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.
Using the Internet increasingly requires people to disclose personal information for various reasons such as establishing legitimacy, authentication, or providing personalized services. An enormous amount of literature analyzed various influencing variables that shape self-disclosure in online interaction. However, the range of studies considers very specific variables and therefore provides merely...
Past research has shown that both social and local features are informative for customer churn, however some studies have found that combining both kinds of data into a single model is ineffective. People who churn based on their neighbors' behavior are a distinct subset of customers from those who churn for personal reasons. However, for an effective retention campaign, it is desired to identify...
This paper describes the optimization of interval type-2 fuzzy integrators in Ensembles of ANFIS (adaptive neuro-fuzzy inferences systems) models for the prediction of the Dow Jones time series. The Dow Jones time series is used to the test of performance of the proposed ensemble architecture. We used the interval type-2 and type-1 fuzzy systems to integrate the output (forecast) of each Ensemble...
Social media has become one of the most popular marketing channels for many companies, which aims at maximizing their influence by various marketing campaigns conducted from their official accounts on social networks. However, most of these marketing accounts merely focus on the contents of their tweets. Less effort has been made on understanding tweeting time, which is a major contributing factor...
Planning in a multi-site, non-mass production environment is a special challenge because of several sources of uncertainty. Unlike in mass production facilities, in our setting the current state at all sites cannot be determined easily and exactly due to the spatial distribution of sites and the low degree of automation. For re-planning in case of failures, the possible alternative actions have to...
Data mining has been recently used in the field of car insurance to help the insurance companies in predicting the customers' choices in order to provide more competitive services. In this composition, the random forest was used to develop a classification model that could be applied in predicting which of the insurance policies would likely to be chosen by the customers. The performance of the developed...
In many organizations, especially in most utility companies including Company X, revenue collection is a major issue when customers face difficulties in paying their utility bills before the deadline. There are many reasons for this problem but it becomes a serious financial issue for the organizations when the cumulative amount of bad debts reached a staggering figure. This paper reports a study...
In the paper, a scheme is proposed to predict whether the new employees could match their jobs or not, and discrete interval type-2 fuzzy set on time-varying universe is used for evaluating the experts' view of the employees' performance. The evaluation results are sent into a BP neural network to get the predicted value. Finally, the Markov model is adopted to revise the result and achieve a final...
In the context of business-to-business (B2B) commerce, one of the most significant strategic activity for marketing and sales teams is to accurately estimate a company's demand for IT products that can be fulfilled by HP. This metric is known as Account level Total Addressable Market (A-TAM) within the HP community. Accurate A-TAM estimates are vital for developing superior marketing strategies, optimizing...
This paper focuses on the problem of company financial risk warning, which is of great importance in modern company management. As BP neural network is a powerful tool to make state forecasting in complex system, in this paper, we propose a new company financial risk warning approach based on BP neural network. After demonstrating the main characterics of BP neural network, the proposed algorithm...
Recent research in the field of computational social science have shown how data resulting from the widespread adoption and use of social media channels such as twitter can be used to predict outcomes such as movie revenues, election winners, localized moods, and epidemic outbreaks. Underlying assumptions for this research stream on predictive analytics are that social media actions such as tweeting,...
Background: In order to address the challenges in companies having no or limited effort datasets of their own, cross-company models have been a focus of interest for previous studies. Further, a particular domain of investigation has been Web projects. Aim: This study investigates to what extent effort predictions obtained using cross-company (CC) datasets are effective in relation to the predictions...
Q-Gaussian function has the extensive scope of application compared with Gaussian function. It can become many different radial basis functions when we choice the different parameters. Q-Gaussian is chose as kernel to establish the financial early warning model of listing Corporation in this paper. Through the contrast of the Fisher model based on Gaussian kernel, polynomial kernel and the linear...
It is very important for the investors to correctly predict the listing status of listed companies (LSLC) in China. This paper is the first to format the problem of predicting LSLC as a multiclass classification problem, while almost all preliminary research considered it as a binary classification problem. Adaboost method is introduced to solve the problem and the experiment result shows that it...
In response to the worsen credibility of projected profit information, China's Securities Regulatory Commission declared the institution of earnings forecast would transfer from mandatory to voluntary in "The public offering of the securities of the company information disclosure content and format- Prospectus". Since voluntary disclosure is applied to profit forecasts of IPO companies in...
With the rise of e-commerce business, sales forecasting plays an increasingly important role, for accurate and speedy forecasting can help e-commerce companies solve all the uncertainty associated with demand and supply and reduce inventory cost. As the rapid growth in the amount of data, traditional intelligence models like Neural Networks have weakness in terms of speed. In this paper, we introduce...
With the economy developing, effective financial distress prediction methods of artificial intelligence have got more and more attention of the academia. Concept drift in a data flow is another hot research topic. This paper firstly introduces several kinds of existing batch weighted methods for financial distress prediction modeling, and analyzes their shortages. To find a solution to deal with them,...
Along with the increasing prosperity of market economy and the growth of online retail, express shipping service (e.g. FedEx, UPS) is playing an increasingly important role in our daily lives. A thorough understanding of the network structure and the package traffic dynamics of largescale express shipping service network (ExpressNet) is essential for performance evaluation, network optimization, and...
Traditional OTA (Online Travel Agent) is challenged by the Internet and mobile business with the evolution of information. The precise forecasting of ticket sales in OTA companies is beneficial to budget control and service quality. The paper develops an integrated forecasting model by combining the internal factors immediately influencing the ticket sales and the external factors reflecting the ticket...
Customer churn is a major problem that is found in the telecommunications industry because it affects the company's revenue. At the time of the customer churn is taking place, the percentage of data that describes the customer churn is usually low. Unfortunately, the churn data is the data which have to be predicted earlier. The lack of data on customer churn led to the problem of imbalanced data...
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.