This paper presents a novel approach for Linked Data-based recommender systems by means of semantic patterns. We associate to each pattern the rating of the arrival book (0 or 1) and compute user profiles by aggregating, for each book in the user training set, the ratings of all the patterns pointing to that book. Ratings are aggregated by estimating the expected value of a Beta distribution de...

We present a new abstraction technique for the exploration of graph transformation systems with infinite state spaces. This technique is based on patterns, simple graphs describing structures of interest that should be preserved by the abstraction. Patterns are collected into pattern graphs, layered graphs that capture the hierarchical composition of smaller patterns into larger ones. Pattern g...

The support vector data description (SVDD) is one of the best-known one-class support vector learning methods, in which one tries the strategy of using balls defined on the feature space in order to distinguish a set of normal data from all other possible abnormal objects. The major concern of this letter is to extend the main idea of SVDD to pattern denoising. Combining the geodesic projection...

People’s demands are escalating with technology advances. Now, people are not happy with only text or voice messages, they like to see video as well. Video transmission through limited bandwidth, for example, an existing telephone line, requires an efficient video coding technique. Unfortunately, existing video coding standards have some limitations due to this demand. Recently, a pattern-based...

Semantic alignment between ontologies is a crucial task for information integration. There are many ongoing efforts to develop matching systems implementing various alignment techniques but it is impossible to predict what strategy is most successful for an application domain or a given pair of ontologies. Very often the quality of the results could be improved by considering the specificities ...

Devising fast and scalable algorithms, able to crunch huge amount of data, was for many years one of the main goals of data mining research. But then we realized that this was not enough. It does not matter how efficient such algorithms can be, the results we obtain are often of limited use in practice. Typically, the knowledge we seek is in a small pool of local patterns hidden within an ocean...

data types (ADTs) [WB01] are used in software applications to model real world entities from the application domain. An ADT can be implemented using different data structures. The study of data structures and the algorithms that manipulate them is among the most fundamental topics in computer science [Mou01]. Most of what computer systems spend their time doing is storing, accessing, and manipu...

In this paper, we study texture metamorphosis, or how to generate texture samples that smoothly transform from a source texture image to a target. We propose a patternbased approach to specify the feature correspondence between two textures, based on the observation that many texture images have stochastically distributed patterns which are similar to each other. First, the user selects a patte...

It has been argued that much of human intelligence can be viewed as the process of matching stored patterns. In particular, it is believed that chess masters use a pattern{based knowledge to analyze a position, followed by a pattern{based controlled search to verify or correct the analysis. In this paper, a rst{order system, called PAL, that can learn patterns in the form of Horn clauses from s...