CIKM Conference on information and knowledge management
copernicus.eu/it/info | climate.copernicus
https://blender.cs.illinois.edu/publications/
Tutorial at the 52nd Annual Meeting of the Association for Computational Linguistics (ACL2014)
Contextual disambiguation and grounding of concepts and entities in natural language text are essential to moving forward in many natural language understanding related tasks and are fundamental to many applications. The Wikification task (Bunescu and Pasca, 2006; Mihalcea and Csomai, 2007; Ratinov et al.,2011) aims at automatically identifying concept mentions appearing in a text document and link it to (or “ground it in”) a concept referent in a knowledge base (KB) (e.g., Wikipedia). For example, consider the sentence, "The Times report on Blumental (D) has the potential to fundamentally reshape the contest in the Nutmeg State.", a Wikifier should identify the key entities and concepts (Times, Blumental, D and the Nutmeg State), and disambiguate them by mapping them to an encyclopedic resource revealing, for example, that “D” here represents the Democratic Party, and that “the Nutmeg State” refers Connecticut.
The resulting link detector and disambiguator performs very well,
with recall and precision of almost 75%. This performance is constant
whether the system is evaluated on Wikipedia articles or "real world"
documents.
This work has implications far beyond enriching documents with
explanatory links. It can provide structured knowledge about any
unstructured fragment of text. Any task that is currently addressed with
bags of words - indexing, clustering, retrieval, and summarization to
name a few - could use the techniques described here to draw on a vast
network of concepts and semantics
http://videolectures.net/cikm08_milne_ltlww/
http://community.nzdl.org/wikification/about.html
https://en.wikipedia.org/wiki/Weka_(machine_learning)
https://www.classcentral.com/report/data-mining-weka-waikato/
https://en.wikipedia.org/wiki/Orange_(software)
use of Wikipedia for
how the two methods can be combined into a system able to automatically enrich a text with links to encyclopedic knowledge.
Given an input document, the system identifies the important concepts in the text and automatically links these concepts to the corresponding Wikipedia pages. Evaluations of the system show that the automatic annotations are reliable and hardly distinguishable from manual annotations.
2007-2010 ebiquity.umbc.edu/Wikitology
2007 ebiquity.umbc.edu/Wikipedia-as-an-ontology