Ontos Solutions for Semantic Web: Text Mining, Navigation and Analytics

2007 ◽  
pp. 11-27
Author(s):  
Vladimir Khoroshevsky ◽  
Irina Efimenko ◽  
Grigory Drobyazko ◽  
Polina Kananykina ◽  
Victor Klintsov ◽  
...  
Keyword(s):  
Text Mining ◽  
Semantic Web ◽  
Web Text Mining

Text Mining for the Semantic Web

2017 ◽  
pp. 1262-1263
Author(s):  
Marko Grobelnik ◽  
Dunja Mladenić ◽  
Michael Witbrock
Keyword(s):  
Text Mining ◽  
Semantic Web

Web Text Mining

2016 ◽  
Author(s):  
Ricardo Baeza-Yates ◽  
Roi Blanco ◽  
Malú Castellanos
Keyword(s):  
Social Media ◽  
Text Mining ◽  
Sentiment Analysis ◽  
Web Search ◽  
Internet Users ◽  
Entity Retrieval ◽  
Web Text Mining ◽  
Text Content ◽  
The Web

Web search has become a ubiquitous commodity for Internet users. This fact puts a large number of documents with plenty of text content at our fingertips. To make good use of this data, we need to mine web text. This triggers the two problems covered here: sentiment analysis and entity retrieval in the context of the Web. The first problem answers the question of what people think about a given product or a topic, in particular sentiment analysis in social media. The second problem addresses the issue of solving certain enquiries precisely by returning a particular object: for instance, where the next concert of my favourite band will be or who the best cooks are in a particular region. Where to find these objects and how to retrieve, rank, and display them are tasks related to the entity retrieval problem.

scholarly journals Text-Mining-Methoden im Semantic Web

2010 ◽  
Vol 47 (1) ◽  
pp. 35-46
Author(s):  
Gerold Schneider ◽  
Heinrich Zimmermann
Keyword(s):  
Text Mining ◽  
Semantic Web
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