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The main aim of this study is to assess the potential copyright infringement risks (CIR) in information resources by using the extension theory. At first, the analytic hierarchy process (AHP) is employed to determine the weights of the existing early warning indicators system. Secondly, a model is built based on the extension theory to evaluate the potential CIR in information resources. Finally,...
Large online music collections often frustrate users and have increased the importance of recommender systems. This has led to interesting problem of automated playlist generation. Most of the existing playlist's compare a pair songs based on low-level/mid-level features and calculate the similarity. These systems lack user perception of music. This work supplements such existing systems by providing...
Many universities conduct student evaluations, with the goal of encouraging improvement in teaching. Evaluations are subjective assessments by students, and do not directly evaluate specific teaching methods or behaviors as being good or bad. Instructors therefore cannot necessarily easily relate evaluations to areas for teaching improvement. To address this issue, we proposed a teaching behavior...
Studying the neuronal pattern of interactions may help us to understand the underlying processes of functional connectivity in the brain. Simultaneous recording of multiple neuronal activities using a multi electrode array provides rich neuronal signals and requires appropriate statistical and computational methods to demonstrate any connectivity. Using ordinary coherence to infer true connectivity...
Dealing with multiple labels is a supervised learning problem of increasing importance. Multi-label classifiers face the challenge of exploiting correlations between labels. While in existing work these correlations are often modelled globally, in this paper we use the divide-and-conquer approach of decision trees which enables taking local decisions about how best to model label dependency. The resulting...
The breach of privacy in encrypted instant messenger (IM) service is a serious threat to user anonymity. Performance of previous de-anonymization strategies was limited to 65%. We perform network de-anonymization by taking advantage of the cause-effect relationship between sent and received packet streams and demonstrate this approach on a data set of Yahoo! IM service traffic traces. An investigation...
This paper examines users who are common to two popular online social networks, Instagram and Ask.fm, That are often used for cyber bullying. An analysis of the negativity and positivity of word usage in posts by common users of these two social networks is performed. These results are normalized in comparison to a sample of typical users in both networks. We also examine the posting activity of common...
Colleges and universities are increasingly interested in tracking student progress as they monitor and work to improve their retention and graduation rates. Ideally, early indicators of student progress, or lack thereof, can be used to provide appropriate interventions that increase the likelihood of student success. In this paper we present a framework that uses data mining and machine learning techniques,...
This paper presents a signal processing technique for segmenting short speech utterances into unvoiced and voiced sections and identifying points where the spectrum becomes steady. The segmentation process is part of a system for deriving musculoskeletal articulation data from disordered utterances, in order to provide training feedback. The functioning of the signal processing technique has been...
In this paper, the sentiment correlation between color and speech has been investigated aiming at multimodal expression of information embedded in speech. To cope with the necessity of information specification for further analyses and control of speech so called para-linguistic information, we carried out an sentiment experiment on the correlations between speech characteristics and color attributes...
We consider the problem of joining two long time series based on their most correlated segments. Two time series can be joined at any locations and for arbitrary length. Such join locations and length provide useful knowledge about the synchrony of the two time series and have applications in many domains including environmental monitoring, patient monitoring and power monitoring. However, join on...
As described in Michael Lewis' Money ball: The Art of Winning an Unfair Game, a baseball player's On Base Percentage is a good metric for rating players' usefulness or productivity. What metrics can be used for gauging a professor's performance? Is there a correlation between salary and these metrics? Are these metrics more accurate for certain fields of study? Is the currently popular practice of...
The spectral radius of a network graph is the largest Eigen value of the adjacency matrix of the graph. We hypothesize the spectral radius to be a measure of the variation in the degrees of the nodes. In this pursuit, we define a metric called the spectral radius ratio for node degree as the ratio of the spectral radius to the average node degree. We validate our hypothesis by determining this metric...
We revisit the problem of predicting directional movements of stock prices based on news articles: here our algorithm uses daily articles from The Wall Street Journal to predict the closing stock prices on the same day. We propose a unified latent space model to characterize the "co-movements" between stock prices and news articles. Unlike many existing approaches, our new model is able...
Using page-level metrics of a randomly selected group of 15,625 among the top 100,000 Face book check-in locations which rank high in terms of customer engagement, we explore if the short-term dynamical information on these metrics could deliver, via a clustering approach, some new insights for marketing decision making. Using a highly-scalable clustering algorithm, statistical methods, and combinatorial...
With the rapid development of online learning, users have more and more diverse ways to learning. The advantage of online learning is that the e-learners' behaviors can be completely recorded in the log events. So learning analytics can be made on these data. More than 500 freshmen used Moodle to study our "C program" course each year. So a large number of learning data have been collected...
It is well-known that locative prepositions are used to make temporal expressions, and that they have been intensively studied in theoretical, cognitive and psycho-linguistics. However, there have been few attempts to develop a theoretical framework to deal with linguistic data on the locative prepositions (see Piñón (1997), Zwarts and Winter (1997) and Zwarts (2000) for a vector semantics to capture...
In this paper we explore and analyse the heterogeneity existent within a seemingly homogenous sample of online consumer behaviours in terms of their demographic profile. The data from a sample of 371 survey respondents is clustered using various distance functions and a clustering algorithm. In doing so, the respondents are clustered based on their response profiles to online behaviour questions rather...
This paper proposes a method for contour completion of a skew-symmetry object which is partly occluded by other objects. The proposed method assumes that skew symmetry of a shape can be measured by correlation with its reflection on a no orthogonal plane. Under the assumption, the method estimates a skew-symmetry axis and a skew transverse angle, and then reflects the contour to the estimated axis...
An ever increasing impact and amount of network attacks have driven many organizations to deploy various network monitoring and analysis systems such as honeypots, intrusion detection systems, log analyzers and flow monitors. Besides improving these systems a logical next step is to collect and correlate alerts from multiple systems distributed across organizations. The idea is to leverage a joint...
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