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Copyright © 2014, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. In the era of Big Data, knowledge integration is key for tasks such as social media aggregation, opinion mining, and cyber-issue detection. The integration of different kinds of knowledge coming from multiple sources, however, is often a problematic issue as it either requires a lot of manual effort in defining aggregation rules or suffers from noise generated by automatic integration techniques. In this work, we propose a method based on conceptual primitives for efficiently integrating pieces of knowledge coming from different common and common-sense resources, which we test in the field of concept-level sentiment analysis.

Type

Conference paper

Publication Date

01/01/2014

Pages

170 - 173