Text search engines are inadequate for indexing and searching XML documents because they ignore metadata and aggregation structure implicit in the XML documents. On the other hand, the query languages supported by specialized XML search engines are very complex. In this paper, we present a simple yet flexible query language, and develop its semantics to enable intuitively appealing extraction o...

Document classification and topic models are useful tools for managing and understanding large corpora. Topic models are used to uncover underlying semantic and structure of document collections. Categorizing large collection of documents requires hand-labeled training data, which is time consuming and needs human expertise. We believe engaging user in the process of document labeling helps red...

During the processes of primary succession and soil development, large stocks of organic C with very long residence times accumulate in many soils. Soluble organic C adsorbed by soils may contribute to the stock of organic C accumulating during soil development. We determined whether the mineralization rate of water-soluble organic C and the insoluble residue from C-labelled leaf litter added t...

BACKGROUND To test the value of a simulated Family Conference Objective Structured Clinical Exam (OSCE) for resident assessment purposes, we examined the generalizability and construct validity of its scores in a multi-institutional study. METHODS Thirty-four first-year (PG1) and 27 third-year (PG3) surgery residents (n = 61) from 6 training programs were tested. The OSCE consisted of 2 cases...

Improving our understanding of cloud chemistry depends on achieving better chemical characterization (90% of the organic carbon [OC] fraction remains uncharacterized) and, consequently, assessing the reactivity of this complex system. In this manuscript, we report for the first time the concentrations of 16 amino acids (AAs) in 25 cloud water samples. The concentrations of individual AAs ranged...

The digital libraries of the future will include not only (ASCII) text information but scanned paper documents as well as still photographs and videos. There is, therefore, a need to index and retrieve information from such multi-media collections. The Center for Intelligent Information Retrieval (CIIR) has a number of projects to index and retrieve multi-media information. These include: 1. Th...

We present a methodology that takes as input scanned documents of typed or hand-written text, and produces transcriptions of the text as output. Instead of using OCR technology, the methodology is game-based and produces such transcriptions as a by-product. The approach is intended particularly for languages for which language technology and resources are scarce and reliable OCR technology may ...

We would like to introduce BEECON, an information and event extraction system for business intelligence. This is the first ontology-based system for business documents analysis that is able to detect 41 different types of business events from unstructured sources of information. The described system is intended to enhance business intelligence efficiency by automatically extracting relevant con...

Common clustering techniques have the disadvantage that they do not provide intensional descriptions of the clusters obtained. Conceptual Clustering techniques, on the other hand, provide such descriptions, but are known to be rather slow. In this paper, we discuss a way of combining both techniques. We rst cluster the documents by a variant of k{Means, using a thesaurus as background knowledge...