We compare expert finding approaches that use and combine different types of expertise evidence: content-based expert finding using academic papers, and expert finding using a social citation network between the documents and authors. We evaluate our approaches on a test collection that represents the research output of a typical average-sized academic workgroup. We find that expert finding usi...

Sentiment analysis is an emerging research field. One of the major tasks of sentiment analysis is building sentiment lexicons and calculating their scores, which is an essential job that provides “material” for all sentiment analysis problems. In this paper, we propose a fuzzy language computation by taking linguistic context into account to provide an effective method for computing the sentime...

Text information embedded in video frames play an important role in content-based multimedia indexing and retrieval as a result the automatic detection of texts from videos has gained wide attention in recent years. In this paper an effective method for text detection and localization approach based on Log Gabor filter and Block Eigen map analysis is proposed. Log Gabor filter response is used ...

We analyze the schema theorem and the building block hypothesis using a recently derived, exact schemata evolution equation. We derive a new schema theorem based on the concept of effective fitness showing that schemata of higher than average effective fitness receive an exponentially increasing number of trials over time. The building block hypothesis is a natural consequence in that the equat...

Learning Granger causality for general point processes is a very challenging task. In this paper, we propose an effective method, learning Granger causality, for a special but significant type of point processes — Hawkes process. According to the relationship between Hawkes process’s impact function and its Granger causality graph, our model represents impact functions using a series of basis f...

In this paper we address the problem of high-dimensionality for data that lies on complex manifolds. In high-dimensional spaces, distances between the nearest and farthest neighbour tend to become equal. This behaviour hardens data analysis, such as clustering. We show that distance transformation can be used in an effective way to obtain an embedding space of lower-dimensionality than the orig...

We present an effective method for simulating wall-bounded multiphase flows consisting of N (N > 2) immiscible incompressible fluids with different densities, viscosities and pairwise surface tensions. The N-phase physical formulation is based on a modified thermodynamically consistent phase field model that is more general than in a previous work, and it is developed by considering the reducti...

Documents Clustering is a technique in which relationships between sets of documents are being automatically discovered and documents are divided into groups of similar specimens. The groups that are created during the process of clustering should be specified by the high degree of similarity between the elements that belong to the same group and low degree of similarity between the elements th...

Automatic software verification relies on constructing, for a given program, an abstract model that is (1) abstract enough to avoid state-space explosion and (2) precise enough to reason about the specification. Counterexample-guided abstraction refinement is a standard technique that suggests to extract information from infeasible error paths, in order to refine the abstract model if it is too...

A semiparametric regression model of a q-dimensional multivariate response y on a p-dimensional covariate x is considered. A new approach is proposed based on sliced inverse regression (SIR) for estimating the effective dimension reduction (EDR) space without requiring a prespecified parametric model. The convergence at rate √ n of the estimated EDR space is shown. The choice of the dimension o...