The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
A comparison of LSA, wordNet and PMI-IR for predicting user click behavior
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Verbosity: a game for collecting common-sense facts
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
The Google Similarity Distance
IEEE Transactions on Knowledge and Data Engineering
Tree-Traversing Ant Algorithm for term clustering based on featureless similarities
Data Mining and Knowledge Discovery
An Introduction to Kolmogorov Complexity and Its Applications
An Introduction to Kolmogorov Complexity and Its Applications
WikiRelate! computing semantic relatedness using wikipedia
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Cheap and fast---but is it good?: evaluating non-expert annotations for natural language tasks
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Computing semantic relatedness using Wikipedia-based explicit semantic analysis
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Non-deterministic policies in Markovian decision processes
Journal of Artificial Intelligence Research
Human wayfinding in information networks
Proceedings of the 21st international conference on World Wide Web
Computing semantic relatedness from human navigational paths on Wikipedia
Proceedings of the 22nd international conference on World Wide Web companion
The last click: why users give up information network navigation
Proceedings of the 7th ACM international conference on Web search and data mining
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Computing the semantic distance between realworld concepts is crucial for many intelligent applications. We present a novel method that leverages data from 'Wikispeedia', an online game played on Wikipedia; players have to reach an article from another, unrelated article, only by clicking links in the articles encountered. In order to automatically infer semantic distances between everyday concepts, our method effectively extracts the common sense displayed by humans during play, and is thus more desirable, from a cognitive point of view, than purely corpus-based methods. We show that our method significantly outperforms Latent Semantic Analysis in a psychometric evaluation of the quality of learned semantic distances.