Studying the Wikipedia Hyperlink Graph for Relatedness and Disambiguation

Agirre, Eneko; Barrena, Ander; Soroa, Aitor

doi:10.48550/arxiv.1503.01655

Cited by 1 publication

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“…Regarding random walk based embeddings, we decided to apply them to the Wikipedia graph described in (Agirre, Barrena, and Soroa 2015) which is publicly available. V consists of all Wikipedia pages except redirect, disambiguation and category pages.…”

Section: Additional Word Representationsmentioning

confidence: 99%

Single or Multiple? Combining Word Representations Independently Learned from Text and WordNet

Goikoetxea

Agirre

Soroa

2016

AAAI

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Text and Knowledge Bases are complementary sources of information. Given the success of distributed word representations learned from text, several techniques to infuse additional information from sources like WordNet into word representations have been proposed. In this paper, we follow an alternative route. We learn word representations from text and WordNet independently, and then explore simple and sophisticated methods to combine them. The combined representations are applied to an extensive set of datasets on word similarity and relatedness. Simple combination methods happen to perform better that more complex methods like CCA or retrofitting, showing that, in the case of WordNet, learning word representations separately is preferable to learning one single representation space or adding WordNet information directly. A key factor, which we illustrate with examples, is that the WordNet-based representations captures similarity relations encoded in WordNet better than retrofitting. In addition, we show that the average of the similarities from six word representations yields results beyond the state-of-the-art in several datasets, reinforcing the opportunities to explore further combination techniques.

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Section: Additional Word Representationsmentioning

confidence: 99%