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Building Mashups by Demonstration

Building Mashups by Demonstration. ACM Transactions on the Web, Vol 5. No.3, Article 16, July 2011. Research By Rattan Tuchinda,Craig A. Knoblock, Pedro Szekely Presenter : Preeti Loomba CSU Id : 2438925. Mashup Overview.

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Building Mashups by Demonstration

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  1. Building Mashups by Demonstration ACM Transactions on the Web, Vol 5. No.3, Article 16, July 2011 Research By Rattan Tuchinda,Craig A. Knoblock, Pedro Szekely Presenter : Preeti Loomba CSU Id : 2438925

  2. Mashup Overview Mashup describes a web application that integrates data from multiple web sources to provide a unique service.

  3. Current Solutions • Widget Paradigm • Current Solutions involve selecting, customizing, and connecting widgets together • Disadvantages • As number of widgets gets large, locating the right widget becomes confusing and time consuming • Connecting widgets required understanding of programming concepts

  4. Yahoo Pipes

  5. Microsoft Popfly

  6. Goal Create a mashup building framework where an average Internet user with no programming experience can build Mashups easily.

  7. Problems • Data Retrieval • Source Modeling • Data Cleaning • Data Integration • Data Display

  8. Mashup Categorization • One Simple Source • Combining data points from two or more separate sources • One source with a form • Combining two or more sources with a database join

  9. Top Mashup Categories

  10. Key Ideas • Focus on data, not the operation • Leverage existing databases • Consolidate rather than divide and conquer

  11. Karma Interface

  12. Data Retrieval

  13. Data Retrieval

  14. Source Modeling • Karma compares extracted data with existing data in its repository • Automatically populates some attributes • User specifying the correct attribute • Users search existing attributes in data repository

  15. Data Cleaning • User selects clean data tab • User specifies what data needs to be cleaned • User specifies cleaned result • Karma will try to induce the cleaning transformation

  16. Cleaning Example

  17. Data Integration • Karma analyzes attributes and data • Karma determines joins between data in table and data in the repository • Karma suggests existing data sources in repository that can be linked to the new data in the table

  18. Data Retrieval • DOM tree as basic structure for extraction • Organization of HTML tags in the web page • Positioning of nodes used for data extraction

  19. Data Retrieval

  20. Related Works- Widget Approach • Yahoo Pipes • Microsoft’s Popfly • Marmite • IBM’s QED wiki • Bungee Labs • Proto Software

  21. Related Works – Other approaches • Simile • Potluck • Intel’s MashMaker • Mario • Cards • Google MyMaps

  22. Karma Advantages • An end-to-end approach • A consistent paradigm • Wide coverage

  23. Overall Performance Comparisons

  24. Future Works • Customizing display by Examples • Recovering from Errors • Source Quality • Support for Advanced Users • Data Cleaning Transformations

  25. Questions ?

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