xn----itbjbanp5adgf8b0d.xn--p1ai/scripts/55.php We test and verify our proposed TagRank and greedy selection algorithm on three real-world datasets and experimental results show that our methods are efficient in terms of precision, recall and F1. Social Networks Influence Maximization Problem has been studied extensively and most have focused on the single influence, while few studies have focused on the Multi-influences co-existence based influence diffusion.
We also elaborate conflict strategies from three different perspectives of propagation rules, customers and producers. To illustrate these issues, we conduct experiments with data from four real datasets, evaluate the performances of the proposed model and algorithms, demonstrate that the final numbers of influential nodes are progressive when MICM uses three different conflict selection strategies.
Information Cascades are fairly important to individual decision making, however, it of lead to adoption of inferior products. Many researches on herd behavior have limited their scope on the phenomenon in capital markets and the behavior of investors, but few of them focus on the herd behavior of agents.
Share this article. Multimedia Interaction and Intelligent User Interfaces. Computer Science Communication Networks. Context and Semantics for Knowledge Management. Lakshmanan, and C. Choose Store. Parent task if any :
This paper aims to employ the evolutionary game theory to explain the cause of the herd behavior of agents in their decision-making process for innovation adoption. Furthermore, the effects of herd behavior on innovation adoption and diffusion are analyzed. A kind of remuneration incentives mechanism is then presented in order to circumvent the herd behavior of agents.
Last but not the least, a case study on the innovation adoption of e-business enterprises in China has been conducted to demonstrate the effectiveness of the proposed methods. Customer Relationship Management CRM has attracted much attention due to the high competition in the retail trade. Meanwhile, data mining has great potential to improve the effectiveness of CRM, since the data volume of customers is drastically increasing. In this paper, we firstly propose a logic structure of the retail CRM system, and thus discuss several data mining techniques, i.
Last but not the least, several sub-fields of CRM that are suitable to the application of data mining techniques are discussed. As can be seen from this paper, the retailers must strengthen the application of data mining technology research in order to support the management decision-making and improve the level of information management. Although the grain industry is a traditional businesses, grain storage, distribution, trading and sales model have occurred remarkable change through the application of information technologies.
In this paper, the representative technologies applied in the grain circulation are first introduced and analyzed. Then, the existing problems in grain informatization are discussed based on the statistics data. Finally, the develop trend and future researching fields are analyzed.
With emergence and development of Web2. In the state-of-the-art retrieval methods, geo-tag and visual feature-based image retrieval has not been touched so far.
In this paper, we present an efficient location-based image retrieval method by conducting the search over combined geotag- and visual-feature spaces. In this retrieval method, a cost-based query optimization scheme is proposed to optimize the query processing. Different from conventional image retrieval methods, our proposed retrieval algorithm combines the above two features to obtain an uniform measure.
Comprehensive experiments are conducted to testify the effectiveness and efficiency of our proposed retrieval and indexing methods respectively. There is no specific plugins required for the framework that extends the availability of the LiDAR data for agriculture related applications.
The experimental results demonstrate the online visualization results of two types of LiDAR point clouds for the agriculture fields. Large-screen intelligent display platform is based on the modern computer technology such as Internet technology, virtualization technology, and etc. Run-Time data visualization can help understand the relationships of different datas and improve the user experience.
It includes social networks, blogs, forum discussions and micro-blogs. Users of social media generate a huge amount of comments on a daily basis.
Due to this revolution, most researches are now focusing on extracting meaningful information from social media to better understand the user's attitude. Sentiment analysis and opinion mining are fields of text mining that focus on extracting and analyzing the emotions and opinions of the users with respect to specific topic.
Editors: Ramzan, N., van Zwol, R., Lee, J.-S., Clüver, K., Hua, X.-S. (Eds.) This comprehensive text/reference examines in depth the synergy between multimedia content analysis, personalization, and next-generation networking. The book demonstrates how this integration can result. The social Web (Web ) changed the way people communicate, now a large number of online tools and platforms, such as participative encyclopedias (e.g.
Many approaches are proposed to extract opinions and classify them based on its polarities as positive, negative or neutral. Most works on sentiment analysis are done over English language, but a few of them focused on Arabic language. In this paper, we review many researches concerned with sentiment analysis over social media in Arabic language, and analyzed them by their methods, tools, and techniques. All these user-generated contents need not only to be indexed and searched in effective and scalable ways, but they also provide a huge number of meaningful data, metadata that can be used as clues of evidences in a number of tasks related particularly to information retrieval.
Indeed, these user-generated contents have several interesting properties, such as diversity, coverage and popularity that can be used as wisdom of crowds in search process. This talk will provide an overview of this research field.
We particularly describe some properties and specificities of these data, some tasks that handle these data, we especially focus on two tasks namely searching in social media ranking models for social IR, micro blog search, forum search, real time social search and exploiting social data to improve a search.