Lori Watrous-deVersterre

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Key-phrase extraction plays a useful a role in research areas of Information Systems (IS) like digital libraries. Short metadata like key phrases are beneficial for searchers to understand the concepts found in the documents. This paper evaluates the effectiveness of different supervised learning techniques on biomedical full-text: Sequential Minimal(More)
Query In Context (QIC) is a personalized search system that enhances individual search by incorporating user preferences in query expansion, capturing meanings embedded in documents, and ranking search results with context-enriched features. In this paper, we propose a new technique for QIC's Query Expansion module, which reformulates user queries by using(More)
For most, the web is the first source to answer a question formulated by curiosity, need, or research reasons. This phenomenon is due to the internet's ubiquitous access, ease of use, and the extensive and ever expanding content. The problem is no longer the need to acquire content to encourage use, but to provide organizational tools to support content(More)
Word sense disambiguation is the problem of selecting a sense for a word from a set of predefined possibilities. This is a significant problem in the biomedical domain where a single word may be used to describe a gene, protein, or abbreviation. In this paper, we evaluate SENSATIONAL, a novel unsupervised WSD technique, in comparison with two popular(More)
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