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The search for Trendsetters in social networks turned to be a complex research topic that has gained much attention. The work here presented uses big data analytics to find who better spreads the word in a social network and is innovative in their choices. The analysis on the Yelp platform can be divided in three parts: first, we justify the use of Tips frequency as a variable to profile business...
Pairs trading is a market-neutral strategy that exploits historical correlation between stocks to achieve statistical arbitrage. Existing pairs-trading algorithms in the literature require rather restrictive assumptions on the underlying stochastic stock-price processes and the so-called spread function. In contrast to existing literature, we consider an algorithm for pairs trading which requires...
With the proliferation of smart phones, mobile applications (APPs) are increasingly being used for mobile work and entertainment. In order to satisfy people's various demands, there are enormous mobile applications being delivered through different mobile application markets. This brings markets owners huge opportunities and tough challenges simultaneously. It is very difficult to find proper APPs...
Real-time accurate ball tracking in sport games is important for automated game analysis and augment reality display. It is very difficult because the ball is usually very small, with few features and large variance appearance, sudden motion change and occlusion occurs quite often as well as the background is noisy. Badminton is one of the fastest ball games in the world and so tracking a shuttlecock...
On-board data compression is a critical task that has to be carried out with restricted computational resources for remote sensing applications. This paper proposes an improved algorithm for onboard lossless compression of hyperspectral images, which combines low encoding complexity and high-performance. This algorithm is based on hybrid prediction. In the proposed work, the decorrelation stage reinforces...
Today internet usage has seen tremendous growth. As English is the primary language, documents are mostly available in English language. In India, Hindi is the prevalent language and user wants to access data in Hindi. For the language processing we are required to get the exact sense of polysemous word interpreting the meaning in a particular context. To disambiguate the meaning of the polysemous...
To help analysts sift through large numbers of documents, we suggest an auto-highlighting system that computationally identifies the topmost salient sentences in each document as a form of summary and rapid comprehension aid. We conducted a user study to gather data about the types of sentences people highlight when reading and comprehending text. Our study focuses not only on the comparison between...
Sharing information and resources on the Internet has become an important activity for education. The use of ubiquitous devices makes possible for learning participants to be engaged in an open and connected social environment, and also allows the learning activities to be performed at any time and any places. In this study, the discovery of correlation among shared resources is concentrated. A hypothetical...
The miss of context data is an inevitable problem of context information processing mechanism, the interpolation technique of missing data is also a research hotspot in data mining. However, the existing interpolation technique of missing data is not suitable for the flow data form of context information that does not make full use of data relevance between every collecting sensor. Moreover, that...
The recentH.264/AVCvideo coding standard provides a higher coding efficiency than previous standards. H.264/AVCachieves a bit rate saving of more than 50 % with many new technologies, but it shows very heavy computational complexity. In this paper, a fast mode decision scheme for inter-frame coding is proposed to reduce the computational complexity for H.264/AVC video encoding system. To reduce the...
The widespread use of positioning technologies ranging from GSM and GPS to WiFi devices, tend to produce large-scale datasets of trajectories, representing the movement of travelling entities. Several applications may benefit from mining such datasets. However, mining results only become truly useful and meaningful for the end user when the intrinsically complex nature of the movement data in terms...
This paper proposes a new negative correlation learning (NCL) algorithm, called AdaBoost.NC, which uses an ambiguity term derived theoretically for classification ensembles to introduce diversity explicitly. All existing NCL algorithms, such as CELS and NCCD, and their theoretical backgrounds were studied in the regression context. We focus on classification problems in this paper. First, we study...
Location obfuscation using cloaking regions preserves location anonymity by hiding the true user among a set of other equally likely users. Furthermore, a cloaking region should also guarantee that the type of queries issued by users within the region are mutually diverse enough. The first requirement is fulfilled by satisfying location k-anonymity while the second one is ensured by satisfying query...
Translation Memory (TM) consists of a collection of previously translated units of text that may prove useful in the translation of new text. The main problem faced by translators who wish to take advantage of TM is that, although search tools do exist, there is no standardized way of effectively ranking search results. This paper proposes a method for effectively ranking TM search results together...
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