A New Approach for Improving Cross-Document Knowledge Discovery Using Wikipedia

From Wikipedia Quality
Jump to: navigation, search


A New Approach for Improving Cross-Document Knowledge Discovery Using Wikipedia
Authors
Peng Yan
Wei Jin
Publication date
2013
DOI
10.1007/978-3-642-38824-8_27
Links
Original Preprint

A New Approach for Improving Cross-Document Knowledge Discovery Using Wikipedia - scientific work related to Wikipedia quality published in 2013, written by Peng Yan and Wei Jin.

Overview

In this paper, authors present a new model that incorporates the extensive knowledge derived from Wikipedia for cross-document knowledge discovery. The model proposed here is based on previously introduced Concept Chain Queries (CCQ) which is a special case of text mining focusing on detecting semantic relationships between two concepts across multiple documents. Authors attempt to overcome the limitations of CCQ by building a semantic kernel for concept closeness computing to complement existing knowledge in text corpus. The experimental evaluation demonstrates that the kernel-based approach outperforms in ranking important chains retrieved in the search results.

Embed

Wikipedia Quality

Peng, Yan; Wei, Jin. (2013). "[[A New Approach for Improving Cross-Document Knowledge Discovery Using Wikipedia]]". Springer, Berlin, Heidelberg. DOI: 10.1007/978-3-642-38824-8_27.

English Wikipedia

{{cite journal |last1=Peng |first1=Yan |last2=Wei |first2=Jin |title=A New Approach for Improving Cross-Document Knowledge Discovery Using Wikipedia |date=2013 |doi=10.1007/978-3-642-38824-8_27 |url=https://wikipediaquality.com/wiki/A_New_Approach_for_Improving_Cross-Document_Knowledge_Discovery_Using_Wikipedia |journal=Springer, Berlin, Heidelberg}}

HTML

Peng, Yan; Wei, Jin. (2013). &quot;<a href="https://wikipediaquality.com/wiki/A_New_Approach_for_Improving_Cross-Document_Knowledge_Discovery_Using_Wikipedia">A New Approach for Improving Cross-Document Knowledge Discovery Using Wikipedia</a>&quot;. Springer, Berlin, Heidelberg. DOI: 10.1007/978-3-642-38824-8_27.