Tackling the Internet Glossary Glut: Automatic Extraction and Evaluation of Genus Phrases

This paper addresses the problem of developing methods to be used in the identification and extraction of meaningful semantic components from large online glossaries. We present two sets of results. First, we report on the algorithm, ParseGloss, which was used to analyze definitions, and extract the main concept, or genus phrase. We ran the system on over 12,000 online glossary entries. Second, we present a method to evaluate our results, using human judgments on a collection of definitions from six different sources. This paper discusses our approach to the evaluation process, since the creation of a standard for evaluation is in itself a contribution to the field. The methods we have developed have required addressing the significant challenges of abstracting a single gold standard from multiple naive, human judgments on a highly subjective task. Once the method for creating the standard was developed, we then established the gold standard data. We report on our performance in running ParseGloss over this controlled collection of definitions. Our first set of results presents precision and recall on system performance. Our second results are presented in terms of techniques for determining agreement between human subjects. Success in the ParseGloss algorithm will contribute to the automatic creation of ontologies

Extending Metadata Definitions by Automatically Extracting and Organizing Glossary Definitions

Metadata descriptions of database contents are required to build and use systems that access and deliver data in response to user requests. When numerous heterogeneous databases are brought together in a single system, their various metadata formalizations must be homogenized and integrated in order to support the access planning and delivery system. This integration is a tedious process that requires human expertise and attention. In this paper we describe a method of speeding up the formalization and integration of new metadata. The method takes advantage of the fact that databases are often described in web pages containing natural language glossaries that define pertinent aspects of the data. Given a root URL, our method identifies likely glossaries, extracts and formalizes aspects of relevant concepts defined in them, and automatically integrates the new formalized metadata concepts into a large model of the domain and associated conceptualizations

Chapter 19 Noise pollution and its impact on human health and the environment

This chapter deals with (1) the basic theory of sound propagation; (2) an overview of noise pollution problem in view of policy and standards by the World Health Organization, the United States, and the European Union; (3) noise exposure sources from aircraft, road traffic and railways, in-vehicle, work, and construction sites, and occupations, and households; (4) the noise pollution impact on human health and the biological environment; (5) modeling of regional noise-affected habitats in protected and unprotected land areas and the marine environment; (6) noise control measures and sustainability in view of sustainable building design, noise mapping, and control measures such as barriers and berms along roadsides, acoustic building materials, roadway vehicle noise source control, road surface, and pavement materials; and (7) environmental noise pollution management measures and their impact on human health

Evaluation Beyond Usability

The evaluation of research artefacts is an important step to validate research contributions. Sub-disciplines of HCI often pursue primary goals other than usability, such as Sustainable HCI (SHCI), HCI for development, or health and wellbeing. For such disciplines, established evaluation methods are not always appropriate or sufficient, and new conventions for identifying, discussing, and justifying suitable evaluation methods need to be established. In this paper, we revisit the purpose and goals of evaluation in HCI and SHCI, and elicit five key elements that can provide guidance to identifying evaluation methods for SHCI research. Our essay is meant as a starting point for discussing current and improving future evaluation practice in SHCI; we also believe it holds value for other subdisciplines in HCI that encounter similar challenges while evaluating their research