The document contains annotations of a form on a web page. It describes the structure of the form using elements like e_489_tbody and relationships like group between elements. It also annotates labels associated with form controls.
The document discusses techniques for extracting data from web pages. It describes approaches using visual information, ontologies, HTML parsing, and regular expressions. Example systems described include ViDE, ODE, FiVaTech, EXALG and DELA. The document also discusses challenges such as handling multiple query results, matching data to labels, resolving labeling conflicts, and extracting both mandatory and optional data items.
Mining Uncertain Data (Sebastiaan van Schaaik)timfu
This document summarizes an upcoming seminar on mining frequent patterns and association rules from uncertain data. It introduces the concepts of frequent patterns, association rules, support and confidence as measures of "interestingness." It describes the classic Apriori algorithm for mining frequent itemsets and rules from certain data. It then discusses challenges introduced by uncertain data, such as modeling item probabilities and possible worlds. Finally, it outlines approaches that have been developed to mine uncertain data, including U-Apriori, p-Apriori, UF-growth, and UFP-tree.
The document discusses the European Research Council's DIADEM project, which aims to develop an automated data extraction methodology. The DIADEM 0.1 prototype promises fact finders for structural information, entities and relationships, as well as tools for classifying web pages, analyzing forms and results pages, and generating data extraction programs. The January milestone focuses on developing the necessary infrastructure, natural language processing capabilities, machine learning models, and tools for form analysis, results page analysis, PDF processing, navigation, and program generation.
This document provides a summary of three articles on ontology-based information extraction and the Sophie system. It describes key concepts in OBIE like using ontologies to guide information extraction and presenting extracted information using ontologies. It also summarizes the Yago ontology which extracts information from Wikipedia and WordNet to build a large knowledge base and the Sophie system which aims to incrementally expand ontologies by leveraging existing knowledge to generate and evaluate new hypotheses.
Machine Learning in DIADEM (Andrey Kravchenko)timfu
The paper proposes classifying web page elements based on their visual features in a DOM tree. It takes a two-phase approach: 1) segment the page into blocks and 2) classify each block using visual features like font, size, color as input to a decision tree classifier. It evaluates on news pages, achieving average F1 scores for coarse labels but lower F1 for fine-grained labels. The approach segments the page then classifies elements in two separate steps using visual features derived from the DOM tree.
Reuters: Pictures of the Year 2016 (Part 2)maditabalnco
This document contains 20 photos from news events around the world between January and November 2016. The photos show international events like the US presidential election, the conflict in Ukraine, the migrant crisis in Europe, the Rio Olympics, and more. They also depict human interest stories and natural phenomena from various countries.
The Six Highest Performing B2B Blog Post FormatsBarry Feldman
If your B2B blogging goals include earning social media shares and backlinks to boost your search rankings, this infographic lists the size best approaches.
1) The document discusses the opportunity for technology to improve organizational efficiency and transition economies into a "smart and clean world."
2) It argues that aggregate efficiency has stalled at around 22% for 30 years due to limitations of the Second Industrial Revolution, but that digitizing transport, energy, and communication through technologies like blockchain can help manage resources and increase efficiency.
3) Technologies like precision agriculture, cloud computing, robotics, and autonomous vehicles may allow for "dematerialization" and do more with fewer physical resources through effects like reduced waste and need for transportation/logistics infrastructure.
The document discusses techniques for extracting data from web pages. It describes approaches using visual information, ontologies, HTML parsing, and regular expressions. Example systems described include ViDE, ODE, FiVaTech, EXALG and DELA. The document also discusses challenges such as handling multiple query results, matching data to labels, resolving labeling conflicts, and extracting both mandatory and optional data items.
Mining Uncertain Data (Sebastiaan van Schaaik)timfu
This document summarizes an upcoming seminar on mining frequent patterns and association rules from uncertain data. It introduces the concepts of frequent patterns, association rules, support and confidence as measures of "interestingness." It describes the classic Apriori algorithm for mining frequent itemsets and rules from certain data. It then discusses challenges introduced by uncertain data, such as modeling item probabilities and possible worlds. Finally, it outlines approaches that have been developed to mine uncertain data, including U-Apriori, p-Apriori, UF-growth, and UFP-tree.
The document discusses the European Research Council's DIADEM project, which aims to develop an automated data extraction methodology. The DIADEM 0.1 prototype promises fact finders for structural information, entities and relationships, as well as tools for classifying web pages, analyzing forms and results pages, and generating data extraction programs. The January milestone focuses on developing the necessary infrastructure, natural language processing capabilities, machine learning models, and tools for form analysis, results page analysis, PDF processing, navigation, and program generation.
