The Impact of DSS Use and Information Load on Errors and Decision Quality

This paper uses a laboratory experiment to examine the effect of DSS use on the decision maker‘s error patterns and decision quality. The DSS used in our experiments is the widely used Expert Choice (EC) implementation of the Analytic Hierarchy Process. Perhaps surprisingly, our experiments do not provide general support for the often tacit assumption that the use of a DSS such as EC improves decision quality. Rather, we find that, whereas a DSS can help decision makers develop a better understanding of the essence of a decision problem and can reduce logical errors (especially if the information load is high), it is also susceptible to introducing accidental effects such as mechanical errors. In some cases, as in our study, the accidental errors may outweigh the benefits of using a DSS, leading to lower quality decisions

Automatic indexing by discipline and high-level categories: Methodology and potential applications.

This paper first describes the methodology of journal descriptor (JD) ndexing, based on human indexing at the journal level using only 127 descriptors, and applying statistical methods that associate this journal indexing with text words in a training set of MEDLINE® citations. These associations form the basis for automatic indexing of documents outside the training set. The paper then presents the new technique of semantic type (ST) indexing, based on JD indexing associated with each of 134 ST's, and applying the standard cosine coefficient measure to compare the similarity between the JD indexing of a document and the JD indexing of each ST. The ST indexing of the document is the list of ST's ranked in decreasing order of similarity between the JD indexing of the document and the JD indexing of the ST's. Discussion of the potential usefulness and application of the very general indexing provided by JD's and ST's comprises the remainder of the paper. JD's have been used for more than thirty years to search MEDLINE by discipline, and discipline-based indexing is in evidence on the Web. It is suggested, with several examples, that ST's may convey a unique slant of a document's content not normally represented in standard indexing vocabularies. Use of ST indexing to rank retrieved output is mentioned as a possible application. Notwithstanding the importance of methodology and performance issues, the intent of this paper is to explore questions of the potential utility and applicability of JD and ST indexing

Analytic Hierarchy Process in Group Decision Making: Much Ado About Nothing

This paper examines the use of the Analytic Hierarchy Process (AHP) in individual and group decision making. Group AHP without individual AHP resulted in the exchange of the most common information while the combination of both group and individual AHP resulted in the least. The use of AHP in group decision making took longer, but did not result in better decisions. Subjects reported that they processed less information when using AHP and felt there was less credibility in the information discussed

Mejora de un corpus extraído automáticamente para desambiguar términos del UMLS Metathesaurus

Anotar a mano un conjunto de ejemplos para entrenar métodos de aprendizaje automático para desambiguar anotaciones con conceptos del UMLS Metathesaurus no es posible debido a su elevado coste. En este artículo, evaluamos dos métodos para mejorar la calidad de un corpus obtenido de manera automática. El primer método busca términos específicos y el segundo filtra falsos positivos. La combinación de los dos métodos obtiene una mejora de 6% en F-measure y un 8% en recall, comparado con el corpus original extraído de manera automática.Manually annotated data is expensive, so manually covering a large terminological resource like the UMLS Metathesaurus is infeasible. In this paper, we evaluate two approaches used to improve the quality of an automatically extracted corpus to train statistical learners to performWSD. The first one contributes to more specific terms while the second filters out false positives. Using both approaches, we have obtained an improvement on the original automatic extracted corpus of approximately 6% in F-measure and 8% in recall

