Difference between revisions of "Building Semantic Kernels for Cross-Document Knowledge Discovery Using Wikipedia"
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| − | '''Building Semantic Kernels for Cross-Document Knowledge Discovery Using Wikipedia''' - scientific work related to Wikipedia quality published in 2017, written by Peng Yan and Wei Jin. | + | '''Building Semantic Kernels for Cross-Document Knowledge Discovery Using Wikipedia''' - scientific work related to [[Wikipedia quality]] published in 2017, written by [[Peng Yan]] and [[Wei Jin]]. |
== Overview == | == Overview == | ||
| − | Research into text mining has progressed over the past decade. One of the main challenges now is gauging the difficulty of taking advantage of outside knowledge in the discovery process. In this work, to address the limitations of the traditional bag-of- words model and expand the search scope beyond the document collections at hand, authors present a new text mining approach incorporating Wikipedia as the background knowledge. Various semantic kernels are built out of the extensive knowledge derived from Wikipedia and applied to the search scenario of detecting potential semantic relationships between topics. Authors demonstrate the effectiveness of approach through comparing with competitive baselines, as well as alternative solutions where only part of Wikipedia resources (e.g., the Wiki-article contents or the associated Wiki-categories) is considered. | + | Research into text mining has progressed over the past decade. One of the main challenges now is gauging the difficulty of taking advantage of outside knowledge in the discovery process. In this work, to address the limitations of the traditional bag-of- words model and expand the search scope beyond the document collections at hand, authors present a new text mining approach incorporating [[Wikipedia]] as the background knowledge. Various semantic kernels are built out of the extensive knowledge derived from Wikipedia and applied to the search scenario of detecting potential semantic relationships between topics. Authors demonstrate the effectiveness of approach through comparing with competitive baselines, as well as alternative solutions where only part of Wikipedia resources (e.g., the Wiki-article contents or the associated Wiki-[[categories]]) is considered. |
Revision as of 10:17, 9 July 2019
Building Semantic Kernels for Cross-Document Knowledge Discovery Using Wikipedia - scientific work related to Wikipedia quality published in 2017, written by Peng Yan and Wei Jin.
Overview
Research into text mining has progressed over the past decade. One of the main challenges now is gauging the difficulty of taking advantage of outside knowledge in the discovery process. In this work, to address the limitations of the traditional bag-of- words model and expand the search scope beyond the document collections at hand, authors present a new text mining approach incorporating Wikipedia as the background knowledge. Various semantic kernels are built out of the extensive knowledge derived from Wikipedia and applied to the search scenario of detecting potential semantic relationships between topics. Authors demonstrate the effectiveness of approach through comparing with competitive baselines, as well as alternative solutions where only part of Wikipedia resources (e.g., the Wiki-article contents or the associated Wiki-categories) is considered.
