatial search, and Solr architectures including single core, multi-core, replication, and sharding. It also provides tips on performance tuning, using plugins, and developing a Solr-based search engine.
Apache Solr is the popular, blazing fast open source enterprise search platform; it uses
Lucene as its core search engine. Solr’s major features include powerful full-text search, hit
highlighting, faceted search, dynamic clustering, database integration, and complex queries.
Solr is highly scalable, providing distributed search and index replication, and it powers the
search and navigation features of many of the world's largest internet sites.
Apache Tika aims to make it easier to extract metadata and structured text content from all kinds of files. Tika is a subproject of Apache Lucene, and leverages libraries like Apache POI and Apache PDFBox to provide a powerful yet simple interface for parsing dozens of document formats. This makes Tika an ideal companion for Apache Lucene, or for any search engine that needs to be able to index metadata and content from many different types of files. This presentation introduces Apache Tika and shows how it's being used in projects like Apache Solr and Apache Jackrabbit. You will learn how to integrate Tika with your application and how to configure and extend Tika to best suit your needs.
En este webminar exploramos el nuevo sistema de búsquedas del portal del Museo Reina Sofía y diseccionamos su implementación basada en Drupal y Apache Solr.
Tika is a toolkit for extracting metadata and text from various document formats. It allows developers to parse documents and extract metadata and text content in 3 main steps. Tika shields systems like Alfresco from needing to integrate many individual parsing components. Alfresco uses Tika to index content from various formats by passing file streams through Tika's parsers rather than using multiple custom transformers.
Building Enterprise Search Engines using Open Source TechnologiesRahul Singh
Enterprise Search is a challenging problem for most organizations. Public search technologies such as Google can index content and use link popularity to rank content in addition to the basic keyword matches. Enterprise Search is different. Sometimes it requires specially designed indexes as well as several processing steps.
At the U.S. Patent & Trademark Office, part of the Department of Commerce, a team of professionals is building the next generation of search tools using open source technologies. Like any large undertaking, it’s not a simple plug and play project.
Main topics to be covered in this talk:
+ Architectures for Large Scale Enterprise Search
+ Leveraging Apache Cassandra & Spark
+ Customizing / Configuring Apache SolR and Indexing
+ Writing a custom Parser for SolR in Scala
Este documento describe Apache Solr, un motor de búsqueda de código abierto que puede indexar y buscar documentos basándose en características especificadas. Solr permite búsquedas de texto completo, resaltado de términos, búsquedas por facetas y correcciones ortográficas. Se utiliza comúnmente para sistemas con grandes volúmenes de datos donde la búsqueda por múltiples parámetros es importante. Solr es independiente del lenguaje de programación, la aplicación o la plataforma y puede
SOLR es el nuevo motor de indexación que incorpora Alfresco en su versión 4.0, no obstante, se puede seguir usando Lucene. En este webinar de una hora de duración, junto a Baratz (Partner Gold de Alfresco), vamos a aprender qué es SOLR, cómo funciona y cómo está soportado, como configurarlo y migrar de Lucene a Solr, qué efectos tiene en el repositorio y que mejoras nos aporta.
In this session, we will look first at the rich metadata that documents in your repository have, how to control the mapping of this on to your content model, and some of the interesting things this can deliver. We’ll then move on to the content transformation and rendition services, and see how you can easily and powerfully generate a wide range of media from the content you already have. Finally, we’ll look at how to extend these services to support additional formats.
Este documento introduce Solr, un servidor de búsqueda y indexación de texto completo. Explica que Solr se comunica a través de HTTP, soporta formatos XML y JSON, y está basado en Lucene, una librería de búsqueda de texto completo. También describe algunos conceptos fundamentales como documentos, campos y términos, e incluye ejemplos de cómo instalar y usar Solr.
Este documento describe cómo extender Solr mediante la implementación de componentes de búsqueda y transformadores de documentos. Explica cómo crear un componente de búsqueda para limitar el número máximo de documentos devueltos y cómo crear un transformador de documentos para añadir o quitar campos de la respuesta antes de la serialización. También cubre conceptos como parámetros de configuración, excepciones Solr y la inicialización de componentes.
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
AI 101: An Introduction to the Basics and Impact of Artificial IntelligenceIndexBug
Imagine a world where machines not only perform tasks but also learn, adapt, and make decisions. This is the promise of Artificial Intelligence (AI), a technology that's not just enhancing our lives but revolutionizing entire industries.
