Persian language is one of the most widely used languages in the Web environment. Hence, the Persian Web includes invaluable information that is required to be retrieved effectively. Similar to other languages, ranking algorithms for the Persian Web content, deal with different challenges, such as applicability issues in real-world situations as well as the lack of user modeling. CF-Rank, as a ...

Low-rank matrix approximation (LRMA) methods have achieved excellent accuracy among today’s collaborative filtering (CF) methods. In existing LRMA methods, the rank of user/item feature matrices is typically fixed, i.e., the same rank is adopted to describe all users/items. However, our studies show that submatrices with different ranks could coexist in the same user-item rating matrix, so that...

For the multisensor stochastic control systems with different measurement matrices and correlated noises, a new weighted measurement fusion (WMF) estimation algorithm is presented by using full-rank decomposition of matrix and weighted least squares theory. The newly presented algorithm can handle the fused filtering, smoothing, and prediction problems for the state in a unified framework and p...

Carbon-fibre-reinforced-polyetherketonketone (CF/PEKK) has attracted increasing interest in the aviation industry due to its self-healing properties and ease of recycle repair. However, machining performance CF/PEKK is not well understood there a lack optimization study for minimizing hole damage improving production efficiency. Here, we report first multi-objective drilling. A hybrid algorithm...

This paper presents the Cholesky factor–alternating direction implicit (CF–ADI) algorithm, which generates a low rank approximation to the solution X of the Lyapunov equation AX + XAT = −BBT . The coefficient matrix A is assumed to be large, and the rank of the righthand side −BBT is assumed to be much smaller than the size of A. The CF–ADI algorithm requires only matrix-vector products and mat...

We describe a case study, which shows how important negative results are in uncovering biased evaluation methodologies. Our research question is how to compare a recommender algorithm that uses an RDF graph to a recommendation algorithm that uses rating data. Our case study uses DBpedia 3.8 and the MovieLens 100k data set. We show that the most popular evaluation protocol in the recommender sys...

Isomap is a well-known nonlinear dimensionality reduction method that highly suffers from computational complexity. Its complexity mainly arises two stages; a) embedding full graph on the data in ambient space, and b) complete eigenvalue decomposition. Although of graphing stage has been investigated by processing methods, decomposition remains bottleneck problem. In this paper, we propose Low-...

In this paper, we investigate some properties on capacity factors, which were proposed to investigate the link failure problem from network coding. A capacity factor (CF) of a network is an edge set, deleting which will cause the maximum flow to decrease while deleting any proper subset will not. Generally, a k-CF is a minimal (not minimum) edge set which will cause the network maximum flow dec...