Student Health Facility Revenue Bond Funds, Iowa State University of Science and Technology, Independent Auditor's Report, Financial Statements and Supplemental Information, June 30, 2005

State University Audit Report

City of Donnellson Independent Auditor's Report Basic Finanical Statements and Supplementary Information Schedule of Findings, June 30, 2004

Independent Auditor's Reports, Basic Financial Statements, Supplementary Information and Schedule of Findings

Office of Treasurer of State Iowa Educational Savings Plan Trust Independent Auditor's Reports Finanical Statements and Supplementary Information, June 30, 2005.

Office of Treasurer of State, Iowa Educational Savings Plan Trust (Trust) for the year ended June 30, 2005. Independent Auditor's Report, Financial Statements and Supplementary Information.

Rural Iowa Waste Management Association Independent Auditor's Reports Finanical Statement and Required Supplementary Information Schedule of Findings for the period ending June 30, 2004.

Rural Iowa Waste Management Association Independent Auditor's Reports, Financial Statement, Required Supplementary Information and Schedule of Findings for the Period Ending June 30, 2004.

Using qualia information to identify lexical semantic classes in an unsupervised clustering task

Acquiring lexical information is a complex problem, typically approached by relying on a number of contexts to contribute information for classification. One of the first issues to address in this domain is the determination of such contexts. The work presented here proposes the use of automatically obtained FORMAL role descriptors as features used to draw nouns from the same lexical semantic class together in an unsupervised clustering task. We have dealt with three lexical semantic classes (HUMAN, LOCATION and EVENT) in English. The results obtained show that it is possible to discriminate between elements from different lexical semantic classes using only FORMAL role information, hence validating our initial hypothesis. Also, iterating our method accurately accounts for fine-grained distinctions within lexical classes, namely distinctions involving ambiguous expressions. Moreover, a filtering and bootstrapping strategy employed in extracting FORMAL role descriptors proved to minimize effects of sparse data and noise in our task.

Sheldon Community School District, Independent Auditor's Reports, Basic Financial Statements and Supplementary Information, Schedule of Findings, June 30, 2005

Community School District Audit Report