Difference between revisions of "Entity Extraction, Linking, Classification, and Tagging for Social Media: a Wikipedia-Based Approach"
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| − | '''Entity Extraction, Linking, Classification, and Tagging for Social Media: a Wikipedia-Based Approach''' - scientific work related to Wikipedia quality published in 2013, written by Abhishek Gattani, Digvijay S. Lamba, Nikesh Garera, Mitul Tiwari, Xiaoyong Chai, Sanjib Das, Sri Subramaniam, Anand Rajaraman, Venky Harinarayan and AnHai Doan. | + | '''Entity Extraction, Linking, Classification, and Tagging for Social Media: a Wikipedia-Based Approach''' - scientific work related to [[Wikipedia quality]] published in 2013, written by [[Abhishek Gattani]], [[Digvijay S. Lamba]], [[Nikesh Garera]], [[Mitul Tiwari]], [[Xiaoyong Chai]], [[Sanjib Das]], [[Sri Subramaniam]], [[Anand Rajaraman]], [[Venky Harinarayan]] and [[AnHai Doan]]. |
== Overview == | == Overview == | ||
| − | Many applications that process social data, such as tweets, must extract entities from tweets (e.g., "Obama" and "Hawaii" in "Obama went to Hawaii"), link them to entities in a knowledge base (e.g., Wikipedia), classify tweets into a set of predefined topics, and assign descriptive tags to tweets. Few solutions exist today to solve these problems for social data, and they are limited in important ways. Further, even though several industrial systems such as OpenCalais have been deployed to solve these problems for text data, little if any has been published about them, and it is unclear if any of the systems has been tailored for social media. | + | Many applications that process social data, such as tweets, must extract entities from tweets (e.g., "Obama" and "Hawaii" in "Obama went to Hawaii"), link them to entities in a knowledge base (e.g., [[Wikipedia]]), classify tweets into a set of predefined topics, and assign descriptive tags to tweets. Few solutions exist today to solve these problems for social data, and they are limited in important ways. Further, even though several industrial systems such as OpenCalais have been deployed to solve these problems for text data, little if any has been published about them, and it is unclear if any of the systems has been tailored for social media. |
Revision as of 21:49, 30 August 2019
Entity Extraction, Linking, Classification, and Tagging for Social Media: a Wikipedia-Based Approach - scientific work related to Wikipedia quality published in 2013, written by Abhishek Gattani, Digvijay S. Lamba, Nikesh Garera, Mitul Tiwari, Xiaoyong Chai, Sanjib Das, Sri Subramaniam, Anand Rajaraman, Venky Harinarayan and AnHai Doan.
Overview
Many applications that process social data, such as tweets, must extract entities from tweets (e.g., "Obama" and "Hawaii" in "Obama went to Hawaii"), link them to entities in a knowledge base (e.g., Wikipedia), classify tweets into a set of predefined topics, and assign descriptive tags to tweets. Few solutions exist today to solve these problems for social data, and they are limited in important ways. Further, even though several industrial systems such as OpenCalais have been deployed to solve these problems for text data, little if any has been published about them, and it is unclear if any of the systems has been tailored for social media.