This document provides a summary of three articles on ontology-based information extraction and the Sophie system. It describes key concepts in OBIE like using ontologies to guide information extraction and presenting extracted information using ontologies. It also summarizes the Yago ontology which extracts information from Wikipedia and WordNet to build a large knowledge base and the Sophie system which aims to incrementally expand ontologies by leveraging existing knowledge to generate and evaluate new hypotheses.
Machine Learning in DIADEM (Andrey Kravchenko)timfu
The paper proposes classifying web page elements based on their visual features in a DOM tree. It takes a two-phase approach: 1) segment the page into blocks and 2) classify each block using visual features like font, size, color as input to a decision tree classifier. It evaluates on news pages, achieving average F1 scores for coarse labels but lower F1 for fine-grained labels. The approach segments the page then classifies elements in two separate steps using visual features derived from the DOM tree.
Reuters: Pictures of the Year 2016 (Part 2)maditabalnco
This document contains 20 photos from news events around the world between January and November 2016. The photos show international events like the US presidential election, the conflict in Ukraine, the migrant crisis in Europe, the Rio Olympics, and more. They also depict human interest stories and natural phenomena from various countries.
The Six Highest Performing B2B Blog Post FormatsBarry Feldman
If your B2B blogging goals include earning social media shares and backlinks to boost your search rankings, this infographic lists the size best approaches.
1) The document discusses the opportunity for technology to improve organizational efficiency and transition economies into a "smart and clean world."
2) It argues that aggregate efficiency has stalled at around 22% for 30 years due to limitations of the Second Industrial Revolution, but that digitizing transport, energy, and communication through technologies like blockchain can help manage resources and increase efficiency.
3) Technologies like precision agriculture, cloud computing, robotics, and autonomous vehicles may allow for "dematerialization" and do more with fewer physical resources through effects like reduced waste and need for transportation/logistics infrastructure.
This document lists and briefly describes several useful WordPress functions:
- It lists over 20 escaping functions used to sanitize output like esc_sql(), esc_url(), and esc_html().
- It discusses utility functions like __return_false() and __return_empty_array() used for filters.
- It mentions functions for specific tasks like wp_is_mobile() to check mobile devices, wp_no_robots() to add noindex meta tags, and wp_parse_args() to merge arrays.
- It covers functions for AJAX responses like wp_send_json_success() and functions to help navigate the WordPress codebase like wp_list_pluck().
Forecasting airline passengers with designer machine learningAlexander Backus
The ability to accurately forecast the amount of passengers that will board a particular flight is crucial for airline operations. But how do we design a machine learning algorithm for this use case and in what ways can we improve it? In this talk, we start with a simple linear model, evolving to increasingly complex deep learning neural network architectures.
Rugalytics is a Ruby library that allows users to easily access and summarize Google Analytics reports and data. It uses a technique called "morphing" to dynamically generate Ruby methods and classes based on the structure and attributes of the Analytics reports. This allows report data to be accessed and manipulated as normal Ruby objects and attributes. The library includes methods to retrieve report data via the Analytics API in various formats including JSON. It also includes a basic web server to demo serving report data via API endpoints.
This document discusses error handling for an MKT_ETL_Load job. It analyzes how structural changes in fields between the MSBI and EBS sources cause failures, mainly due to NULLs, duplicates and invalid date formats. It also provides examples of four cases where mismatches between the source and target schemas could cause failures: 1) NULL values, 2) data types, 3) primary keys, 4) date formatting. The document recommends implementing error handling by adding a data conversion task before the target to redirect invalid records to a secondary destination like a flat file or table.
Tutorial - Learn SQL with Live Online DatabaseDBrow Adm
The document provides an overview of SQL queries that can be practiced on a sample eCommerce database using an online tool. It covers basic queries including selecting columns, filtering rows, sorting results, joining tables, aggregate functions and more advanced topics such as subqueries, outer joins and regular expressions. Each example is accompanied by a link to test the query directly and view the output. The goal is to help users test and solidify their understanding of SQL.
This document provides a high-level summary of 12 new features in Oracle Database 12c, including:
1. Data redaction for masking sensitive data.
2. Temporal validity for querying data that was valid during a specific time period.
3. SQL text expansion for programmatically expanding SQL statements.
4. Increased size limits for VARCHAR2, NVARCHAR2 and RAW data types up to 32KB.
5. Easy top-N and pagination queries using new row limiting clauses.
The document discusses migrating from the HTML::Template template engine to Template Toolkit. It describes some of the key differences between the two engines and the process involved in converting templates from one to the other. Tips are provided for the conversion including avoiding reserved keywords and variable naming conventions to ensure a smooth migration.
