This study proposes a model of factors that may be driving previously observed gender differences in acceptance decisionmaking. In particular, a significant effect is found for generalized computer self-efficacy, over and above that of psychological gender role identified in prior related research. However, this study departs from prior work in technology adoption by employing actual choice bet...

We leveraged a wide range of knowledge in machine learning and information retrieval to develop a robust keywords identification system. In particular, we adapted the Tf-Idf heuristic for feature selection, investigated linear regression, logistic regression, and SVM for predicting number of keywords (tags), and also implemented NaiveBayes, Labeled Latent Dirichlet Allocation(L-LDA) algorithms ...

at present, the solutions to prevent bedsore include using various techniques for movement and displacement of patients, which is not  possible for some patients or dangerous for some of them while it also poses problems for health care providers. on the other hand, development of information technology in the health care system including application of wireless sensor networks (wsns) has led t...

Keyword search enjoys great popularity due to succinctness and easy operability for exploring RDF data. SPARQL has been recommended as the standard query language that can retrieve any answers users need from available RDF data. Thus, keyword search based on keywords-to-SPARQL attracts more and more attention. However, existing solutions have main limitations that the summary index used for tra...

With the increasing trend towards collaborations for innovation across organizational boundaries, the strategic gravity of exploring potential technology partners has been accentuated in the paradigm of open innovation. However, as the openness across nations or industries has become broad, the conventional approaches to searching external partners have encountered a number of difficulties. The...

We discuss the problem of model selection in Genetic Programming using the framework provided by Statistical Learning Theory, i.e. Vapnik-Chervonenkis theory (VC). We present empirical comparisons between classical statistical methods (AIC, BIC) for model selection and the Structural Risk Minimization method (based on VC-theory) for symbolic regression problems. Empirical comparisons of differe...

Selection statements – if-then-else, switch and try-catch – are commonly used in modern imperative programming languages. We propose another selection statement called a choice existentially quantified statement. This statement turns out to be quite useful for pattern matching among several merits. Examples will be provided for this statement. keywords: selection, pattern matching, choice quant...

Documents clustering become an essential technology with the popularity of the Internet. That also means that fast and high-quality document clustering technique play core topics. Text clustering or shortly clustering is about discovering semantically related groups in an unstructured collection of documents. Clustering has been very popular for a long time because it provides unique ways of di...