Towards new information resources for public health: From WordNet to MedicalWordNet

In the last two decades, WORDNET has evolved as the most comprehensive computational lexicon of general English. In this article, we discuss its potential for supporting the creation of an entirely new kind of information resource for public health, viz. MEDICAL WORDNET. This resource is not to be conceived merely as a lexical extension of the original WORDNET to medical terminology; indeed, there is already a considerable degree of overlap between WORDNET and the vocabulary of medicine. Instead, we propose a new type of repository, consisting of three large collections of (1) medically relevant word forms, structured along the lines of the existing Princeton WORDNET; (2) medically validated propositions, referred to here as medical facts, which will constitute what we shall call MEDICAL FACTNET; and (3) propositions reflecting laypersons’ medical beliefs, which will constitute what we shall call the MEDICAL BELIEFNET. We introduce a methodology for setting up the MEDICAL WORDNET. We then turn to the discussion of research challenges that have to be met in order to build this new type of information resource

Generating indicative-informative summaries with SumUM

We present and evaluate SumUM, a text summarization system that takes a raw technical text as input and produces an indicative informative summary. The indicative part of the summary identifies the topics of the document, and the informative part elaborates on some of these topics according to the reader's interest. SumUM motivates the topics, describes entities, and defines concepts. It is a first step for exploring the issue of dynamic summarization. This is accomplished through a process of shallow syntactic and semantic analysis, concept identification, and text regeneration. Our method was developed through the study of a corpus of abstracts written by professional abstractors. Relying on human judgment, we have evaluated indicativeness, informativeness, and text acceptability of the automatic summaries. The results thus far indicate good performance when compared with other summarization technologies

IEEE Standard 1500 Compliance Verification for Embedded Cores

Core-based design and reuse are the two key elements for an efficient system-on-chip (SoC) development. Unfortunately, they also introduce new challenges in SoC testing, such as core test reuse and the need of a common test infrastructure working with cores originating from different vendors. The IEEE 1500 Standard for Embedded Core Testing addresses these issues by proposing a flexible hardware test wrapper architecture for embedded cores, together with a core test language (CTL) used to describe the implemented wrapper functionalities. Several intellectual property providers have already announced IEEE Standard 1500 compliance in both existing and future design blocks. In this paper, we address the problem of guaranteeing the compliance of a wrapper architecture and its CTL description to the IEEE Standard 1500. This step is mandatory to fully trust the wrapper functionalities in applying the test sequences to the core. We present a systematic methodology to build a verification framework for IEEE Standard 1500 compliant cores, allowing core providers and/or integrators to verify the compliance of their products (sold or purchased) to the standar

Natural language processing

Beginning with the basic issues of NLP, this chapter aims to chart the major research activities in this area since the last ARIST Chapter in 1996 (Haas, 1996), including: (i) natural language text processing systems - text summarization, information extraction, information retrieval, etc., including domain-specific applications; (ii) natural language interfaces; (iii) NLP in the context of www and digital libraries ; and (iv) evaluation of NLP systems