The Wikipedia is characterized by its dense link structure and a huge amount of articles in different languages, which make it a notable Web corpus for knowledge extraction and mining, in particular for mining the multilingual associations. In this paper, motivated by a psychological theory of word meaning, we propose a graphbased approach to constructing a cross-language association dictionary...

We document a causal impact of online user-generated information on real-world economic outcomes. In particular, we conduct randomized field experiment to test whether additional content Wikipedia pages about cities affects tourists' choices overnight visits. Our treatment adding increases stays in treated compared nontreated cities. The is largely driven by improvements shorter and relatively ...

The article presents experiments on mining Wikipedia for extracting SMT useful sentence pairs in three language pairs. Each extracted sentence pair is associated with a cross-lingual lexical similarity score based on which, several evaluations have been conducted to estimate the similarity thresholds which allow the extraction of the most useful data for training three-language pairs SMT system...

We describe a new method of reduced Google matrix which allows to establish direct and hidden links between a subset of nodes of a large directed network. This approach uses parallels with quantum scattering theory, developed for processes in nuclear and mesoscopic physics and quantum chaos. The method is applied to the Wikipedia networks in different language editions analyzing several groups ...

The challenges of commons based peer production are usually associated with the development of complex software projects such as Linux and Apache. But the case of open content production should not be treated as a trivial one. For instance, while the task of maintaining a collection of encyclopedic articles might seem negligible compared to the one of keeping together a software system with its...

The Word Wide Web is a continuous challenge to machine learning. Established approaches have to be enhanced and new methods be developed in order to tackle the problem of finding and organising relevant information. It has often been motivated that semantic classifications of input documents help solving this task. But while approaches of supervised text categorisation perform quite well on gen...

The outgrowth of social networks in the recent years has resulted in opportunities for interesting data mining problems, such as interest or friendship recommendations. A global ontology over the interests specified by the users of a social network is essential for accurate recommendations. We propose, evaluate and compare three approaches to engineering a hierarchical ontology over user intere...