Question classification in restricted domain using syntactic parsing-based quadratic-Bayesian model

2013 ◽  
Vol 32 (6) ◽  
pp. 1685-1687 ◽  
Author(s):  
Yu JI ◽  
Rong-bo WANG ◽  
Zhi-qun CHEN
Author(s):  
Shanthi Palaniappan ◽  
Sridevi U. K. ◽  
Pathur Nisha S.

Question Classification(QC) mainly deals with syntactic parsing for finding the similarity. To improve the accuracy of classification, a semantic similarity approach of a question along with the question dataset is calculated. The semantic similarity of the question is initially achieved by syntactic parsing to extract the noun, verb, adverb, and adjective. However, adjectives and adverbs do give sentences an exact meaning that should also be considered for computing the semantic similarity. The proposed RLQC (Register Linear and Question Classification) model for semantic similarity of questions uses HSO (Hirst and St. Onge) measure with Gloss based measure to enhance the semantic similarity relatedness by considering the Noun, Verb, Adverb and Adjective. The semantic similarity of the question pairs for RLQC is 0.2% higher compared to HSO model. The highest semantic similarity of the proposed model achieves a better accuracy.


1981 ◽  
Vol 20 (03) ◽  
pp. 174-178 ◽  
Author(s):  
A. I. Barnett ◽  
J. Cynthia ◽  
F. Jane ◽  
Nancy Gutensohn ◽  
B. Davies

A Bayesian model that provides probabilistic information about the spread of malignancy in a Hodgkin’s disease patient has been developed at the Tufts New England Medical Center. In assessing the model’s reliability, it seemed important to use it to make predictions about patients other than those relevant to its construction. The accuracy of these predictions could then be tested statistically. This paper describes such a test, based on 243 Hodgkin’s disease patients of known pathologic stage. The results obtained were supportive of the model, and the test procedure might interest those wishing to determine whether the imperfections that attend any attempt to make probabilistic forecasts have gravely damaged their accuracy.


1996 ◽  
Vol 35 (04/05) ◽  
pp. 309-316 ◽  
Author(s):  
M. R. Lehto ◽  
G. S. Sorock

Abstract:Bayesian inferencing as a machine learning technique was evaluated for identifying pre-crash activity and crash type from accident narratives describing 3,686 motor vehicle crashes. It was hypothesized that a Bayesian model could learn from a computer search for 63 keywords related to accident categories. Learning was described in terms of the ability to accurately classify previously unclassifiable narratives not containing the original keywords. When narratives contained keywords, the results obtained using both the Bayesian model and keyword search corresponded closely to expert ratings (P(detection)≥0.9, and P(false positive)≤0.05). For narratives not containing keywords, when the threshold used by the Bayesian model was varied between p>0.5 and p>0.9, the overall probability of detecting a category assigned by the expert varied between 67% and 12%. False positives correspondingly varied between 32% and 3%. These latter results demonstrated that the Bayesian system learned from the results of the keyword searches.


2008 ◽  
Vol 31 (4) ◽  
pp. 23
Author(s):  
Rachel Vanderlaan ◽  
Rod Hardy ◽  
Golam Kabir ◽  
Peter Back ◽  
A J Pawson

Background: ShcA, a scaffolding protein, generates signalspecificity by docking to activated tyrosine kinases through distinct phosphotyrosine recognition motifs, while mediating signal complexity through formation of diverse downstream phosphotyrosine complexes. Mammalian ShcA encodes 3 isoforms having a modular architecture of a PTB domain and SH2 domain, separated by a CH1 region containing tyrosine phosphorylation sites important in Ras-MAPK activation. Objective and Methods: ShcA has a necessary role in cardiovascular development^1,2. However, the role of ShcA in the adult myocardium is largely unknown, also unclear, is how ShcA uses its signaling modules to mediate downstream signaling. To this end, cre/loxP technology was employed to generate a conditional ShcA allele series. The myocardial specific ShcA KO (ShcA CKO) and myocardial restricted domain mutant KI mice were generated using cre expressed from the mlc2v locus^3 coupled with the ShcA floxed allele and in combination with the individual ShcA domain mutant KI alleles^2. Results: ShcACKO mice develop a dilated cardiomyopathy phenotype by 3 months of life, typified by depressed cardiac function and enlarged chamber dimensions. Isolated cardiomyocytes from ShcA CKO mice have preserved contractility indicating an uncoupling between global heart function and single myocyte contractile mechanics. Force-length experiments suggest that the loss of shcAmediates the uncoupling through deregulation of extracellular matrix interactions. Subsequent, analysis of the ShcA myocardial restricted domain mutant KImice suggests that ShcA requires PTB domain docking to upstream tyrosine kinases and subsequent phosphorylation of the CH1 tyrosines important for downstream signaling. Conclusion: ShcA is required for proper maintenance of cardiac function, possibly regulation of extracellular matrix interactions. References: 1. Lai KV, Pawson AJ. The ShcA phosphotyrosine docking protein sensitizescardiovascular signaling in the mouse embryo. Genes and Dev 2000;14:1132-45. 2. Hardy WR. et al. Combinatorial ShcA docking interactions supportdiversity in tissue morphogenesis. Science2007;317:251-6. 3.Minamisawa, s. et al. A post-transcriptional compensatory pathway inheterozygous ventricular myosin light chain 2-deficient mice results in lack ofgene dosage effect during normal cardiac growth or hypertrophy. J Biol Chem 1999;274:10066-70.


Author(s):  
Lorenzo Bencivelli ◽  
Massimiliano Giuseppe Marcellino ◽  
Gianluca Moretti

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