PPT-Learning-based Entity Resolution

Author : tatiana-dople | Published Date : 2017-05-13

with MapReduce Lars Kolb Hanna Köpcke Andreas Thor Erhard Rahm Database Group Leipzig httpdbsunileipzigde Glasgow CloudDB 2011 Identification of semantically

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Learning-based Entity Resolution: Transcript

with MapReduce Lars Kolb Hanna Köpcke Andreas Thor Erhard Rahm Database Group Leipzig httpdbsunileipzigde Glasgow CloudDB 2011 Identification of semantically equivalent entities. WHEREAS the City of Vestavia Hills provides em ergency services and public work services to its citizens the cost of which is funded through city revenues and WHEREAS some subdivision construction and devel opment outside the city does not conform Joe Meehean. 1. Entity Relationship Model. Entity type. an object (noun). e.g., student. attributes (e.g., last name). Relationship. association between entity types. bidirectional relationship between entities. Martin . Ja. čala and . Jozef Tvarožek. Špindlerův. . Mlýn. , Czech Republic. January 23, 2012. Slovak University of Technology. Bratislava, Slovakia. Problem. Given an input text, detect and decide on correct meaning of named entites. Shyam Pather (spather@microsoft.com). Development Manager. Microsoft. Session Code: DTL402. Session Objectives And Takeaways. Discuss the Entity Framework. Historic Perspective. Improvements. in Visual Studio 2010. Working with ADEConnect . &. Entity Admin Portal. ADEConnect. Agenda. ADEConnect overview. Entity Administrator Functions. Adding a new user. Adding users to programs within ADEConnect. Adding other Entity Administrators. Real-Time Exploitation of Linked Data. University of Crete. Computer Science . Department. Greece . Foundation for Research and Technology – Hellas (FORTH). Institute of Computer Science (ICS). Information Systems Laboratory (ISL). Rowan Miller. DEV-B417. Setting expectations. This is a level 400 session. Assumes prior knowledge of data access and EF. For getting started with EF. http://bit.ly/EFTechEd2014. Agenda. Where are we at?. 1. Enhanced-ER (EER) Model Concepts. Includes all modeling concepts of basic ER . Additional concepts: subclasses/. superclasses. , specialization/generalization, categories, attribute inheritance. Nobal B. Niraula. March 26, 2014. Advisor: Dr. . Vasile. . Rus. Anaphora in Etymology. Ancient Greek : Anaphora = . anajora. (. Anajora. ). ana. (. Ana) . . . back in an upward direction. jora. 2. Outline. Data Modeling: Big picture. E-R Model. Attributes. types. Relationships. connectivity, cardinality. strength, participation, degree. Entities. composite entity. supertype/subtype. Table Normalization. Sam Smith, FSB Secretariat. Meeting of the CEPS Task Force. Brussels,11 December 2015. TLAC: overview and objectives. Calibration . set at. . 16% RWA and 6% LR from 1 January 2019, 18% RWA and 6.75% LR from 1 January 2022. COMMON RESOLUTION OPTIONS AND RECENT NIGERIA BANK RESOLUTION EXPERIENCE Adeleke A. A. Director Asset Management Department, NDIC. Common Resolution Options & Recent Nigeria Bank Resolution Experience. Pankaj. . Vanwari. . Under guidance of . Dr. S. . Sudarshan. . Overview of Presentation. Introduction to Entity Queries. Keyword search on structured data. Querying over unstructured data. Entity queries using ontology based extraction. Queries . Using . an . Extended . Graph Model. Ankur. . Agrawal. . S. Sudarshan . Ajitav. . Sahoo. . Adil. . Sandalwala. . Prashant. . Jaiswal. . IIT . Bombay. History of Keyword Queries.

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