The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Accurate and reliable prediction incidence of diarrhea disease is necessary for the health authorities to ensure the appropriate action for the control of the outbreak. In this study, a hybrid prediction algorithm (EMD-GRNN), which combines empirical mode decomposition (EMD) as time series decomposition method and the generalized regression neural network (GRNN) as prediction model, is proposed to...
Accurate and reliable forecasts of diarrhoeal outpatient visits are necessary for the health authorities to ensure the appropriate action for the control of the outbreak. In this study, a novel forecasting model based on hybridization the Firefly Algorithm (FA) and Support Vector Regression (SVR) has been proposed to forecast the diarrhoeal outpatient visits in Shanghai. The performance of SVR models...
Infectious diarrhea is an important public health problem around the world. Meteorological factors have been strongly linked to the incidence of infectious diarrhea. Therefore, accurately forecast infectious diarrhea under the effect of meteorological factors is critical to control efforts. In this paper, the abilities of three different artificial neural network (ANN) models, including feed forward...
A robust numerical measures of lexical relatedness is significant for many applications, such as text summarization system and information retrieval researches. Standard seme-based measures of word pair relatedness are based on only the comparison of semes of the two words. This paper propose a new model called seme based graph using an extended random walk to measure explicit and implicit relatedness...
Various types of structured information in Chinese encyclopedia HDWiki like as Wikipedia were divided into three categories: concept, relationship and entity. This paper described a novel symbols guided search that facilitated user to format unambiguous and complex logical queries in the logic of natural language. This facilitation and understanding base on the ternary relationships exist among the...
This paper investigates the link prediction problem in location-based social networking services (LBSNS) with protected location history. While former approaches mainly utilize the accurate locations, the relevant data we analyzed are modeled by a location privacy protection model called k-anonymous spatial-temporal cloaking model (KSTCM) which perturbs the location-related records on both temporal...
Currently, with the emerging of Clouds and Internet Of Things technologies, researches of context-aware applications have extended from individual-smart-space to ubiquitous intelligent environments. A context management system (CMS) is an important component of a context-aware middleware that supports distributed, context-aware applications to obtain context information from pervasive computing environments...
A new semi-supervised approach for Chinese relation extraction (RE) over constantly growing and edgeless web data is introduced in this paper. Existing semi-supervised approaches have the better improvement potential while lacking syntactic structure and semantic meaning of a sentence and unsuitable to loosely structured Chinese sentences. To follow their basic procedures as well as covering their...
Sensor plays an important role in context-aware computing. While sensor modeling is usually isolated from former researches on context modeling and sensor type is always restricted to physical ones, this paper aims to provide a more comprehensive insight into the relationships between sensor and context. Based on a more generic definition of sensor and a corresponding sensor category in context-aware...
Nowadays, numerous applications involving spatial data are emerging. While efficient management of tremendous spatial-temporal objects is a challenge due to the highly dynamic nature of the data, the demand for fast getting query results and minimum update cost. However, the query performance optimizations and the update cost minimizations cannot be achieved at the same time. In this paper, a novel...
As a widespread approach in recommender systems, item-based collaborative filtering can predict an active user's interest for a target item based on his interest and the ratings for those similar items to his visited items. As the effect of human's conformity psychology, an individual user's judgment usually tends to follow the general view. The majority of existing item-based collaborative filtering...
The emergence of location-aware mobile social networking applications (SNAs) has gained considerable prominence in ubiquitous computing. However, the weak designs of privacy protection result in more potential risks that users have to face. This paper presents a deep insight into the designs of privacy protection, especially from the perspective of location privacy. Three main potential risks and...
With the development of mobile technology, Internet and GIS, LBS plays an important role in various applications. As the basis of LBS, the research on acquisition, processing, storage, query of mobile object trajectories has been quite mature, but the analysis and the application of movement patterns contained in mobile object trajectories is relatively lagging behind. The calculation of trajectory...
Sequential pattern mining based on constraint is now an important research direction of data mining, since it can reduce the generation of useless candidates as well as make the generated patterns meet the requirements of special users. Average value constraint is a kind of tough aggregate constraint. We propose here an effective pruning strategy based on average value constraint to avoid constructing...
Existing evaluation methods either investigate whether ontologies are “fit for purpose”, or focus on evaluating consistencies of the data in regard to the axioms defined in the ontologies. In this paper, we focus on how to evaluate the consistency of ontology with respect to taxonomic relationships, and we suggest a new measure to evaluate the taxonomic consistency of an ontology. As the semantic...
Skyline query is widely used in many applications, such as multi-criteria decision making, data mining and visualization, as well as Location-Based Services (LBS). The previous works about skyline mainly focuses on static attributes, such as Branch and Bound Skyline and Probabilistic Skyline. However, due to the requirements in the privacy-protection as protecting individual position and individual...
As a scheduled World Expo in the grand tradition of international fairs and expositions, Shanghai World Expo (SWE) has recently gained much attention for its highly sophisticated online vision called "Online Expo Shanghai". In this context, researchers are working to provide intelligent mechanisms to SWE. To support intelligent SWE managements and services, SWE modeling is an essential requirement...
Recommender system emerges as a technology addressing "information overload" problem. Collaborative Filtering (CF) is successful and widely used in many personalized recommender applications, such as digital library, e-commerce, news sites, and so on. However, most collaborative filtering algorithms suffer from data sparsity problem which leads to inaccuracy of recommendation. This paper...
In recent years, the travel time predictions have become a popular research topic. In this paper, we present a new algorithm of the travel time predictions based on the idea of using the shared traveler's positions to collect traffic conditions. Several experiments show that our algorithm has a broader applied area than existing algorithms and can provide real-time and the accurate predictions for...
In this paper, we propose a new measure framework for evaluating taxonomy relationships in ontologies using lexical semantic relatedness. First, we suggest a new quantitative measure model for WordNet, the model can be used to compute the semantic relatedness of concepts in ontologies. Next, according to the relativities of concepts, we describe the way to estimate the classification consistency of...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.