An operational system for subject switching between controlled vocabularies: A computational linguistics approach

The NASA Lexical Dictionary (NLD), a system that automatically translates input subject terms to those of NASA, was developed in four phases. Phase One provided Phrase Matching, a context sensitive word-matching process that matches input phrase words with any NASA Thesaurus posting (i.e., index) term or Use reference. Other Use references have been added to enable the matching of synonyms, variant spellings, and some words with the same root. Phase Two provided the capability of translating any individual DTIC term to one or more NASA terms having the same meaning. Phase Three provided NASA terms having equivalent concepts for two or more DTIC terms, i.e., coordinations of DTIC terms. Phase Four was concerned with indexer feedback and maintenance. Although the original NLD construction involved much manual data entry, ways were found to automate nearly all but the intellectual decision-making processes. In addition to finding improved ways to construct a lexical dictionary, applications for the NLD have been found and are being developed

A study of the relative effectiveness and cost of computerized information retrieval in the interactive mode

Results of a number of experiments to illuminate the relative effectiveness and costs of computerized information retrieval in the interactive mode are reported. It was found that for equal time spent in preparing the search strategy, the batch and interactive modes gave approximately equal recall and relevance. The interactive mode however encourages the searcher to devote more time to the task and therefore usually yields improved output. Engineering costs as a result are higher in this mode. Estimates of associated hardware costs also indicate that operation in this mode is more expensive. Skilled RECON users like the rapid feedback and additional features offered by this mode if they are not constrained by considerations of cost

Hybrid Query Expansion on Ontology Graph in Biomedical Information Retrieval

Nowadays, biomedical researchers publish thousands of papers and journals every day. Searching through biomedical literature to keep up with the state of the art is a task of increasing difficulty for many individual researchers. The continuously increasing amount of biomedical text data has resulted in high demands for an efficient and effective biomedical information retrieval (BIR) system. Though many existing information retrieval techniques can be directly applied in BIR, BIR distinguishes itself in the extensive use of biomedical terms and abbreviations which present high ambiguity. First of all, we studied a fundamental yet simpler problem of word semantic similarity. We proposed a novel semantic word similarity algorithm and related tools called Weighted Edge Similarity Tools (WEST). WEST was motivated by our discovery that humans are more sensitive to the semantic difference due to the categorization than that due to the generalization/specification. Unlike most existing methods which model the semantic similarity of words based on either the depth of their Lowest Common Ancestor (LCA) or the traversal distance of between the word pair in WordNet, WEST also considers the joint contribution of the weighted distance between two words and the weighted depth of their LCA in WordNet. Experiments show that weighted edge based word similarity method has achieved 83.5% accuracy to human judgments. Query expansion problem can be viewed as selecting top k words which have the maximum accumulated similarity to a given word set. It has been proved as an effective method in BIR and has been studied for over two decades. However, most of the previous researches focus on only one controlled vocabulary: MeSH. In addition, early studies find that applying ontology won\u27t necessarily improve searching performance. In this dissertation, we propose a novel graph based query expansion approach which is able to take advantage of the global information from multiple controlled vocabularies via building a biomedical ontology graph from selected vocabularies in Metathesaurus. We apply Personalized PageRank algorithm on the ontology graph to rank and identify top terms which are highly relevant to the original user query, yet not presented in that query. Those new terms are reordered by a weighted scheme to prioritize specialized concepts. We multiply a scaling factor to those final selected terms to prevent query drifting and append them to the original query in the search. Experiments show that our approach achieves 17.7% improvement in 11 points average precision and recall value against Lucene\u27s default indexing and searching strategy and by 24.8% better against all the other strategies on average. Furthermore, we observe that expanding with specialized concepts rather than generalized concepts can substantially improve the recall-precision performance. Furthermore, we have successfully applied WEST from the underlying WordNet graph to biomedical ontology graph constructed by multiple controlled vocabularies in Metathesaurus. Experiments indicate that WEST further improve the recall-precision performance. Finally, we have developed a Graph-based Biomedical Search Engine (G-Bean) for retrieving and visualizing information from literature using our proposed query expansion algorithm. G-Bean accepts any medical related user query and processes them with expanded medical query to search for the MEDLINE database

ARTeFACT Movement Thesaurus

The ARTeFACT Movement Thesaurus is a continuation of the ARTeFACT project which was developed at the University of Virginia as a means of enabling research into movement-based arts, specifically dance. The Movement Thesaurus is a major step toward providing access to movement-derived data. By using motion capture technologies we plan to provide a sophisticated, open source tool that can help make film searchable for single movements and movement phrases. The ARTeFACT Movement Thesaurus will contain over 100 codified dance movements derived from Western concert dance genres and styles from which we can develop algorithms for automatic search capabilities in film. By bringing together engineers, movement specialists, and mathematicians we will forge ahead to break new ground in movement research and take one step closer to the creation of an automated means of mining danced texts and filmed movement