Helsinki Institute for Information Technology

About: Helsinki Institute for Information Technology is a facility organization based out in Espoo, Finland. It is known for research contribution in the topics: Population & Bayesian network. The organization has 630 authors who have published 1962 publications receiving 63426 citations.

Premise Set Caching for Enumerating Minimal Correction Subsets

Abstract: Methods for explaining the sources of inconsistency of overconstrained systems find an ever-increasing number of applications, ranging from diagnosis and configuration to ontology debugging and axiom pinpointing in description logics. Efficient enumeration of minimal correction subsets (MCSes), defined as sets of constraints whose removal from the system restores feasibility, is a central task in such domains. In this work, we propose a novel approach to speeding up MCS enumeration over conjunctive normal form propositional formulas by caching of so-called premise sets (PSes) seen during the enumeration process. Contrasting to earlier work, we move from caching unsatisfiable cores to caching PSes and propose a more effective way of implementing the cache. The proposed techniques noticeably improves on the performance of state-of-the-art MCS enumeration algorithms in practice.

Secure Hierarchical VPLS Architecture for Provider Provisioned Networks

Abstract: Virtual private LAN service (VPLS) is a Layer 2 virtual private network technique that has gained enormous popularity in industrial networks. However, the deployment of legacy VPLS architectures in large-scale networks is challenging due to unresolved security and scalability issues. In this paper, we propose a novel hierarchical VPLS architecture based on host identity protocol. The proposed architecture tackles both security and scalability issues in legacy VPLS architectures. It secures the VPLS network by delivering vital security features such as authentication, confidentiality, integrity, availability, and secured control protocol. The security analysis and simulation results confirm that the proposed architecture is protected from various IP-based attacks as well. Theoretical analysis and simulation results have also verified that the proposed architecture provides scalability in control, forwarding, and security planes. Finally, the data plane performance of the proposed architecture is measured in a real-world testbed implementation.

Association of social isolation, loneliness, and genetic risk with incidence of dementia: UK Biobank cohort study

Abstract: Objective To examine the associations of social isolation and loneliness with incident dementia by level of genetic risk. Design Prospective population-based cohort study. Setting and participants 155 074 men and women (mean age 64.1, SD 2.9 years) from the UK Biobank Study, recruited between 2006 and 2010. Main exposures Self-reported social isolation and loneliness, and polygenic risk score for Alzheimer’s disease with low (lowest quintile), intermediate (quintiles 2 to 4), and high (highest quintile) risk categories. Main outcome Incident all-cause dementia ascertained using electronic health records. Results Overall, 8.6% of participants reported that they were socially isolated and 5.5% were lonely. During a mean follow-up of 8.8 years (1.36 million person-years), 1444 (0.9% of the total sample) were diagnosed with dementia. Social isolation, but not loneliness, was associated with increased risk of dementia (hazard ratio 1.62, 95% confidence interval 1.38 to 1.90). Of the participants who were socially isolated and had high genetic risk, 4.2% (2.9% to 5.5%) were estimated to develop dementia compared with 3.1% (2.7% to 3.5%) in participants who were not socially isolated but had high genetic risk. The corresponding estimated incidence in the socially isolated and not isolated were 3.9% (3.1% to 4.6%) and 2.5% (2.2% to 2.6%) in participants with intermediate genetic risk. Conclusion Socially isolated individuals are at increased risk of dementia at all levels of genetic risk. What is already known on this topic Social isolation and loneliness have been associated with increased risk of dementia It is not known whether this risk is modified or confounded by genetic risk of dementia What this study adds This is the first study to show that social isolation is associated with increased risk of dementia across the spectrum of genetic risk Loneliness, although considered as a significant risk for multiple health problems, seems to be associated with dementia only when combined with high genetic risk

Finding relational redescriptions

Abstract: We introduce relational redescription mining, that is, the task of finding two structurally different patterns that describe nearly the same set of object pairs in a relational dataset. By extending redescription mining beyond propositional and real-valued attributes, it provides a powerful tool to match different relational descriptions of the same concept. We propose an alternating scheme for solving this problem. Its core consists of a novel relational query miner that efficiently identifies discriminative connection patterns between pairs of objects. Compared to a baseline Inductive Logic Programming (ILP) approach, our query miner is able to mine more complex queries, much faster. We performed extensive experiments on three real world relational datasets, and present examples of redescriptions found, exhibiting the power of the method to expressively capture relations present in these networks.

CHICO: A Compressed Hybrid Index for Repetitive Collections

Abstract: Indexing text collections to support pattern matching queries is a fundamental problem in computer science. New challenges keep arising as databases grow, and for repetitive collections, compressed indexes become relevant. To successfully exploit the regularities of repetitive collections different approaches have been proposed. Some of these are Compressed Suffix Array, Lempel-Ziv, and Grammar based indexes. In this paper, we present an implementation of an hybrid index that combines the effectiveness of Lempel-Ziv factorization with a modular design. This allows to easily substitute some components of the index, such as the Lempel-Ziv factorization algorithm, or the pattern matching machinery. Our implementation reduces the size up to a $$50\,\%$$50% over its predecessor, while improving query times up to a $$15\,\%$$15%. Also, it is able to successfully index thousands of genomes in a commodity desktop, and it scales up to multi-terabyte collections, provided there is enough secondary memory. As a byproduct, we developed a parallel version of Relative Lempel-Ziv compression algorithm.