The document discusses the differences in performance between Objective-C and Swift. Objective-C is slower than Swift because it is dynamically typed and relies on the objc_msgSend function at runtime to determine method implementations, which has higher overhead than Swift's static compilation to native code. Swift avoids the overhead of objc_msgSend by compiling the code directly to native functions, making method calls as fast as in other compiled languages like C++.
The document contains code snippets from a Perl module related to querying a database table. It includes SQL queries to count the number of rows in a series_comment table where the series_id and is_public columns meet certain criteria. It also contains Perl code implementing a select_query method that constructs a SQL query from a table name, fields, and where conditions.
This document discusses Brick, a Perl module for validating data against business rules. Brick allows separating validation logic from code by defining rules as closures. Rules can be composed together to validate complex relationships. Validation results are returned as objects containing labels, methods, success indicators, and any errors, making issues easy to identify. The document provides examples of defining validation profiles and routines with Brick and using the results.
This document lists and briefly describes several useful WordPress functions:
- It lists over 20 escaping functions used to sanitize output like esc_sql(), esc_url(), and esc_html().
- It discusses utility functions like __return_false() and __return_empty_array() used for filters.
- It mentions functions for specific tasks like wp_is_mobile() to check mobile devices, wp_no_robots() to add noindex meta tags, and wp_parse_args() to merge arrays.
- It covers functions for AJAX responses like wp_send_json_success() and functions to help navigate the WordPress codebase like wp_list_pluck().
Forecasting airline passengers with designer machine learningAlexander Backus
The ability to accurately forecast the amount of passengers that will board a particular flight is crucial for airline operations. But how do we design a machine learning algorithm for this use case and in what ways can we improve it? In this talk, we start with a simple linear model, evolving to increasingly complex deep learning neural network architectures.
Rugalytics is a Ruby library that allows users to easily access and summarize Google Analytics reports and data. It uses a technique called "morphing" to dynamically generate Ruby methods and classes based on the structure and attributes of the Analytics reports. This allows report data to be accessed and manipulated as normal Ruby objects and attributes. The library includes methods to retrieve report data via the Analytics API in various formats including JSON. It also includes a basic web server to demo serving report data via API endpoints.
This document discusses error handling for an MKT_ETL_Load job. It analyzes how structural changes in fields between the MSBI and EBS sources cause failures, mainly due to NULLs, duplicates and invalid date formats. It also provides examples of four cases where mismatches between the source and target schemas could cause failures: 1) NULL values, 2) data types, 3) primary keys, 4) date formatting. The document recommends implementing error handling by adding a data conversion task before the target to redirect invalid records to a secondary destination like a flat file or table.
Tutorial - Learn SQL with Live Online DatabaseDBrow Adm
The document provides an overview of SQL queries that can be practiced on a sample eCommerce database using an online tool. It covers basic queries including selecting columns, filtering rows, sorting results, joining tables, aggregate functions and more advanced topics such as subqueries, outer joins and regular expressions. Each example is accompanied by a link to test the query directly and view the output. The goal is to help users test and solidify their understanding of SQL.
This document provides a high-level summary of 12 new features in Oracle Database 12c, including:
1. Data redaction for masking sensitive data.
2. Temporal validity for querying data that was valid during a specific time period.
3. SQL text expansion for programmatically expanding SQL statements.
4. Increased size limits for VARCHAR2, NVARCHAR2 and RAW data types up to 32KB.
5. Easy top-N and pagination queries using new row limiting clauses.
The document discusses migrating from the HTML::Template template engine to Template Toolkit. It describes some of the key differences between the two engines and the process involved in converting templates from one to the other. Tips are provided for the conversion including avoiding reserved keywords and variable naming conventions to ensure a smooth migration.
The document discusses the differences in performance between Objective-C and Swift. Objective-C is slower than Swift because it is dynamically typed and relies on the objc_msgSend function at runtime to determine method implementations, which has higher overhead than Swift's static compilation to native code. Swift avoids the overhead of objc_msgSend by compiling the code directly to native functions, making method calls as fast as in other compiled languages like C++.
The document contains code snippets from a Perl module related to querying a database table. It includes SQL queries to count the number of rows in a series_comment table where the series_id and is_public columns meet certain criteria. It also contains Perl code implementing a select_query method that constructs a SQL query from a table name, fields, and where conditions.
This document discusses Brick, a Perl module for validating data against business rules. Brick allows separating validation logic from code by defining rules as closures. Rules can be composed together to validate complex relationships. Validation results are returned as objects containing labels, methods, success indicators, and any errors, making issues easy to identify. The document provides examples of defining validation profiles and routines with Brick and using the results.