HCL Notes and Domino License Cost Reduction in the World of DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
Taking AI to the Next Level in Manufacturing.pdfssuserfac0301
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
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.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/building-and-scaling-ai-applications-with-the-nx-ai-manager-a-presentation-from-network-optix/
Robin van Emden, Senior Director of Data Science at Network Optix, presents the “Building and Scaling AI Applications with the Nx AI Manager,” tutorial at the May 2024 Embedded Vision Summit.
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van Emden shows how Nx can simplify the developer’s life and facilitate a rapid transition from concept to production-ready applications.He provides valuable insights into developing scalable and efficient edge AI solutions, with a strong focus on practical implementation.
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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.
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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.
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* 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
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#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
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Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
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Spark is the widely used ETL tool for processing, indexing and ingesting data to serving stack for search. Milvus is the production-ready open-source vector database. In this talk we will show how to use Spark to process unstructured data to extract vector representations, and push the vectors to Milvus vector database for search serving.
Building Production Ready Search Pipelines with Spark and Milvus
Open source enterprise search and retrieval platform
1. Datum 21 augustus 2010
Enterprise Search
EAI
Semantic Web
Open Source
Search & Retrieval
Platform
Marc Teutelink
2. How Apache open source software is used
during the implementation of an
Enterprise Search and Retrieval Platform
(Lucene/SOLR, Nutch, Tika, ServiceMix/Camel, Felix/Ace)
3. Marc Teutelink
marc.teutelink@luminis.eu
@mteutelink
•Software architect at Luminis
•15+ years experience in software development; specialized in
Enterprise Search, Enterprise Application Integration and
Semantic Web technology
•Currently writing “Enterprise Search in Action” for Manning
(Mid-2011)
4. Agenda
•Enterprise Search
• What is Enterprise Search: Functions and features
• Challenges
• Logical Architecture
•Enterprise Search Solution
• Technology Stack
• Collection Process
• Publication Process
• Enricher framework
• Deployment
•Conclusion
5. What is Enterprise Search?
“Enterprise Search offers a solution for searching,
finding and presenting enterprise related information
in the larger sense of the word”
Enterprise search is all about searching through documents from
any type and format from any sources located anywhere with the
upmost flexibility
• Web search: limited to public documents on the web
• Desktop search: limited to private documents on the local machine
• Enterprise search: no limitations on document type and location
6. Enterprise Search
(features)
•Information Sources and Types
• Wide range of sources: local and remote filesystems, content repositories,
e-mail, databases, internet, intranet and extranet
• Type not limited: any type ranging from structured to unstructured data, text
and binary formats and compound formats (zip)
•Usage
• Not limited to interactive use automated business processes
•Security
• Integrations with enterprise security infrastructure
•User Interaction and personalization
• Identity enables more personalized search results
7. Enterprise Search
(features)
•Extended metadata
• More metadata better and more precise search results
• More control over schema (for example Dynamic Fields)
•Ranking
• More control over ranking: personalized ranking (group)
•Data extraction and derivation
• Extract data using various techniques: Xpath, Xquery
• Derive data: using external knowledge models: RDBMS, RDF Store, Web Services
• Conditional extraction & derivation
•Managing and monitoring
• On-the-fly management (JMX)
• Real time monitoring
8. Enterprise Search
(features)
•User Interfaces
• Web search
• All about selling advertisements to the mass
• Generalistic & minimalistic screens; focus on adds
• Enterprise search
• All about finding: rich navigation; focus on quick find
• Small targeted audience
• Specialized and customized screens (use of ontologies, taxonomies
and classifications)
• Use of identity (results customized to user) and web 2.0
• Grouping
• field collapsing, faceted search & clustering
9. Enterprise Search
(Challenges)
•Performance and scalability
•Rich functions and features
•Managebility
•Flexibility
•Easy maintenance
•Quick issue and problem solving
•Reduce total cost of ownerschip
10. Enterprise Search
(Challenges)
•Performance and scalability
•Rich functions and features
•Managebility
•Flexibility
•Easy maintenance
•Quick issue and problem solving
•Reduce total cost of ownerschip
Commercial Search Engines?
11. Enterprise Search
(Challenges)
•Performance and scalability
•Rich functions and features
•Managebility
•Flexibility
•Easy maintenance
•Quick issue and problem solving
•Reduce total cost of ownerschip
Apache Based (Open Source)
Search & Retrieval Platform
30. Luminis Enricher Framework
•Custom Enricher Framework
• Existing ESB & SOLR enricher capabilities not sufficient.
