Prioritized Repairing and Consistent Query Answering in Relational Databases

A consistent query answer in an inconsistent database is an answer obtained in every (minimal) repair. The repairs are obtained by resolving all conflicts in all possible ways. Often, however, the user is able to provide a preference on how conflicts should be resolved. We investigate here the framework of preferred consistent query answers, in which user preferences are used to narrow down the set of repairs to a set of preferred repairs. We axiomatize desirable properties of preferred repairs. We present three different families of preferred repairs and study their mutual relationships. Finally, we investigate the complexity of preferred repairing and computing preferred consistent query answers.Comment: Accepted to the special SUM'08 issue of AMA

HoloDetect: Few-Shot Learning for Error Detection

We introduce a few-shot learning framework for error detection. We show that data augmentation (a form of weak supervision) is key to training high-quality, ML-based error detection models that require minimal human involvement. Our framework consists of two parts: (1) an expressive model to learn rich representations that capture the inherent syntactic and semantic heterogeneity of errors; and (2) a data augmentation model that, given a small seed of clean records, uses dataset-specific transformations to automatically generate additional training data. Our key insight is to learn data augmentation policies from the noisy input dataset in a weakly supervised manner. We show that our framework detects errors with an average precision of ~94% and an average recall of ~93% across a diverse array of datasets that exhibit different types and amounts of errors. We compare our approach to a comprehensive collection of error detection methods, ranging from traditional rule-based methods to ensemble-based and active learning approaches. We show that data augmentation yields an average improvement of 20 F1 points while it requires access to 3x fewer labeled examples compared to other ML approaches.Comment: 18 pages

Alpha Entanglement Codes: Practical Erasure Codes to Archive Data in Unreliable Environments

Data centres that use consumer-grade disks drives and distributed peer-to-peer systems are unreliable environments to archive data without enough redundancy. Most redundancy schemes are not completely effective for providing high availability, durability and integrity in the long-term. We propose alpha entanglement codes, a mechanism that creates a virtual layer of highly interconnected storage devices to propagate redundant information across a large scale storage system. Our motivation is to design flexible and practical erasure codes with high fault-tolerance to improve data durability and availability even in catastrophic scenarios. By flexible and practical, we mean code settings that can be adapted to future requirements and practical implementations with reasonable trade-offs between security, resource usage and performance. The codes have three parameters. Alpha increases storage overhead linearly but increases the possible paths to recover data exponentially. Two other parameters increase fault-tolerance even further without the need of additional storage. As a result, an entangled storage system can provide high availability, durability and offer additional integrity: it is more difficult to modify data undetectably. We evaluate how several redundancy schemes perform in unreliable environments and show that alpha entanglement codes are flexible and practical codes. Remarkably, they excel at code locality, hence, they reduce repair costs and become less dependent on storage locations with poor availability. Our solution outperforms Reed-Solomon codes in many disaster recovery scenarios.Comment: The publication has 12 pages and 13 figures. This work was partially supported by Swiss National Science Foundation SNSF Doc.Mobility 162014, 2018 48th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN

The Influence of Trust in Traditional Contracting: Investigating the "Lived Experience" of Stakeholders

The traditional procurement approach is ever-present within the construction industry. With fundamental design principles founded on definitive risk allocation, this transactional based approach fails to acknowledge or foster the cooperative relationships considered to be vital to the success of any project. Contractual design encourages stakeholders to defend their own individual interest to the likely detriment of project objectives. These failings are not disputed, however, given that trust is a fundamental requirement for human interaction the influence of trust is potentially important in terms of stakeholder relationships and ultimate project success. Trust is therefore examined within this context. A conceptual framework of trust is presented and subsequently used to code and analyse detailed, semi-structured interviews with multiple stakeholders from different projects. Using a phenomenological investigation of trust via the lived experiences of multiple practitioners, issues pertaining to the formation and maintenance of trust within traditionally procured construction projects are examined. Trust was found to be integral to the lived experiences of practitioners, with both good and bad relationships evident within the constructs of traditional procurement mechanisms. In this regard, individual personalities were considered significant, along with appropriate risk identification and management. Communication, particularly of an informal nature, was also highlighted. A greater emphasis on project team selection during the initial stages of a project would therefore be beneficial, as would careful consideration of the allocation of risk. Contract design would also be enhanced through prescriptive protocols for developing and maintaining trust, along with mandated mechanisms for informal communication, particularly when responding to negative events. A greater understanding regarding the consequences of lost trust and the intricacies of trust repair would also be of value. 

A grounded theory study of factors and conditions associated with customer trust recovery in a retailer

Although in recent years academic interest in trust repair following a breach has grown significantly, we still know very little about how trust repair happens and in what contexts. This study focuses on customer trust repair following a major food adulteration scandal. Through a grounded theory study of customer experiences of real-life trust breakdown and recovery, we identify four factors (absence of further transgressions, positive personal experience with the retailer, the retailer’s normal functioning, and the normal behavior of other customers) and three contextual conditions (passage of time, institutional context, and immediate trust repair strategies) associated with customers’ trust recovery in food retailers. In addition, we show that trust recovery is not necessarily a direct result of the trustee’s trust repair activities, as theorized previously, before discussing the implications of our findings for theory and practice

Design of Automatically Adaptable Web Wrappers

Nowadays, the huge amount of information distributed through the Web motivates studying techniques to\ud be adopted in order to extract relevant data in an efficient and reliable way. Both academia and enterprises\ud developed several approaches of Web data extraction, for example using techniques of artificial intelligence or\ud machine learning. Some commonly adopted procedures, namely wrappers, ensure a high degree of precision\ud of information extracted from Web pages, and, at the same time, have to prove robustness in order not to\ud compromise quality and reliability of data themselves.\ud In this paper we focus on some experimental aspects related to the robustness of the data extraction process\ud and the possibility of automatically adapting wrappers. We discuss the implementation of algorithms for\ud finding similarities between two different version of a Web page, in order to handle modifications, avoiding\ud the failure of data extraction tasks and ensuring reliability of information extracted. Our purpose is to evaluate\ud performances, advantages and draw-backs of our novel system of automatic wrapper adaptation

Banking system soundness is the key to more SME financing. Bruegel Policy Contribution 2013/10, July 2013

The SME access-to-finance problem is not universal in the European Union and there are reasons for the fall in credit aggregates and higher SME lending rates in southern Europe. Possible market failures, high unemployment and externalities justify making greater and easier access to finance for SMEs a top priority. Previous European initiatives were able to support only a tiny fraction of Europe’s SMEs; merely stepping-up these programmes is unlikely to result in a breakthrough. Without repairing bank balance sheets and resuming economic growth, initiatives to help SMEs get access to finance will have limited success. The European Central Bank can foster bank recapitalisation by performing in the toughest possible way the asset quality review before it takes over the single supervisory role. Of the possible initiatives for fostering SME access to finance, a properly designed scheme for targeted central bank lending seems to be the best complement to the banking clean-up, but other options, such as increased European Investment Bank lending and the promotion of securitisation of SME loans, should also be explored