LivingKnowledge goal is to bring a new quality into search and knowledge management technology for more concise, complete and contextualised search results.
The paper “Detecting and Exploiting Stability in Evolving Heterogeneous Information Spaces” co-written by G. Papadakis, G. Giannakopoulosy, C. Niederée, T. Palpanas and W. Nejdl has been published in the 11th ACM/IEEE Joint Conference on Digital Libraries JCDL, on June 2011, in Ottawa, Canada.
Individuals contribute content on the Web at an unprecedented rate, accumulating immense quantities of (semi-) structured data. Wisdom of the Crowds theory advocates that such information (or parts of it) is constantly overwritten, updated, or even deleted by other users, with the goal of rendering it more accurate, or up-to-date. This is particularly true for the collaboratively edited, semi-structured data of entity repositories, whose entity proles are consistently kept fresh. Therefore, their core information that remain stable with the passage of time, despite being reviewed by numerous users, are particularly useful for the description of an entity.
Based on the above hypothesis, we introduce a classication scheme that predicts, on the basis of statistical and content patterns, whether an attribute (i.e., name-value pair) is going to be modied in the future. We apply our scheme on a large, real-world, versioned dataset and verify its effectiveness. Our thorough experimental study also suggests that reducing entity proles to their stable parts conveys signicant benets to two common tasks in computer science: information retrieval and information integration.