BACKGROUND Virtual screening in the form of similarity rankings is often applied in the early drug discovery process to rank and prioritize compounds from a database. This similarity ranking can be achieved with structural similarity measures. However, their general nature can lead to insufficient performance in some application cases. In this paper, we provide a link between ranking-based virt...

Traditionally, information retrieval experts have addressed the problem of information overload. This pursuit has yielded automated electronic bibliographic card catalogs as well as effective search engines for enormous collections including the World Wide Web. Despite advances in this area, librarians lament the ambiguity or absence of metadata required to effectively communicate content. In t...

Systems based on statistical and machine learning methods have been shown to be extremely effective and scalable for the analysis of large amount of textual data. However, in the recent years, it becomes evident that one of the most important direction of improvement in natural language processing (NLP) tasks, like word sense disambiguation, coreference resolution, relation extraction, and othe...

Association rule mining (Agrawal, Imielinski & Swami, 1993) is one of the most important data mining tasks. Initially only simple conjunctions of items were allowed as patterns, but generalizations of the framework to other pattern types such as sequences, trees, graphs etc. have been developed, significantly expanding its applicability. Curiously there has been relatively little effort devoted...

Ontology matching is a growing field of research that is of critical importance for the semantic web initiative. The use of background knowledge for ontology matching is often a key factor for success, particularly in complex and lexically rich domains such as the life sciences. However, in most ontology matching systems, the background knowledge sources are either predefined by the system or h...

The canonical base of a formal context plays a distinguished role in Formal Concept Analysis, as it is the only minimal implicational base known so far that can be described explicitly. Consequently, several algorithms for the computation of this base have been proposed. However, all those algorithms work sequentially by computing only one pseudointent at a time – a fact that heavily impairs th...

The product homomorphism method is a combinatorial tool that can be used to develop polynomial PAC-learning algorithms in predicate logic. Using the product homomorphism method, we show that a single nonrecursive definite Horn clause is polynomially PAC-learnable if the background knowledge is a function-free extensional database over a single binary predicate and the ground atoms in the backgr...

Change your habit to hang or waste the time to only chat with your friends. It is done by your everyday, don't you feel bored? Now, we will show you the new habit that, actually it's a very old habit to do that can make your life more qualified. When feeling bored of always chatting with your friends all free time, you can find the book enPDF concurrent zero knowledge with additional background...

The use of statistical measures to constrain generalisa-tion in learning systems has proved successful in many domains, but can only be applied where large numbers of examples exist. In domains where few training examples are available, other mechanisms for constraining gener-alisation are required. In this paper, we propose a representation of background knowledge based on arguments for and ag...