Showing papers in "Information Systems in 2013"

TL;DR: This paper presents an overview of techniques that allow the linking of databases between organizations while at the same time preserving the privacy of these data, and presents a taxonomy of PPRL techniques to characterize these techniques along 15 dimensions.

TL;DR: This work proposes methods to derive a text-based rating from the body of the reviews, and uses these techniques to make fine-grained predictions of user sentiments towards the individual topics covered in reviews with good accuracy.

TL;DR: A formally specified well-formedness condition on GSM models is introduced that guarantees the equivalence of the three formulations of the GSM operational semantics while permitting commonly arising patterns for using GSM constructs to model business operations.

TL;DR: In this paper, the PPINOT metamodel is proposed to define PPIs in a way that is unambiguous and highly expressive, understandable by technical and non-technical users and traceable with the business process.

TL;DR: The method, based on the concept of space stratification, efficiently identifies the different densities in the dataset and, accordingly, ranks the objects of the original space and performs a density based clustering taking into account the reverse-nearest-neighbor of the objects.

TL;DR: The sampling algorithm proved to be the most effective solution, and was applied to a real log, and compared the resulting detected anomalous traces with the ones detected by a different procedure that relies on manual choices.

TL;DR: The artifact-centric approach to model compliance rules is extended to model Compliance by design and it is shown how compliant business processes can be synthesized automatically.

TL;DR: A new linear time algorithm for computing small SLCF tree grammars, called TreeRePair, is presented and it is shown that it greatly outperforms the best known previous algorithm BPLEX.

TL;DR: This work presents a crowdsourcing marketplace that matches complex tasks, requiring multiple skills, to suitable workers and presents auction mechanisms that help to correctly estimate workers and to evolve skills that are needed in the system.

TL;DR: An online homebuyer's search program is developed, based on an investigation of search behaviors, and a user-oriented recommendation system for real estate websites is implemented via a combination of case-based reasoning and an ontological structure.

TL;DR: This paper proposes the notion of business process families by building upon the well-known software engineering discipline-software product line engineering, and proposes a correct validation algorithm ensuring that each member of a business process family adheres to the core intended behavior that is specified in the process model template.

TL;DR: This paper presents a construction for (minimal) perfect hash functions that combines theoretical analysis, practical performance, expected linear construction time and nearly optimal space consumption for the data structure.

TL;DR: CARVE (Context-Aware Relational View dEfinition), a methodology for context-aware view definition, well-suited for the design of modern, dynamic applications that, in different environments and situations, need to access different portions of data.

TL;DR: A blocking approach is introduced that avoids selecting a blocking key altogether, relieving the user from this difficult task and is based on maximal frequent itemsets selection, allowing early evaluation of block quality based on the overall commonality of its members.

TL;DR: A post-processing approach to simplify discovered process models while controlling the balance between overfitting and underfitting is presented.

TL;DR: This work proposes an indexing structure to support fast detection of clones in process model repositories, called RPSDAG, based on a novel combination of a method for process model decomposition, with established graph canonization and string matching techniques.

TL;DR: The Unified Service Description Language (USDL) as discussed by the authors aims at describing services across the human-to-automation continuum, following well-defined requirements which are expressed against a common service discourse and synthesized from currently available service description efforts.

TL;DR: A followee recommender system based on both the analysis of the content of micro-blogs to detect users' interests and in the exploration of the topology of the network to find candidate users for recommendation is proposed.

TL;DR: This paper focuses on the issue of ontological analysis for organizational structure modeling in the ARIS method with an interpretation of the language in terms of real-world entities in the UFO foundational ontology, using a systematic ontology-based analysis approach.

TL;DR: A new agent-based system is proposed, whose architecture allows to compute recommendations of multimedia Web services, considering the effect of the currently exploited device, and some experimental results confirm the high quality of the recommendations generated by the proposed approach.

TL;DR: An instance-based schema matching technique that exploits information overlap in infoboxes across different language editions is presented and a robust similarity measure is presented that can reliably quantify the similarity of strings with mixed types of data.

TL;DR: This paper investigates the effects of four scheduling policies on different flow structures and configurations and experimentally shows that the use of different scheduling policies may improve ETL performance in terms of memory consumption and execution time.

TL;DR: This paper presents a framework that automatically learns and adapts execution models for arbitrary algorithms on any (co-)processor, and uses the execution models to distribute a workload of database operators on available (co-processing devices).

TL;DR: The results suggest that both the use of concept mapping as well as the refining step are acceptable from the point of view of the end user, supporting the claim that this method is viable as an option to reduce some of the difficulties in large scale ontology construction.

TL;DR: The procedure for comparing costs of leasing IT resources in a commercial computing cloud against those incurred in using on-premise resources is presented and enables cloud providers to determine marginal costs in their services' price, and allows users to calculate costs they would incur by executing the same application using their own resources.

TL;DR: This paper studies the problem of efficiently computing the skyline over sliding windows on uncertain data elements against probability thresholds, and characterize the properties of elements to be kept in the computation.

TL;DR: This paper presents an equally contributory multiparty k-means clustering protocol for vertically partitioned data, in which each party equally contributes to k-measures clustering.

TL;DR: This work proposes a temporal model that assigns a time interval to each event to represent all of its possible occurrence times and proposes the formal semantics of such pattern evaluation, two evaluation frameworks, and algorithms and optimizations in these frameworks.

TL;DR: This paper shows how schema mappings, that are obtained automatically using existing matching and mapping generation techniques, can be annotated with metrics estimating their fitness to user requirements using feedback on query results obtained from end users.

TL;DR: It is proved that, for any @d>0 (that is, whenever there is actual uncertainty), (k,@d)-anonymity does not offer trajectory k-anonymsity, that is, it does not hide an original trajectory in a set of k indistinguishable anonymized trajectories.