• Enriching = one or more actions (extraction, enhancing &
filtering) performed on documents with fields
• Same enricher to be used for:
• Collection process:
• Documents enriching, filtering & splitting
• Publication process:
• Search requests’first-components’ searchcomponent
• Search response’last-components’ searchcomponent
31. Luminis Enricher Framework
•Custom Enricher Framework
• Existing ESB & SOLR enricher capabilities not sufficient.
• Enriching = one or more actions (extraction, enhancing &
filtering) performed on documents with fields
• Same enricher to be used for:
• Collection process:
• Documents enriching, filtering & splitting
• Publication process:
• Search requests’first-components’ searchcomponent
• Search response’last-components’ searchcomponent
Content Indexer
Content Inbound
2
1
Documents
Message
N
D
Document
Messages
D D
Lucene/Solr
INDEX
SOLR Indexer
(Channel Adapter)
Lucene/SOLR
(SOLRJ)
D
SOLR Document
Message
Splitter
Channel
Content Validation Content Enrichment
Enricher
Content Filter
Content Enricher
Syntactic Validation
(Channel Purger)
Push Inbound
(Message Endpoint)
Semantic Validation
(Channel Purger)
Invalid Message
Channel
!
?
Invalid Message
ChannelChannel
32. Luminis Enricher Framework
•Custom Enricher Framework
• Existing ESB & SOLR enricher capabilities not sufficient.
• Enriching = one or more actions (extraction, enhancing &
filtering) performed on documents with fields
• Same enricher to be used for:
• Collection process:
• Documents enriching, filtering & splitting
• Publication process:
• Search requests’first-components’ searchcomponent
• Search response’last-components’ searchcomponent
Content Indexer
Content Inbound
2
1
Documents
Message
N
D
Document
Messages
D D
Lucene/Solr
INDEX
SOLR Indexer
(Channel Adapter)
Lucene/SOLR
(SOLRJ)
D
SOLR Document
Message
Splitter
Channel
Content Validation Content Enrichment
Enricher
Content Filter
Content Enricher
Syntactic Validation
(Channel Purger)
Push Inbound
(Message Endpoint)
Semantic Validation
(Channel Purger)
Invalid Message
Channel
!
?
Invalid Message
ChannelChannel
<<SearchHandler>>
RequestHandler
"first-components" "components" "last-components"
<<XML>>
Response
<<SearchComponent>>
query
<<SearchComponent>>
facet
<<SearchComponent>>
mlt
<<SearchComponent>>
highlight
<<SearchComponent>>
stats
<<SearchComponent>>
debug
<<SOLRQueryRequest>>
Query
<<XSLT>>
XML2HTML
<<QueryResponseWriter>>
XSLTResponseWriter
<<(X)HTML>>
Resultaat
33. Luminis Enricher Framework
(architecture)
•Pipe-and-filter architecture
• Documents flow through series of actions
• Output from one action is input to another action
• Fields from input document can be used in action’s clauses: values in
expressions filled by replacing velocity type patterns with field values
•Conditional flows supported
•Reuse of flows & Subflows supported
34. Luminis Enricher Framework
(architecture)
•Pipe-and-filter architecture
• Documents flow through series of actions
• Output from one action is input to another action
• Fields from input document can be used in action’s clauses: values in
expressions filled by replacing velocity type patterns with field values
•Conditional flows supported
•Reuse of flows & Subflows supported
Action
(select C where ${B})
Action
(remove A2)
Document
[[A1,A2],[B]]
Document
[[A1],[B]]
Document
[[A1],[B],[C1]]
If [B=3]
YES
Action
(select C where ${A})
Document
[[A1],[B],[C2]]
NO
35. Luminis Enricher Framework
(Configuration)
•Enricher flow and expression configuration via XML based DSL
• Conditional: if-then-else & switch-case-else (with regex support)
• Actions: Add & remove fields and field values using expressions
• Expression handlers currently supported:
• Field
• Function (execute methods via Java Reflection)
• HttpClient (retrieve content by URL described by field values)
• Xslt, Xpath, Xquery (external XML databases)
• JDBC
• SparQL (OpenRDF)
• Apache Lucene/Solr
• Apache Tika (Meta and Text extraction)
40. Luminis Enricher Framework
(Technology)
•Enricher and expresion handlers are Java based OSGi
services:
• Hot pluggable and updatable
• Flow and expression configuration changes no restart
• Extendible: New expression handlers immediatly available in
actions after installing OSGi bundle
•Runs in Apache Felix
• Collection Process: ServiceMix contains OSGi container
• Publication Process: Custom OSGi loader for Lucene/Solr
•Centralized & transactional provisioning (Apache Ace)
‑ Components & Configuration