Non-computer scientists, don't be afraid of the big complicated equations and stuff, if you get the gist of it that's perfectly cool - you can pick these up with practice, and remember, it's not rocket science, it's computer science :)
Here they are:
Word association norms, mutual information, and lexicography – Church, Hanks - 1989
Evaluation techniques for automatic semantic extraction: Comparing syntactic and window-based approaches – Grefenstette - 1993
A WordNet based rule generalization engine for meaning extraction by Joyce Yue Chai, Alan W. Biermann — 1997 — Tenth International Symposium On Methodologies For Intelligent Systems
Finding Semantically Related Words in Large corpora by Fi Mu, Pavel Smrž, Pavel Rychlý
Syntactic contexts for finding semantically related words by Lonneke Van Der Plas, Gosse Bouma — In CLIN
Making senses: Bootstrapping sense-tagged lists of semantically related words by Nancy Ide — 2006 — Computational Linguistics and Intelligent Text Processing. Lecture notes in Computer Science 3878
Mapping syntactic dependencies onto semantic relations by Pablo Gamallo, Marco Gonzalez, Alexandre Agustini, Gabriel Lopes, Vera S. De Lima — 2002 — ECAI Workshop on Machine Learning and Natural Language Processing for Ontology Engineering
Contextual word similarity and estimation from sparse data (1993) by Ido Dagan In Proceedings of the 31st Annual Meeting of the Association for Computational Linguistics
Putting Pieces Together: Combining FrameNet, VerbNet and WordNet for Robust Semantic Parsing (2005) by L Shi, R Mihalcea in Proceedings of the Sixth International Conference on Intelligent Text Processing and Computational Linguistics
Exploring the Potential of Semantic Relatedness in Information Retrieval (2006) by Christ of Müller, Iryna Gurevych, In Proc. of LWA 2006 Lernen - Wissensentdeckung - Adaptivität: Information Retrieval
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