The interaction between humans and knowledge management systems : rethinking the future

In this workshop position paper, we propose a study to understand the importance of knowledge management systems among academics in Saudi higher education institutions, admitting that knowledge workers and Knowledge Management Systems are valuable organizational assets whose interaction should be improved. We intend to understand Saudi academics’ perception toward using the knowledge management system to share their teaching experiences. Based on the findings, we investigate the major research trends in knowledge management systems and give some recommendations for future research

Stigmergic hyperlink's contributes to web search

Stigmergic hyperlinks are hyperlinks with a "heart beat": if used they stay healthy and online; if neglected, they fade, eventually getting replaced. Their life attribute is a relative usage measure that regular hyperlinks do not provide, hence PageRank-like measures have historically been well informed about the structure of webs of documents, but unaware of what users effectively do with the links. This paper elaborates on how to input the users’ perspective into Google’s original, structure centric, PageRank metric. The discussion then bridges to the Deep Web, some search challenges, and how stigmergic hyperlinks could help decentralize the search experience, facilitating user generated search solutions and supporting new related business models.info:eu-repo/semantics/publishedVersio

Random Surfing Without Teleportation

In the standard Random Surfer Model, the teleportation matrix is necessary to ensure that the final PageRank vector is well-defined. The introduction of this matrix, however, results in serious problems and imposes fundamental limitations to the quality of the ranking vectors. In this work, building on the recently proposed NCDawareRank framework, we exploit the decomposition of the underlying space into blocks, and we derive easy to check necessary and sufficient conditions for random surfing without teleportation.Comment: 13 pages. Published in the Volume: "Algorithms, Probability, Networks and Games, Springer-Verlag, 2015". (The updated version corrects small typos/errors

True scale-free networks hidden by finite size effects

We analyze about two hundred naturally occurring networks with distinct dynamical origins to formally test whether the commonly assumed hypothesis of an underlying scale-free structure is generally viable. This has recently been questioned on the basis of statistical testing of the validity of power law distributions of network degrees by contrasting real data. Specifically, we analyze by finite-size scaling analysis the datasets of real networks to check whether purported departures from the power law behavior are due to the finiteness of the sample size. In this case, power laws would be recovered in the case of progressively larger cutoffs induced by the size of the sample. We find that a large number of the networks studied follow a finite size scaling hypothesis without any self-tuning. This is the case of biological protein interaction networks, technological computer and hyperlink networks, and informational networks in general. Marked deviations appear in other cases, especially infrastructure and transportation but also social networks. We conclude that underlying scale invariance properties of many naturally occurring networks are extant features often clouded by finite-size effects due to the nature of the sample data