@conference {1973176,
	title = {Affordance Perception in Risk Adverse IT Adoption: An Agenda to Identify Drivers of Risk Consideration and Control Adoption in Individual Technology Choices},
	booktitle = {2015 Pre-ICIS Workshop on Accounting Information Systems},
	year = {2015},
	month = {2015},
	keywords = {Accounting, BIS},
	author = {Curry,Michael and Marshall,Byron}
}
@article {1973196,
	title = {Aspects of {\textquoteright}Relevance{\textquoteright} in the Alignment of Curriculum with Educational Standards},
	journal = {Information Processing \& Management},
	volume = {46},
	year = {2010},
	month = {2010},
	pages = {362-376},
	abstract = {Retrieval of useful digitized learning objects is a key objective for educational digital libraries, but imprecise definitions of alignment hinder the development of effective retrieval mechanisms. With over 63,000 U.S. K-12 science and mathematics education standards and a rapid proliferation of Web-enabled curriculum, retrieving curriculum that aligns with the standards to which teachers must teach is increasingly important. Previous studies of such alignment use single-dimensional and binary measures of relevance. Perhaps as a consequence they suffer from low inter-rater reliability (IRR), with experts agreeing about alignments only some 20-40\% of the time. We present the results of an experiment in which the dependent variable {\textquoteleft}alignment{\textquoteright} is operationalized using the Saracevic model of relevance in which; i.e., alignment is defined and measured through {\textquoteleft}clues{\textquoteright} from the everyday practice of K-12 teaching. Results show higher inter-rater reliability on all clues with significantly higher IRR on several specific alignment dimensions. In addition, a (linear) model of {\textquoteleft}overall alignment{\textquoteright} is derived and estimated. Both the structure and explanatory power of the model differ significantly between searching vs. assessment. These results illustrate the usefulness of clue-based relevance measures for information retrieval and have important consequences for both the formulation of automated retrieval mechanisms and the construction of a gold standard set of standard-curriculum alignments.},
	keywords = {Accounting, BIS},
	url = {http://www.sciencedirect.com/science/article/B6VC8-4XF7Y02-1/2/3fd5e4257f3d904d5929eeff2185c678},
	author = {Reitsma,Reindert and Marshall,Byron and Zarske,Malinda}
}
@article {1973221,
	title = {Aggregating Automatically Extracted Regulatory Pathway Relations},
	journal = {IEEE Transactions on Information Technology in Biomedicine},
	volume = {10},
	year = {2006},
	month = {2006},
	pages = {100- 108},
	abstract = {Automatic tools to extract information from biomedical texts are needed to help researchers leverage the vast and increasing body of biomedical literature. While several biomedical relation extraction systems have been created and tested, little work has been done to meaningfully organize the extracted relations. Organizational processes should consolidate multiple references to the same objects over various levels of granularity, connect those references to other resources, and capture contextual information. We propose a feature decomposition approach to relation aggregation to support a five-level aggregation framework. Our BioAggregate tagger uses this approach to identify key features in extracted relation name strings. We show encouraging feature assignment accuracy and report substantial consolidation in a network of extracted relations.},
	keywords = {Accounting, BIS},
	url = {http://people.oregonstate.edu/~marshaby/Papers/Marshall_IEEE_TITB_2005.pdf},
	author = {Marshall,Byron and Su,Hua and McDonald,Daniel and Eggers,Shauna and Chen,Hsinchun}
}
