Intro: The OpenCalais Web Service automatically creates rich semantic metadata for the content you submit – in well under a second. Using natural language processing (NLP), machine learning and other methods, Calais analyzes your document and finds the entities within it. But, Calais goes well beyond classic entity identification and returns the facts and events hidden within your text as well.
Wednesday, 28 March 2012
Calais
Link: http://www.opencalais.com/
Labels:
information extraction,
machine learning,
NLP,
toolkits
Downloading full CiteSeerX data
Just saw this link and found it very interesting.
Link: http://b010.blogspot.com/2008/11/downloading-full-citeseerx-data.html
I copy here for backup (to avoid if the original link dies).
Steps for downloading the full dataset from CiteSeerX:
Thanks the author for that.
--
Cheers,
Vu
Link: http://b010.blogspot.com/2008/11/downloading-full-citeseerx-data.html
I copy here for backup (to avoid if the original link dies).
Steps for downloading the full dataset from CiteSeerX:
- Download and extract the "Demo" from http://www.oclc.org/research/software/oai/harvester.htm
- Go to the directory of the extracted files, type the following command to download the full dataset of CiteSeerX to the file "citeseerx_alldata.xml"java -classpath .;oaiharvester.jar;xerces.jar org.acme.oai.OAIReaderRawDump http://citeseerx.ist.psu.edu/oai2 -o citeseerx_alldata.xml
Thanks the author for that.
--
Cheers,
Vu
Tuesday, 27 March 2012
Preference Learning
Introduction: http://www.ke.tu-darmstadt.de/publications/papers/PLBook-Introduction.pdf
Applications to NLP???
Applications to NLP???
Labels:
learning to rank,
links,
machine learning,
NLP,
preference learning,
technology
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