MeSH indexing based on automatically generated summaries

BACKGROUND: MEDLINE citations are manually indexed at the U.S. National Library of Medicine (NLM) using as reference the Medical Subject Headings (MeSH) controlled vocabulary. For this task, the human indexers read the full text of the article. Due to the growth of MEDLINE, the NLM Indexing Initiative explores indexing methodologies that can support the task of the indexers. Medical Text Indexer (MTI) is a tool developed by the NLM Indexing Initiative to provide MeSH indexing recommendations to indexers. Currently, the input to MTI is MEDLINE citations, title and abstract only. Previous work has shown that using full text as input to MTI increases recall, but decreases precision sharply. We propose using summaries generated automatically from the full text for the input to MTI to use in the task of suggesting MeSH headings to indexers. Summaries distill the most salient information from the full text, which might increase the coverage of automatic indexing approaches based on MEDLINE. We hypothesize that if the results were good enough, manual indexers could possibly use automatic summaries instead of the full texts, along with the recommendations of MTI, to speed up the process while maintaining high quality of indexing results. RESULTS: We have generated summaries of different lengths using two different summarizers, and evaluated the MTI indexing on the summaries using different algorithms: MTI, individual MTI components, and machine learning. The results are compared to those of full text articles and MEDLINE citations. Our results show that automatically generated summaries achieve similar recall but higher precision compared to full text articles. Compared to MEDLINE citations, summaries achieve higher recall but lower precision. CONCLUSIONS: Our results show that automatic summaries produce better indexing than full text articles. Summaries produce similar recall to full text but much better precision, which seems to indicate that automatic summaries can efficiently capture the most important contents within the original articles. The combination of MEDLINE citations and automatically generated summaries could improve the recommendations suggested by MTI. On the other hand, indexing performance might be dependent on the MeSH heading being indexed. Summarization techniques could thus be considered as a feature selection algorithm that might have to be tuned individually for each MeSH heading

Knowledge-based biomedical word sense disambiguation: comparison of approaches

<p>Abstract</p> <p>Background</p> <p>Word sense disambiguation (WSD) algorithms attempt to select the proper sense of ambiguous terms in text. Resources like the UMLS provide a reference thesaurus to be used to annotate the biomedical literature. Statistical learning approaches have produced good results, but the size of the UMLS makes the production of training data infeasible to cover all the domain.</p> <p>Methods</p> <p>We present research on existing WSD approaches based on knowledge bases, which complement the studies performed on statistical learning. We compare four approaches which rely on the UMLS Metathesaurus as the source of knowledge. The first approach compares the overlap of the context of the ambiguous word to the candidate senses based on a representation built out of the definitions, synonyms and related terms. The second approach collects training data for each of the candidate senses to perform WSD based on queries built using monosemous synonyms and related terms. These queries are used to retrieve MEDLINE citations. Then, a machine learning approach is trained on this corpus. The third approach is a graph-based method which exploits the structure of the Metathesaurus network of relations to perform unsupervised WSD. This approach ranks nodes in the graph according to their relative structural importance. The last approach uses the semantic types assigned to the concepts in the Metathesaurus to perform WSD. The context of the ambiguous word and semantic types of the candidate concepts are mapped to Journal Descriptors. These mappings are compared to decide among the candidate concepts. Results are provided estimating accuracy of the different methods on the WSD test collection available from the NLM.</p> <p>Conclusions</p> <p>We have found that the last approach achieves better results compared to the other methods. The graph-based approach, using the structure of the Metathesaurus network to estimate the relevance of the Metathesaurus concepts, does not perform well compared to the first two methods. In addition, the combination of methods improves the performance over the individual approaches. On the other hand, the performance is still below statistical learning trained on manually produced data and below the maximum frequency sense baseline. Finally, we propose several directions to improve the existing methods and to improve the Metathesaurus to be more effective in WSD.</p

Sensitivity of CPT Tests with Neutral Mesons

The sensitivity of experiments with neutral mesons to possible indirect CPT violation is examined. It is shown that experiments conventionally regarded as equivalent can have CPT reaches differing by orders of magnitude within the framework of a minimal CPT- and Lorentz-violating extension of the standard model.Comment: 4 pages REVTeX, published in Physical Review Letter

Velocity Selection for Propagating Fronts in Superconductors

Using the time-dependent Ginzburg-Landau equations we study the propagation of planar fronts in superconductors, which would appear after a quench to zero applied magnetic field. Our numerical solutions show that the fronts propagate at a unique speed which is controlled by the amount of magnetic flux trapped in the front. For small flux the speed can be determined from the linear marginal stability hypothesis, while for large flux the speed may be calculated using matched asymptotic expansions. At a special point the order parameter and vector potential are dual, leading to an exact solution which is used as the starting point for a perturbative analysis.Comment: 4 pages, 2 figures; submitted to Phys. Rev. Letter